Datasets:
truongpdd
/
BIRD_for_augment_sql2question

Dataset card Viewer Files Community
1
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int64
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question How many office supply orders were made by Cindy Stewart in the south superstore? Clarification: office supply refers to Category = 'Office Supplies'
[query_database(**{'query': 'SELECT COUNT(*) FROM south_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T1.`Product ID` WHERE T3.Category = 'Office Supplies' AND T2.`Customer Name` = 'Cindy Stewart''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,408
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question What product category that Sam Craven ordered from the central and east superstore? Clarification:
[query_database(**{'query': 'SELECT DISTINCT T3.Category FROM east_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T1.`Product ID` LEFT JOIN central_superstore AS T4 ON T3.`Product ID` = T4.`Product ID` WHERE T2.`Customer Name` = 'Sam Craven''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,412
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question What is the total profit of "Memorex Froggy Flash Drive 8 GB in south superstore? Clarification: "Memorix Froggy Flash Drive 8 GB" is the "Product Name"
[query_database(**{'query': 'SELECT SUM(T1.Profit) FROM south_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` GROUP BY T2.`Product Name` = 'Memorix Froggy Flash Drive 8 GB''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,416
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question What is the ratio between customers who live in Texas and customers who live in Indiana? Clarification: live in Texas refers to State = 'Texas'; live in Indiana refers to State = 'Indiana'; Ratio = divide(sum(State = 'Texas'), sum(State = 'Indiana'))
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN State = 'Texas' THEN 1 ELSE 0 END) AS REAL) * 100 / SUM(CASE WHEN State = 'Indiana' THEN 1 ELSE 0 END) FROM people'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,420
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question How many orders were made by Corey Roper in 2015? Clarification:
[query_database(**{'query': 'SELECT COUNT(T2.`Customer ID`) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.`Customer Name` = 'Corey Roper' AND STRFTIME('%Y', T2.`Ship Date`) = '2015''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,424
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question How many orders of O'Sullivan Plantations 2-Door Library in Landvery Oak in central superstore were shipped through the shipping mode with the fastest delivery speed? Clarification: 'O'Sullivan Cherrywood Estates Traditional Bookcase' is the "Product Name"; shipping mode with the fastest delivery speed refers to "Ship Mode" = 'First Class'
[query_database(**{'query': 'SELECT COUNT(DISTINCT T1.`Order ID`) FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Product Name` = 'O''Sullivan Plantations 2-Door Library in Landvery Oak' AND T2.Region = 'Central' AND T1.`Ship Mode` = 'First Class''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question What is the shipment duration for order number CA-2011-134103? Clarification: shipment duration = subtract("Ship Date", "Order Date"); order number CA-2011-134103 refers to "Order ID" = 'CA-2011-134103'
[query_database(**{'query': 'SELECT DISTINCT strftime('%J', `Ship Date`) - strftime('%J', `Order Date`) AS duration FROM central_superstore WHERE `Order ID` = 'CA-2011-134103''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,432
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question Who was the customer in the South Region superstore who bought the most “Hon Multipurpose Stacking Arm Chairs"? Clarification: customer refers to "Customer Name"; “Hon Multipurpose Stacking Arm Chairs" is the "Product Name";
[query_database(**{'query': 'SELECT T2.`Customer Name` FROM south_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T1.`Product ID` WHERE T3.`Product Name` = 'Hon Multipurpose Stacking Arm Chairs' GROUP BY T2.`Customer Name` ORDER BY COUNT(T2.`Customer Name`) DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,436
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question What is the original price of the "Black Avery Flip-Chart Easel Binder"? Clarification: "Black Avery Flip-Chart Easel Binder" is the "Product Name"; original price = divide(Sales, subtract(1, Discount))
[query_database(**{'query': 'SELECT T1.Sales / (1 - T1.Discount) FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.`Product Name` = 'Blackstonian Pencils''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,440
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question What is the highest profit order in the East superstore of customers from Houston, Texas? Clarification: highest profit refers to max(Profit); Houston, Texas refers to City = 'Houston' and State = 'Texas'
[query_database(**{'query': 'SELECT T1.`Order ID` FROM east_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T2.City = 'Houston' AND T2.State = 'Texas' ORDER BY T1.Profit DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,444
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question How many orders were made by Alan Barnes in 2015 at the Central superstore? Clarification: in 2015 refers to "Order Date" = '2015%'
[query_database(**{'query': 'SELECT COUNT(DISTINCT T2.`Order ID`) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.`Customer Name` = 'Alan Barnes' AND STRFTIME('%Y', T2.`Order Date`) = '2015''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,448
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question Who order from the west region on August 12, 2013, and received a discount of 0.2? Clarification: Who refers to "Customer Name"; on August 12, 2013 refers to "Order Date" = '2013-08-12'; discount of 0.2 refers to discount = 0.2
[query_database(**{'query': 'SELECT DISTINCT T2.`Customer Name` FROM west_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T1.`Order Date` = '2013-08-12' AND T1.Discount = 0.2 AND T1.Region = 'West''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,452
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question Among the customers from Houston, Texas, what is the total profit of their orders in the Central region? Clarification: customers from Houston, Texas refers to State = 'Texas' and City = 'Houston'; total profit = sum(Profit)
[query_database(**{'query': 'SELECT SUM(T2.Profit) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T2.`Product ID` WHERE T1.City = 'Houston' AND T1.State = 'Texas' AND T2.Region = 'Central''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,456
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question Provide the product's name of the product with the highest sales in the South region. Clarification: highest sales refers to max(Sales)
[query_database(**{'query': 'SELECT T2.`Product Name` FROM south_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.Region = 'South' ORDER BY T1.Sales DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,460
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ ### Question Among the customers from Indiana, what is the percentage of their purchased orders in the Central region with no discount? Clarification: Indiana refers to State = 'Indiana'; no discount refers to Discount = 0; percentage = divide(sum(Discount) when Discount = 0, count(Discount)) as percentage
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN T2.Discount = 0 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM people AS T1 INNER JOIN central_superstore AS T2 ON T1.`Customer ID` = T2.`Customer ID` WHERE T2.Region = 'Central' AND T1.State = 'Indiana''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE people ( "Customer ID" TEXT, "Customer Name" TEXT, Segment TEXT, Country TEXT, City TEXT, State TEXT, "Postal Code" INTEGER, Region TEXT, primary key ("Customer ID", Region) ) /* 1 example row: SELECT * FROM people LIMIT 1; Customer ID ||Customer Name || Segment || Country || City ||State ||Postal Code || Region AA-10315 || Alex Avila ||Consumer ||United States ||Round Rock ||Texas || 78664 ||Central */ /* column definitions { "Customer ID": "the id of the customers", "Customer Name": "the name of the customers", "Segment": "the segment that the customers belong to", "Country": "the country of people", "City": "the city of people", "State": "the state of people", "Postal Code": "the postal code", "Region": "the region of people" }*/ CREATE TABLE product ( "Product ID" TEXT, "Product Name" TEXT, Category TEXT, "Sub-Category" TEXT, Region TEXT, primary key ("Product ID", Region) ) /* 1 example row: SELECT * FROM product LIMIT 1; Product ID || Product Name || Category ||Sub-Category ||Region FUR-BO-10000330 ||Sauder Camden County Barrister Bookcase, Planked Cherry Finish ||Furniture || Bookcases || West */ /* column definitions { "Product ID": "the id of products", "Product Name": "the name of products", "Category": "the categories of products", "Sub-Category": "the sub-categories of products", "Region": "the region of products" }*/ CREATE TABLE central_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM central_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID || Region || Product ID || Sales ||Quantity ||Discount ||Profit 1 ||CA-2011-103800 ||2013-01-03 ||2013-01-07 ||Standard Class || DP-13000 ||Central ||OFF-PA-10000174 ||16.448 || 2 || 0.2 ||5.5512 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE east_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM east_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID || Sales ||Quantity ||Discount ||Profit 4647 ||CA-2011-141817 ||2013-01-05 ||2013-01-12 ||Standard Class || MB-18085 || East ||OFF-AR-10003478 ||19.536 || 3 || 0.2 || 4.884 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE south_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM south_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 10343 ||CA-2011-106054 ||2013-01-06 ||2013-01-07 ||First Class || JO-15145 || South ||OFF-AR-10002399 ||12.78 || 3 || 0.0 ||5.2398 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/ CREATE TABLE west_superstore ( "Row ID" INTEGER primary key, "Order ID" TEXT, "Order Date" DATE, "Ship Date" DATE, "Ship Mode" TEXT, "Customer ID" TEXT, Region TEXT, "Product ID" TEXT, Sales REAL, Quantity INTEGER, Discount REAL, Profit REAL, foreign key ("Customer ID", Region) references people("Customer ID",Region), foreign key ("Product ID", Region) references product("Product ID",Region) ) /* 1 example row: SELECT * FROM west_superstore LIMIT 1; Row ID || Order ID ||Order Date || Ship Date || Ship Mode ||Customer ID ||Region || Product ID ||Sales ||Quantity ||Discount ||Profit 13583 ||CA-2011-130813 ||2013-01-06 ||2013-01-08 ||Second Class || LS-17230 || West ||OFF-PA-10002005 ||19.44 || 3 || 0.0 ||9.3312 */ /* column definitions { "Row ID": "the unique id for rows", "Order ID": "the unique identifier for the order", "Order Date": "the date of the order", "Ship Date": "the date of the shipment", "Ship Mode": "the ship mode of the order", "Customer ID": "the id of the customer", "Region": "region of the customer's address", "Product ID": "the id of the product", "Sales": "the sales of the product", "Quantity": "the quantity of the product", "Discount": "the discount of the product", "Profit": "the profit that the company got by selling the product" }*/
2,465
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question Did the number of cases with Vehicle as subject weapon increase or decrease from year 2007 to 2008. State the difference. Clarification: number of cases refers to count(case_number); with Vehicle as subject weapon refers to subject_weapon = 'Vehicle'; year 2007 refers to date between '2007-01-01' and '2007-12-31'; year 2008 refers to date between '2008-01-01' and '2008-12-31'
[query_database(**{'query': 'SELECT SUM(IIF(STRFTIME('%Y', date) = '2007', 1, 0)) - SUM(IIF(STRFTIME('%Y', date) = '2008', 1, 0)) FROM incidents WHERE subject_weapon = 'Vehicle''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question From the cases where the subject are male, list the case number and the location and subject status. Clarification: male refers to gender = 'M'
[query_database(**{'query': 'SELECT T1.case_number, T1.location, T1.subject_statuses FROM incidents AS T1 INNER JOIN subjects AS T2 ON T1.case_number = T2.case_number WHERE T2.gender = 'M''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
2,473
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question What is the percentage of subject who are female used the Vehicle as weapon? Clarification: female refers to gender = 'F'; use Vehicle as weapon refers to subject_weapon = 'Vehicle'; percentage = divide(count(case_number where subject_weapon = 'Vehicle'), count(case_number)) where gender = 'F' * 100%
[query_database(**{'query': 'SELECT CAST(SUM(T1.subject_weapon = 'Vehicle') AS REAL) * 100 / COUNT(T1.case_number) FROM incidents T1 INNER JOIN subjects T2 ON T1.case_number = T2.case_number WHERE T2.gender = 'F''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question Of all male officers, what percentage are black officers? Clarification: male refers to gender = 'M'; black refers to race = 'B'; percentage = divide(count(officers where race = 'B'), count(officers)) where gender = 'M' * 100%
[query_database(**{'query': 'SELECT CAST(SUM(race = 'B') AS REAL) * 100 / COUNT(case_number) FROM officers WHERE gender = 'M''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question How many instances were found in June 2015? Clarification: in June 2015 refers to date between '2015-06-01' and '2015-06-30'; record number refers to case_number
[query_database(**{'query': 'SELECT COUNT(case_number) FROM incidents WHERE date BETWEEN '2015-06-01' AND '2015-06-30''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question How many more black female victims than white female victims were discovered? Clarification: black refers to race = 'B'; female refers to gender = 'F'; white refers to race = 'W'; result = subtract(count(victims where race = 'B'), count(victims where race = 'W')) where gender = 'F'
[query_database(**{'query': 'SELECT SUM(race = 'B') - SUM(race = 'W') FROM subjects WHERE gender = 'F''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ ### Question What proportion of male police officers looked into events where people were injured? Clarification: male refers to gender = 'M'; people were injured refers to subject_statuses = 'Injured'; proportion = divide(count(case_number where gender = 'M'), count(case_number)) where subject_statuses = 'Injured' * 100%
[query_database(**{'query': 'SELECT CAST(SUM(T2.gender = 'M') AS REAL) * 100 / COUNT(T1.case_number) FROM incidents T1 INNER JOIN officers T2 ON T1.case_number = T2.case_number WHERE T1.subject_statuses = 'Injured''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE incidents ( case_number TEXT not null primary key, date DATE not null, location TEXT not null, subject_statuses TEXT not null, subject_weapon TEXT not null, subjects TEXT not null, subject_count INTEGER not null, officers TEXT not null ) /* 1 example row: SELECT * FROM incidents LIMIT 1; case_number || date || location ||subject_statuses ||subject_weapon || subjects ||subject_count || officers 031347-2015 ||2015/2/9 ||7400 Bonnie View Road || Deceased || Vehicle ||Luster, Desmond Dwayne B/M || 1 ||Tollerton, Aaron W/M */ /* column definitions { "case_number": "case number", "date": "date", "location": "location", "subject_statuses": "statuses of the victims ", "subject_weapon": "subject weapon", "subjects": "subjects", "subject_count": "subject_count", "officers": "officers" }*/ CREATE TABLE officers ( case_number TEXT not null, race TEXT null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM officers LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Patino || Michael ||Patino, Michael */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/ CREATE TABLE subjects ( case_number TEXT not null, race TEXT not null, gender TEXT not null, last_name TEXT not null, first_name TEXT null, full_name TEXT not null, foreign key (case_number) references incidents (case_number) ) /* 1 example row: SELECT * FROM subjects LIMIT 1; case_number ||race ||gender ||last_name ||first_name || full_name 44523A || L || M || Curry || James ||Curry, James */ /* column definitions { "case_number": "case number", "race": "race", "gender": "gender", "last_name": "last name", "first_name": "first name", "full_name": "full name" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/ ### Question Please list the location of the genes that have the most chromosomes. Clarification:
[query_database(**{'query': 'SELECT T2.Localization FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID ORDER BY T1.Chromosome DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/ ### Question For the pairs of genes with one having 8 chromosomes and the other having 6 chromosomes, what is the highest expression correlation score? Clarification:
[query_database(**{'query': 'SELECT T2.Expression_Corr FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Chromosome = 6 OR T1.Chromosome = 8 ORDER BY T2.Expression_Corr DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/
2,500
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/ ### Question If a pair of genes is positively correlated, what is the possibility of it being composed of two genes both with over 10 chromosomes? Clarification: Positively correlated means Expression_Corr > 0; Possibility = count(the pairs of genes with both chromosomes over 20) / count(pairs of genes that are positively correlated)
[query_database(**{'query': 'SELECT CAST(SUM(IIF(T1.Chromosome > 10 AND T3.Chromosome > 10, 1, 0)) AS REAL) * 100 / COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 INNER JOIN Genes AS T3 ON T3.GeneID = T2.GeneID2 WHERE T2.Expression_Corr > 0'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/ ### Question What percentage of genes located in the cytoskeleton are of unknown class? And of these, how many are not conditional phenotypes? Clarification: Percentage = count(genes located in the cytoskeleton unknown class) / count(genes located in the cytoskeleton) * 100%
[query_database(**{'query': 'SELECT SUM(Localization = 'cytoskeleton' AND Phenotype = 'Conditional phenotypes') , CAST(SUM(Localization = 'cytoskeleton') AS REAL) * 100 / COUNT(GeneID) FROM Genes;'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/
2,509
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/ ### Question Of all the nonessential genes that are not of the motorprotein class and whose phenotype is cell cycle defects, how many do not have a physical type of interaction? Clarification:
[query_database(**{'query': 'SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Type != 'Physical' AND T1.Phenotype = 'Cell cycle defects' AND T1.Class != 'Motorproteins' AND T1.Essential = 'Non-Essential''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Classification ( GeneID TEXT not null primary key, Localization TEXT not null ) /* 1 example row: SELECT * FROM classification LIMIT 1; GeneID ||Localization G234064 || cytoplasm */ /* column definitions { "GeneID": "unique identifier number of genes", "Localization": "location" }*/ CREATE TABLE Genes ( GeneID TEXT not null, Essential TEXT not null, Class TEXT not null, Complex TEXT null, Phenotype TEXT not null, Motif TEXT not null, Chromosome INTEGER not null, Function TEXT not null, Localization TEXT not null, foreign key (GeneID) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM genes LIMIT 1; GeneID ||Essential || Class || Complex ||Phenotype || Motif ||Chromosome || Function ||Localization G234064 ||Essential ||GTP/GDP-exchange factors (GEFs) ||Translation complexes || ? ||PS00824 || 1 ||CELLULAR ORGANIZATION (proteins are localized to the corresponding organelle) || cytoplasm */ /* column definitions { "GeneID": "identifier number of genes", "Essential ": "essential ", "Class": "class", "Complex": "Complex", "Phenotype": "Phenotype", "Motif": "Motif", "Chromosome": "Chromosome", "Function": "Function", "Localization": "" }*/ CREATE TABLE Interactions ( GeneID1 TEXT not null, GeneID2 TEXT not null, Type TEXT not null, Expression_Corr REAL not null, primary key (GeneID1, GeneID2), foreign key (GeneID1) references Classification (GeneID) on update cascade on delete cascade, foreign key (GeneID2) references Classification (GeneID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM interactions LIMIT 1; GeneID1 ||GeneID2 || Type ||Expression_Corr G234064 ||G234126 ||Genetic-Physical || 0.914095071 */ /* column definitions { "GeneID1": "identifier number of genes", "GeneID2": "identifier number of genes", "Type": "Type", "Expression_Corr": "Expression correlation score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question How many users mildly likes the 7 Minute Workout app and when was it last updated? Clarification: mildly likes the app refers to Sentiment_Polarity> = 0 and Sentiment_Polarity<0.5;
[query_database(**{'query': 'SELECT COUNT(T2.Sentiment_Polarity), T1."Last Updated" FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = '7 Minute Workout' AND T2.Sentiment_Polarity BETWEEN 0 AND 0.5'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What is the lowest sentiment polarity score of the Basketball Stars app for people who dislikes the app pretty much and how many downloads does it have? Clarification: lowest sentiment polarity score refers to MIN(Sentiment_Polarity); user dislike the app pretty much refers to Sentiment_Polarity<-0.5; number of downloads it has refers to installs;
[query_database(**{'query': 'SELECT MIN(T2.Sentiment_Polarity), T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Basketball Stars''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What are the top 5 installed free apps? Clarification: free app refers to price = 0; most installed app refers to MAX(Installs);
[query_database(**{'query': 'SELECT App FROM playstore WHERE Price = 0 ORDER BY CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER) DESC LIMIT 5'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question How many of the users hold neutral attitude on "10 Best Foods for You" app and what category is this app? Clarification: neutral attitude refers to Sentiment = 'Neutral';
[query_database(**{'query': 'SELECT COUNT(T2.App), T1.Category FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = '10 Best Foods for You' AND T2.Sentiment = 'Neutral''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question Which apps have multiple genres and what is the total sentiment subjectivity of these apps? Clarification: multiple genres refers to COUNT(Genres>1; total sentiment subjectivity = Sum(Sentiment_Subjectivity);
[query_database(**{'query': 'SELECT SUM(T2.Sentiment_Subjectivity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres > 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question List the top 5 shopping apps with the most reviews. Clarification: shopping apps refers to Genre = 'Shopping'; most reviews refers to MAX(Reviews);
[query_database(**{'query': 'SELECT DISTINCT App FROM playstore WHERE Genres = 'Shopping' GROUP BY App ORDER BY COUNT(App) DESC LIMIT 5'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question Which free app has the most Negative comments? Clarification: paid app refers to Type = 'Paid'; negative comment refers to Sentiment = 'Negative'; paid app with most negative comments refers to MAX(COUNT(Sentiment = 'Negative')) where Type = 'Paid';
[query_database(**{'query': 'SELECT T1.App FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Type = 'Free' AND T2.Sentiment = 'Negative' GROUP BY T1.App ORDER BY COUNT(T2.Sentiment) DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What is the rating for "Garden Coloring Book"? List all of its reviews. Clarification: Golfshot Plus: Golf GPS refers to App = 'Golfshot Plus: Golf GPS'; review refers to Translated_Review;
[query_database(**{'query': 'SELECT T1.Rating, T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Garden Coloring Book''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What is the number of installments of the app with the highest total Sentiment polarity score? Clarification: installments refers to Installs; highest total sentiment polarity score = MAX(SUM(Sentiment_Polarity));
[query_database(**{'query': 'SELECT T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App GROUP BY T1.App ORDER BY SUM(T2.Sentiment_Polarity) DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What percentage of no comment reviews are from "Teen" content rating apps? Clarification: no comment refers to Translated_Review = 'nan'; percentage = DIVIDE((SUM(Content Rating = 'Teen')), COUNT(*));
[query_database(**{'query': 'SELECT CAST(COUNT(CASE WHEN T1.`Content Rating` = 'Teen' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.App) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Translated_Review = 'nan''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What is the average price for a dating application? Clarification: average price = AVG(Price where Genre = 'Dating'); dating application refers to Genre = 'Dating';
[query_database(**{'query': 'SELECT AVG(Price) FROM playstore WHERE Genres = 'Dating''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question What is the percentage of application with 4.7 rating having more positives sentiment than negative sentiment? Clarification: percentage = DIVIDE(SUBTRACT(SUM(Sentiment = 'Positive')), (SUM(Sentiment = 'Negative')), SUM(Sentiment = 'Negative')) as percentage; having more positive sentiment than negative sentiment refers to Sentiment = 'Positive'>Sentiment = 'Negative';
[query_database(**{'query': 'SELECT CAST(COUNT(CASE WHEN ( SELECT COUNT(CASE WHEN Sentiment = 'Positive' THEN 1 ELSE NULL END) - COUNT(CASE WHEN Sentiment = 'Negative' THEN 1 ELSE NULL END) FROM user_reviews GROUP BY App ) > 0 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T2.Sentiment) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Rating = 4.7'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
2,561
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question List down the rating for the App Learn C++. Clarification: FALSE;
[query_database(**{'query': 'SELECT DISTINCT Rating FROM playstore WHERE App = 'Learn C++''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question How much is the average sentiment polarity score of Golf GPS Rangefinder: Golf Pad and what is it's rating in the Google Play Store? Clarification: average sentiment polarity score = AVG(Sentiment_Polarity); Golf GPS Rangefinder: Golf Pad  is the App;
[query_database(**{'query': 'SELECT AVG(T2.Sentiment_Polarity), T1.Rating FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Golf GPS Rangefinder: Golf Pad''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question For the Honkai Impact 3rd App, what is the highest sentiment polarity score and what genre does it belong to? Clarification: highest sentiment polarity score refers to MAX(Sentiment_Polarity);
[query_database(**{'query': 'SELECT MAX(T2.Sentiment_Polarity), T1.Genres FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Honkai Impact 3rd' AND T2.Sentiment_Polarity > 0.5 GROUP BY T1.Genres'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/ ### Question Among the role playing game genre, how many are targeted to teens and what is their average sentiment polarity score? Clarification: targeted to teen refers to Content Rating = 'Teen'; average = AVG(Sentiment_Polarity);
[query_database(**{'query': 'SELECT COUNT(T1.App), AVG(T2.Sentiment_Polarity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1."Content Rating" = 'Teen' AND T1.Genres = 'Role Playing''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE "playstore" ( App TEXT, Category TEXT, Rating REAL, Reviews INTEGER, Size TEXT, Installs TEXT, Type TEXT, Price TEXT, "Content Rating" TEXT, Genres TEXT ) /* 1 example row: SELECT * FROM playstore LIMIT 1; App || Category ||Rating ||Reviews ||Size ||Installs ||Type ||Price ||Content Rating || Genres Photo Editor & Candy Camera & Grid & ScrapBook ||ART_AND_DESIGN || 4.1 || 159 || 19M || 10,000+ ||Free || 0 || Everyone ||Art & Design */ /* column definitions { "App": "Application name", "Category": "Category the app belongs to", "Rating": "Overall user rating of the app (as when scraped)", "Reviews": "Number of user reviews for the app (as when scraped)", "Size": "Size of the app (as when scraped)", "Installs": "Number of user downloads/installs for the app (as when scraped)", "Type": "Paid or Free", "Price": "Price of the app (as when scraped)", "Content Rating": "Age group the app is targeted at - Children / Mature 21+ / Adult", "Genres": "An app can belong to multiple genres (apart from its main category)." }*/ CREATE TABLE "user_reviews" ( App TEXT references "playstore" (App), Translated_Review TEXT, Sentiment TEXT, Sentiment_Polarity TEXT, Sentiment_Subjectivity TEXT ) /* 1 example row: SELECT * FROM user_reviews LIMIT 1; App || Translated_Review ||Sentiment ||Sentiment_Polarity ||Sentiment_Subjectivity 10 Best Foods for You ||I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" || Positive || 1.0 || 0.5333333333333333 */ /* column definitions { "App": "Name of app", "Translated_Review": "User review (Preprocessed and translated to English)", "Sentiment": "Overall user rating of the app (as when scraped)", "Sentiment_Polarity": "Sentiment polarity score", "Sentiment_Subjectivity": "Sentiment subjectivity score" }*/
2,577
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question What is the average median income for all City type of stores? Clarification: AVG(Median Income) where Type = 'City';
[query_database(**{'query': 'SELECT AVG(`Median Income`) FROM `Store Locations` WHERE Type = 'City''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,581
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question List all the order numbers for In-Store sales and find the city where the store is located. Clarification: In-Store sales refer to Sales Channel = 'In-Store'; city refers to City Name;
[query_database(**{'query': 'SELECT DISTINCT T1.OrderNumber, T2.`City Name` FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T1.`Sales Channel` = 'In-Store''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Provide all the orders from WARE-NMK1003. Name the product and sales team for each of these order. Clarification: all the orders from WARE-NMK1003 refer to OrderNumber where WarehouseCode = 'WARE-NMK1003'; product refers to Product Name;
[query_database(**{'query': 'SELECT DISTINCT T1.`Product Name`, T3.`Sales Team` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Sales Team` AS T3 ON T3.SalesTeamID = T2._SalesTeamID WHERE T2.WarehouseCode = 'WARE-NMK1003''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,588
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Sate the order number and calculate the net profit for each order under Joshua Bennett. Clarification: net profit can be computed as SUBTRACT(Unit Price, Unit Cost); Joshua Bennett is the name of Sales Team;
[query_database(**{'query': 'SELECT T1.OrderNumber , REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '') FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.`Sales Team` = 'Joshua Bennett''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,592
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Among the sales with 40% discount via in-store channel, how many products were shipped from warehouse code of WARE-NMK1003? Clarification: 40% discount refers to Discount Applied = 0.4; in-store channel refers to Sales Channel = 'In-Store'; orders refer to OrderNumber;
[query_database(**{'query': 'SELECT COUNT(DISTINCT T) FROM ( SELECT CASE WHEN `Sales Channel` = 'In-Store' AND WarehouseCode = 'WARE-NMK1003' AND `Discount Applied` = '0.4' THEN OrderNumber ELSE NULL END AS T FROM `Sales Orders` ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Calculate the percentage of order via in-store channel of customer "Medline". Clarification: Medline is the name of the customer; DIVIDE(COUNT(OrderNumber where Sales Channel = 'In-Store' and Customer Names = 'Medline'), COUNT(OrderNumber where Customer Names = 'Medline')) as percentage;
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN T1.`Sales Channel` = 'In-Store' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1._CustomerID) FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID WHERE T2.`Customer Names` = 'Medline ''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,601
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Calculate the order percentage by "Carlos Miller" sales team. Clarification: DIVIDE(COUNT(OrderNumber where Sales Team = 'Carlos Miller'), COUNT(OrderNumber)) as percentage;
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN T2.`Sales Team` = 'Carlos Miller' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,605
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many orders have order date in 5/31/2018? Clarification: orders refer to OrderNumber;
[query_database(**{'query': 'SELECT SUM(IIF(OrderDate = '5/31/18', 1, 0)) FROM `Sales Orders`'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,608
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question State the full name of state code "GA". Clarification:
[query_database(**{'query': 'SELECT T FROM ( SELECT IIF(StateCode = 'GA', State, NULL) AS T FROM Regions ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many furniture cushions orders which have date of order in 2018? Clarification: furniture cushions orders refer to OrderNumber where Product Name = 'Furniture Cushions'; date of order in 2018 refers to SUBSTR(OrderDate, -2) = '18'
[query_database(**{'query': 'SELECT SUM(CASE WHEN T1.OrderDate LIKE '%/%/18' AND T2.`Product Name` = 'Furniture Cushions' THEN 1 ELSE 0 END) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,616
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question List out the city name of states located in South region. Clarification:
[query_database(**{'query': 'SELECT T FROM ( SELECT DISTINCT CASE WHEN T1.Region = 'South' THEN T2.`City Name` END AS T FROM Regions T1 INNER JOIN `Store Locations` T2 ON T2.StateCode = T1.StateCode ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,620
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question State the customer name of orders which has shipped date in 7/8/2018. Clarification: shipped date in 7/8/2018 refers to ShipDate = '7/8/18'
[query_database(**{'query': 'SELECT T FROM ( SELECT DISTINCT CASE WHEN T2.ShipDate = '7/8/18' THEN T1.`Customer Names` END AS T FROM Customers T1 INNER JOIN `Sales Orders` T2 ON T2._CustomerID = T1.CustomerID ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Please list the id and detailed position of all stores in Birmingham city. Clarification: Latitude and Longitude coordinates can be used to identify the detailed position of stores; id refers to StoreID;
[query_database(**{'query': 'SELECT StoreID, Latitude, Longitude FROM `Store Locations` WHERE `City Name` = 'Birmingham''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Please give the order number and product name of the order which has the lowest unit price. Clarification: the lowest unit price refers to MIN(Unit Price);
[query_database(**{'query': 'SELECT T1.OrderNumber, T2.`Product Name` FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE REPLACE(T1.`Unit Price`, ',', '') = ( SELECT REPLACE(T1.`Unit Price`, ',', '') FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID ORDER BY REPLACE(T1.`Unit Price`, ',', '') LIMIT 1 )'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,632
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question From 2018 to 2020, which year did the George Lewis group have the highest number of orders? Clarification: George Lewis refers to Sales Team; the highest number of orders refers to MAX(COUNT(OrderNumber)); which year from 2018 to 2020 refers to SUBSTR(OrderDate, -2) IN ('18', '19', '20') GROUP BY SUBSTR(OrderDate, -2);
[query_database(**{'query': 'SELECT SUBSTR(T1.OrderDate, -2, 2) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.`Sales Team` = 'George Lewis' GROUP BY SUBSTR(T1.OrderDate, -2, 2) ORDER BY COUNT(T1.OrderNumber) DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,636
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question What is the unit cost of order SO - 000103? Clarification: OrderNumber = 'SO - 000103';
[query_database(**{'query': 'SELECT DISTINCT T FROM ( SELECT IIF(OrderNumber = 'SO - 000103', `Unit Cost`, NULL) AS T FROM `Sales Orders` ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Please list the names of customers who have total orders of over 3 in 2018. Clarification: total orders of over 3 in 2018 refer to COUNT(OrderNumber) > 3 where SUBSTR(OrderDate, -2) = '18';
[query_database(**{'query': 'SELECT DISTINCT IIF(COUNT(T2.CustomerID) > 3, T2.`Customer Names`, NULL) FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID WHERE T1.OrderDate LIKE '%/%/18' GROUP BY T1._CustomerID HAVING COUNT(T2.CustomerID)'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,644
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many sales team were from Northeast? Clarification: Northeast is the name of the region;
[query_database(**{'query': 'SELECT SUM(CASE WHEN Region = 'Northeast' THEN 1 ELSE 0 END) FROM `Sales Team`'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,648
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Calculate ratio between the highest unit cost and the lowest unit cost? Clarification: ratio can be calculated as DIVIDE(MAX(Unit_Cost)), MIN(Unit Cost);
[query_database(**{'query': 'SELECT ( SELECT REPLACE(`Unit Cost`, ',', '') FROM `Sales Orders` WHERE REPLACE(`Unit Cost`, ',', '') = ( SELECT REPLACE(`Unit Cost`, ',', '') FROM `Sales Orders` ORDER BY REPLACE(`Unit Cost`, ',', '') DESC LIMIT 1 ) ORDER BY REPLACE(`Unit Cost`, ',', '') DESC LIMIT 1 ) / ( SELECT REPLACE(`Unit Cost`, ',', '') FROM `Sales Orders` WHERE REPLACE(`Unit Cost`, ',', '') = ( SELECT REPLACE(`Unit Cost`, ',', '') FROM `Sales Orders` ORDER BY REPLACE(`Unit Cost`, ',', '') ASC LIMIT 1 ) ORDER BY REPLACE(`Unit Cost`, ',', '') ASC LIMIT 1 )'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many orders made by Rochester Ltd? Clarification: Rochester Ltd is the name of the customer; orders refer to OrderNumber;
[query_database(**{'query': 'SELECT SUM(CASE WHEN T1.`Customer Names` = 'Rochester Ltd' THEN 1 ELSE 0 END) FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,656
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Among the products sold in Maricopa County, which was the least sold? Clarification: the least sold product refers to Product Name where MIN(Order Quantity);
[query_database(**{'query': 'SELECT T1.`Product Name` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Store Locations` AS T3 ON T3.StoreID = T2._StoreID WHERE T3.County = 'Maricopa County' ORDER BY T2.`Order Quantity` ASC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,660
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Find the percentage of products that were shipped from Burbank in 2018? Clarification: DIVIDE(SUM(Order Quantity where City Name = 'Burbank' and SUBSTR(OrderDate, -2) = '18')), (SUM(Order Quantity where SUBSTR(OrderDate, -2) = '18')) as percentage;
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN T3.`City Name` = 'Burbank' THEN T2.`Order Quantity` ELSE 0 END) AS REAL) * 100 / SUM(T2.`Order Quantity`) FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Store Locations` AS T3 ON T3.StoreID = T2._StoreID WHERE T2.OrderDate LIKE '%/%/18''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,666
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question List down the customer names and product names of the order made by "Anthony Torres" via distributor channel. Clarification: "Anthony Torres" is the name of Sales Team; distributor channel refers to Sales Channel = 'Distributor'
[query_database(**{'query': 'SELECT DISTINCT T1.`Customer Names`, T4.`Product Name` FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID INNER JOIN `Sales Team` AS T3 ON T3.SalesTeamID = T2._SalesTeamID INNER JOIN Products AS T4 ON T4.ProductID = T2._ProductID WHERE T3.`Sales Team` = 'Anthony Torres' AND T2.`Sales Channel` = 'Distributor''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Name the products via wholesale channel of the store under Pacific/Honolulu time zone. Clarification: products refers to Product Name; via wholesale channel refers to Sales Channel = 'Wholesale'
[query_database(**{'query': 'SELECT T FROM ( SELECT DISTINCT CASE WHEN T3.`Time Zone` = 'Pacific/Honolulu' AND T2.`Sales Channel` = 'Wholesale' THEN T1.`Product Name` ELSE NULL END AS T FROM Products T1 INNER JOIN `Sales Orders` T2 ON T2._ProductID = T1.ProductID INNER JOIN `Store Locations` T3 ON T3.StoreID = T2._StoreID ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,674
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Indicate the procured dates for the customer whose ID is 11. Clarification: ID is 11 refers to _CustomerID = 11;
[query_database(**{'query': 'SELECT DISTINCT T FROM ( SELECT IIF(_CustomerID = 11, ProcuredDate, NULL) AS T FROM `Sales Orders` ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,677
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many Borough-type stores located in the city of Brooklyn have a population of less than 3 million? Clarification: "Brooklyn" is the CityName; population of less than 3 million refers to Population < 3000000
[query_database(**{'query': 'SELECT SUM(CASE WHEN Population < 3000000 AND Type = 'Borough' AND `City Name` = 'Brooklyn' THEN 1 ELSE 0 END) FROM `Store Locations`'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question In which regions are the stores that have shipped products through the WARE-UHY1004 warehouse? Clarification: "WARE-UHY1004" is the WarehouseCode
[query_database(**{'query': 'SELECT T FROM ( SELECT DISTINCT CASE WHEN T3.WarehouseCode = 'WARE-UHY1004' THEN T1.Region END AS T FROM Regions T1 INNER JOIN `Store Locations` T2 ON T2.StateCode = T1.StateCode INNER JOIN `Sales Orders` T3 ON T3._StoreID = T2.StoreID ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many stores procured products on October 27, 2018, in the city of Oregon? Clarification: October 27, 2018 refers to ProcuredDate = '10/27/18'; 'Oregon' is the State
[query_database(**{'query': 'SELECT SUM(CASE WHEN T1.ProcuredDate = '10/27/18' AND T2.`City Name` = 'Orlando' THEN 1 ELSE 0 END) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,689
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many different time zones are there in the Northeast region? Clarification:
[query_database(**{'query': 'SELECT COUNT(DISTINCT T2.`Time Zone`) FROM Regions AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StateCode = T1.StateCode WHERE T1.Region = 'Northeast''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,693
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many online purchases did Ole Group make in May 2019? Clarification: "Ole Group" is the Customer Names; online purchase refers to Sales Channel = 'Online'; made in May 2019 refers to OrderDate LIKE '5/%/19'
[query_database(**{'query': 'SELECT SUM(CASE WHEN T1.`Sales Channel` = 'Online' AND T2.`Customer Names` = 'Ole Group' AND T1.OrderDate LIKE '5/%/19' THEN 1 ELSE 0 END) FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question What percentage of sell orders on 04/04/2020 were for the state of New York? Clarification: sales order on 04/04/2020 refers to OrderDate = '4/4/20'; 'New York' is  the City Name; percentage = Divide (Sum(OrderNumber where City Name = 'New York'), Count (OrderNumber)) * 100
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN T2.State = 'New York' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T1.OrderDate = '4/4/20''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,702
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many sales channels does the sales team have in the Midwest? Clarification: "Midwest" is the Region
[query_database(**{'query': 'SELECT COUNT(T1.`Sales Channel`) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.Region = 'Midwest''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,706
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Provide order number, warehouse code of customers Elorac, Corp. Clarification: "Elorac, Corp" is the Customer Names
[query_database(**{'query': 'SELECT DISTINCT T1.OrderNumber, T1.WarehouseCode FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID WHERE T2.`Customer Names` = 'Elorac, Corp''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,710
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Among sales teams in Midwest region, which sales team has an order quantity greater than 5? Clarification: order quantity greater than 5 refers to Order Quantity > 5
[query_database(**{'query': 'SELECT DISTINCT T2.`Sales Team` FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.Region = 'Midwest' AND T1.`Order Quantity` > 5'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Please indicate total order quantity of product Candles and calculate the percentage of such product among all the orders. Clarification: total order quantity refers to Sum (Order Quantity); 'Candles' is the Products Name; percentage = Divide (Sum(Order Quantity where Product Name = 'Candles'), Sum(Order Quantity)) * 100
[query_database(**{'query': 'SELECT SUM(CASE WHEN T1.`Product Name` = 'Candles' THEN T2.`Order Quantity` ELSE 0 END), CAST(SUM(CASE WHEN T1.`Product Name` = 'Candles' THEN T2.`Order Quantity` ELSE 0 END) AS REAL) * 100 / SUM(T2.`Order Quantity`) FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Store Locations` AS T3 ON T3.StoreID = T2._StoreID'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,718
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question How many online orders were shipped during the month of June 2018? Clarification: online orders refers to Sales Channel = 'Online'; shipped during the month of June 2018 refers to SUBSTR(ShipDate, 1, 1) = '6' AND SUBSTR(ShipDate,-2) = '18'
[query_database(**{'query': 'SELECT SUM(IIF(ShipDate LIKE '6/%/18' AND `Sales Channel` = 'Online', 1, 0)) FROM `Sales Orders`'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,722
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question In which region can you find the stores located in the state whose median income is no more than 30,000? Clarification: median income no more than 30,000 refers to Median Income < 30,000
[query_database(**{'query': 'SELECT T FROM ( SELECT DISTINCT CASE WHEN T2.`Median Income` < 30000 THEN T1.Region END AS T FROM Regions T1 INNER JOIN `Store Locations` T2 ON T2.StateCode = T1.StateCode ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,725
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question In 2019, how many orders were shipped by the sales team with the highest number of orders in the said year? Provide the name of the sales team. Clarification: shipped refers to ShipDate; in 2019 refers to shipped in 2019 refers to SUBSTR(ShipDate, -2) = '19'; order in the said year refers to SUBSTR(OrderDate, -2) = '19'; highest number of order refers to Max(Count(OrderNumber))
[query_database(**{'query': 'SELECT COUNT(T1.OrderNumber), T2.`Sales Team` FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T1.OrderDate LIKE '%/%/19' AND T1.ShipDate LIKE '%/%/19' GROUP BY T2.`Sales Team` ORDER BY COUNT(T1.OrderNumber) DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,729
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Between 2018 to 2020, what is the average amount of shipped orders per year under Carl Nguyen? Clarification: shipped refers to ShipDate; between 2018 and 2020 refers to SUBSTR(ShipDate, -2) IN ('18', '19', '20'); 'Carl Nguyen' is the name of Sales Team; average shipped orders per year = Divide (Count(OrderNumber), 3)
[query_database(**{'query': 'SELECT CAST(COUNT(T1.OrderNumber) AS REAL) / 3 FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE (T2.`Sales Team` = 'Carl Nguyen' AND ShipDate LIKE '%/%/18') OR (T2.`Sales Team` = 'Carl Nguyen' AND ShipDate LIKE '%/%/19') OR (T2.`Sales Team` = 'Carl Nguyen' AND ShipDate LIKE '%/%/20')'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
2,733
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question Name the product that was registered in the sales order 'SO - 0005951'. Clarification: sales order 'SO - 0005951' refers to OrderNumber = 'SO - 0005951'; product refers to Product Name
[query_database(**{'query': 'SELECT T FROM ( SELECT DISTINCT CASE WHEN T2.OrderNumber = 'SO - 0005951' THEN T1.`Product Name` ELSE NULL END AS T FROM Products T1 INNER JOIN `Sales Orders` T2 ON T2._ProductID = T1.ProductID ) WHERE T IS NOT NULL'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/ ### Question What is the average household income of Glendale? Clarification: "Glendale" is the City Name; Average household income refers to avg(Household Income)
[query_database(**{'query': 'SELECT AVG(`Household Income`) FROM `Store Locations` WHERE `City Name` = 'Glendale''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE Customers ( CustomerID INTEGER constraint Customers_pk primary key, "Customer Names" TEXT ) /* 1 example row: SELECT * FROM customers LIMIT 1; CustomerID ||Customer Names 1 || Avon Corp */ /* column definitions { "CustomerID": "unique id number indicating which customer", "Customer Names": "the name of the customer" }*/ CREATE TABLE Products ( ProductID INTEGER constraint Products_pk primary key, "Product Name" TEXT ) /* 1 example row: SELECT * FROM products LIMIT 1; ProductID ||Product Name 1 || Cookware */ /* column definitions { "ProductID": "unique id number representing each product", "Product Name": "name of the product" }*/ CREATE TABLE Regions ( StateCode TEXT constraint Regions_pk primary key, State TEXT, Region TEXT ) /* 1 example row: SELECT * FROM regions LIMIT 1; StateCode || State ||Region AL ||Alabama || South */ /* column definitions { "StateCode": "the unique code identifying the state", "State": "full state name", "Region": "the region where the state is located in" }*/ CREATE TABLE "Sales Team" ( SalesTeamID INTEGER constraint "Sales Team_pk" primary key, "Sales Team" TEXT, Region TEXT ) /* 1 example row: SELECT * FROM `sales team` LIMIT 1; SalesTeamID || Sales Team || Region 1 ||Adam Hernandez ||Northeast */ /* column definitions { "SalesTeamID": "unique sales team id", "Sales Team": "sales team names", "Region": "the region where the state is located in" }*/ CREATE TABLE "Store Locations" ( StoreID INTEGER constraint "Store Locations_pk" primary key, "City Name" TEXT, County TEXT, StateCode TEXT constraint "Store Locations_Regions_StateCode_fk" references Regions(StateCode), State TEXT, Type TEXT, Latitude REAL, Longitude REAL, AreaCode INTEGER, Population INTEGER, "Household Income" INTEGER, "Median Income" INTEGER, "Land Area" INTEGER, "Water Area" INTEGER, "Time Zone" TEXT ) /* 1 example row: SELECT * FROM `store locations` LIMIT 1; StoreID || City Name || County ||StateCode || State ||Type ||Latitude ||Longitude ||AreaCode ||Population ||Household Income ||Median Income ||Land Area ||Water Area || Time Zone 1 ||Birmingham ||Shelby County/Jefferson County || AL ||Alabama ||City ||33.52744 ||-86.79905 || 205 || 212461 || 89972 || 31061 ||378353942 || 6591013 ||America/Chicago */ /* column definitions { "StoreID": "unique store id", "City Name": "City Name", "County": "full county name", "StateCode": "state code", "State": "full state name", "Type": "type of the store", "Latitude": "Latitude", "Longitude": "Longitude", "AreaCode": "", "Population": "Population", "Household Income": "Household Income", "Median Income": "Median Income", "Land Area": "Land Area", "Water Area": "Water Area", "Time Zone": "Time Zone" }*/ CREATE TABLE "Sales Orders" ( OrderNumber TEXT constraint "Sales Orders_pk" primary key, "Sales Channel" TEXT, WarehouseCode TEXT, ProcuredDate TEXT, OrderDate TEXT, ShipDate TEXT, DeliveryDate TEXT, CurrencyCode TEXT, _SalesTeamID INTEGER constraint "Sales Orders_Sales Team_SalesTeamID_fk" references "Sales Team"(SalesTeamID), _CustomerID INTEGER constraint "Sales Orders_Customers_CustomerID_fk" references Customers(CustomerID), _StoreID INTEGER constraint "Sales Orders_Store Locations_StoreID_fk" references "Store Locations"(StoreID), _ProductID INTEGER constraint "Sales Orders_Products_ProductID_fk" references Products(ProductID), "Order Quantity" INTEGER, "Discount Applied" REAL, "Unit Price" TEXT, "Unit Cost" TEXT ) /* 1 example row: SELECT * FROM `sales orders` LIMIT 1; OrderNumber ||Sales Channel ||WarehouseCode ||ProcuredDate ||OrderDate ||ShipDate ||DeliveryDate ||CurrencyCode ||_SalesTeamID ||_CustomerID ||_StoreID ||_ProductID ||Order Quantity ||Discount Applied ||Unit Price ||Unit Cost SO - 000101 || In-Store || WARE-UHY1004 || 12/31/17 || 5/31/18 || 6/14/18 || 6/19/18 || USD || 6 || 15 || 259 || 12 || 5 || 0.075 || 1,963.10 || 1,001.18 */ /* column definitions { "OrderNumber": "the unique number identifying the order", "Sales Channel": "Sales Channel", "WarehouseCode": "Warehouse Code", "ProcuredDate": "Procured Date", "OrderDate": "Order Date", "ShipDate": "Ship Date", "DeliveryDate": "Delivery Date", "CurrencyCode": "Currency Code", "_SalesTeamID": "Sales Team ID", "_CustomerID": "_Customer ID", "_StoreID": "_Store ID", "_ProductID": "_Product ID", "Order Quantity": "Order Quantity", "Discount Applied": "Discount Applied", "Unit Price": "", "Unit Cost": "" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question What percentage of games won, games lost and games drawn does Cittadella have as a home team in total? Clarification: Percentage of games won = DIVIDE(COUNT(FTR = 'H' where HomeTeam = 'Cittadella'), COUNT(Div where HomeTeam = 'Cittadella')) as percentage; Percentage of games lost = DIVIDE(COUNT(FTR = 'A' where HomeTeam = 'Cittadella')), COUNT(Div where HomeTeam = 'Cittadella') as percentage; percentage of games drawn = DIVIDE(SUM(FTR = 'D'where HomeTeam = 'Cittadella'), COUNT(Div where HomeTeam = 'Cittadella')) as percentage;
[query_database(**{'query': 'SELECT CAST(COUNT(CASE WHEN FTR = 'H' THEN 1 ELSE NULL END) / COUNT(HomeTeam) AS REAL) * 100, CAST(COUNT(CASE WHEN FTR = 'A' THEN 1 ELSE NULL END) AS REAL) / COUNT(HomeTeam), CAST(COUNT(CASE WHEN FTR = 'D' THEN 1 ELSE NULL END) AS REAL) / COUNT(HomeTeam) FROM matchs WHERE HomeTeam = 'Cittadella''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question What percentage of all tied games did the Sassuolo team play in? Clarification: tied games refer FTR = 'D'; DIVIDE(COUNT(Div where FTR = 'D', HomeTeam = 'Sassuolo' or AwayTeam = 'Sassuolo'), COUNT(Div where HomeTeam = 'Sassuolo' or AwayTeam = 'Sassuolo')) as percentage;
[query_database(**{'query': 'SELECT CAST(SUM(CASE WHEN HomeTeam = 'Sassuolo' OR AwayTeam = 'Sassuolo' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(FTR) FROM matchs WHERE FTR = 'D''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question How many matches played in the 2019 season of Scottish Championship league were ended with an equal result of 2-2? Clarification: matches refer to Div; Scottish Championship is a name of the league; equal result of 2-2 refers to FTAG = 2 AND FTHG = 2;
[query_database(**{'query': 'SELECT COUNT(T1.Div) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.season = 2019 AND T2.name = 'Scottish Championship' AND T1.FTAG = 2 AND T1.FTHG = 2'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,752
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question What is the highest final-time score across all divisions in the 2021 season? Which team was the team that made up that score? Clarification: MAX(SUM where FTHG, FTAG, season = 2021);
[query_database(**{'query': 'SELECT ( SELECT MAX(MAX(FTAG), MAX(FTHG)) FROM matchs WHERE season = 2021 ) AS T1, AwayTeam FROM matchs WHERE season = 2021 AND FTHG = T1 OR FTAG = T1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,756
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question Which team won the match in the EC division on January 20, 2008 at home? Clarification: won at home refers to FTR = 'H'; January 20, 2008 refers to Date = '2008-01-20'; EC division refers to Div = 'EC';
[query_database(**{'query': 'SELECT HomeTeam FROM matchs WHERE Div = 'EC' AND Date = '2008-01-20' AND FTR = 'H''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,760
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question Which away team in the division of Bundesliga has the highest final time goals? Clarification: Bundesliga is a name of division; the highest final time goals refers to MAX(FTAG);
[query_database(**{'query': 'SELECT T1.AwayTeam FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div=T2.division WHERE T2.name = 'Bundesliga' ORDER BY T1.FTAG DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,764
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question In how many matches in the Seria A division did both teams have equal goals? Clarification: Seria A is a name of division; equal goals refers to FTR = 'D', where D stands for draft;
[query_database(**{'query': 'SELECT COUNT(T1.FTR) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'Seria A' AND T1.FTR = 'D''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,768
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question What was the final score for the game Bursaspor vs Denizlispor on 2009/4/26? Clarification: Bursaspor vs Denizlispor are names of teams where HomeTeam = 'Bursaspor' and AwayTeam = 'Denizlispor'; Date = '2009-04-26'; final score refers to FTHG, FTAG;
[query_database(**{'query': 'SELECT FTHG, FTAG FROM matchs WHERE Date = '2009-04-26' AND HomeTeam = 'Bursaspor' AND AwayTeam = 'Denizlispor''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,772
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question How many draw games happened on 2018/8/7 for National League? Clarification: National League is the name of division; Date = '2018-08-07'; draw refers to FTR = 'D'; games refer to Div;
[query_database(**{'query': 'SELECT COUNT(T1.FTR) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'National League' AND T1.Date = '2018-08-07' AND T1.FTR = 'D''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,776
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question Give the full name of the divison that had the most 0-0 games. Clarification: the most 0-0 games means a no-score draw and refers to MAX(COUNT(Div where FTHG = '0' and FTAG = '0'));
[query_database(**{'query': 'SELECT T2.name FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.FTAG = 0 AND T1.FTHG = 0 GROUP BY T2.division ORDER BY COUNT(T1.FTAG) DESC LIMIT 1'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,779
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question Which country did Bradford Team belongs to? Clarification: Bradford team refers to HomeTeam = 'Bradford' or AwayTeam = 'Bradford';
[query_database(**{'query': 'SELECT DISTINCT T2.country FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.HomeTeam = 'Bradford' OR T1.AwayTeam = 'Bradford''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,783
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question How many matches were held during the 2021 season's Premier League? Clarification: Premier League is the name of division;
[query_database(**{'query': 'SELECT COUNT(T1.Div) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.season = 2021 AND T2.name = 'Premier League''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question How many times did the team Werder Bremen win as the away team in matches of the Bundesliga division? Clarification: Bundesliga is the name of division; win as the away team refers to FTR = 'A', where 'A' stands for away victory;
[query_database(**{'query': 'SELECT COUNT(T1.Div) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'Bundesliga' AND T1.AwayTeam = 'Werder Bremen' AND T1.FTR = 'A''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,791
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question Please list the home teams in the matches of the Bundesliga division that ended with a home victory in the 2021 season. Clarification: Bundesliga is the name of division; home victory refers to refer to FTR = 'H', where H stands for home victory;
[query_database(**{'query': 'SELECT DISTINCT T1.HomeTeam FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.season = 2021 AND T1.FTR = 'H' AND T2.name = 'Bundesliga''})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,794
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/ ### Question How many final-time home-team goals were there in total in all the matches of the Bundesliga division in the 2021 season? Clarification: Bundesliga is the name of division; final-time home-team goals refers to FTHG;
[query_database(**{'query': 'SELECT SUM(T1.FTHG) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'Bundesliga' AND T1.season = 2021'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE divisions ( division TEXT not null primary key, name TEXT, country TEXT ) /* 1 example row: SELECT * FROM divisions LIMIT 1; division || name ||country B1 ||Division 1A ||Belgium */ /* column definitions { "division": "division id", "name": "name of the division", "country": "country of the division" }*/ CREATE TABLE matchs ( Div TEXT, Date DATE, HomeTeam TEXT, AwayTeam TEXT, FTHG INTEGER, FTAG INTEGER, FTR TEXT, season INTEGER, foreign key (Div) references divisions(division) ) /* 1 example row: SELECT * FROM matchs LIMIT 1; Div || Date || HomeTeam || AwayTeam ||FTHG ||FTAG ||FTR ||season B1 ||2020-08-08 ||Club Brugge ||Charleroi || 0 || 1 || A || 2021 */ /* column definitions { "Div": "Division Id", "Date": "Match Date", "HomeTeam": "Name of Home Team", "AwayTeam": "Name of Away Team", "FTHG": "Final-time Home-team Goals", "FTAG": "Final-time Away-team Goals", "FTR": "Final-time Results", "season": "season of the match" }*/
2,798
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Bellow is a sequence of instructions describing a question answering task that may require text to sql parsing, using the Sqlite syntax. Generate an appropriate answer to the given question. A question is considered 'Foo' if it can be answered by querying from the database. Strictly follow the required format. In your answer(s), give only the necessary information in a concise way. You must not re generate the input prompt. ### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE awards_players ( playerID TEXT not null, award TEXT not null, year INTEGER not null, lgID TEXT null, note TEXT null, pos TEXT null, primary key (playerID, year, award), foreign key (playerID) references players (playerID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM awards_players LIMIT 1; playerID || award ||year ||lgID ||note || pos abdulka01 ||All-Defensive Second Team ||1969 || NBA ||None ||None */ /* column definitions { "playerID": "ID number identifying the unique number of the player", "award": "the name of the award", "year": "the time of this award", "lgID": "the name of the league", "note": "notification", "pos": "the position of the player" }*/ CREATE TABLE coaches ( coachID TEXT not null, year INTEGER not null, tmID TEXT not null, lgID TEXT null, stint INTEGER not null, won INTEGER null, lost INTEGER null, post_wins INTEGER null, post_losses INTEGER null, primary key (coachID, year, tmID, stint), foreign key (tmID, year) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM coaches LIMIT 1; coachID ||year ||tmID ||lgID ||stint ||won ||lost ||post_wins ||post_losses adelmri01 ||1988 || POR || NBA || 2 || 14 || 21 || 0 || 3 */ /* column definitions { "coachID": "ID number identifying the unique number of the coach", "year": "", "tmID": "team name", "lgID": "league name", "stint": "the period of the time coaching this team", "won": "the number of won games", "lost": "the number of lost games", "post_wins": "the number of games won in the post-season (playoffs) games", "post_losses": "the number of games lost in the post-season (playoffs) games" }*/ CREATE TABLE draft ( id INTEGER default 0 not null primary key, draftYear INTEGER null, draftRound INTEGER null, draftSelection INTEGER null, draftOverall INTEGER null, tmID TEXT null, firstName TEXT null, lastName TEXT null, suffixName TEXT null, playerID TEXT null, draftFrom TEXT null, lgID TEXT null, foreign key (tmID, draftYear) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM draft LIMIT 1; id ||draftYear ||draftRound ||draftSelection ||draftOverall ||tmID ||firstName ||lastName ||suffixName || playerID ||draftFrom ||lgID 1 || 1967 || 0 || 0 || 0 || ANA || Darrell || Hardy || None ||hardyda01 || Baylor || ABA */ /* column definitions { "id": "the unique number to determine one row of the data", "draftYear": "which year does this draft happens", "draftRound": "the Round number of this draft", "draftSelection": "the position that the player was picked", "draftOverall": "The player's overall draft position for the year", "tmID": "team name", "firstName": "the first name of the player", "lastName": "the last name of the player", "suffixName": "the suffix name of the player", "playerID": "ID number identifying the unique number of the player", "draftFrom": "the university that the drafted players come from", "lgID": "the league name" }*/ CREATE TABLE player_allstar ( playerID TEXT not null, last_name TEXT null, first_name TEXT null, season_id INTEGER not null, conference TEXT null, league_id TEXT null, games_played INTEGER null, minutes INTEGER null, points INTEGER null, o_rebounds INTEGER null, d_rebounds INTEGER null, rebounds INTEGER null, assists INTEGER null, steals INTEGER null, blocks INTEGER null, turnovers INTEGER null, personal_fouls INTEGER null, fg_attempted INTEGER null, fg_made INTEGER null, ft_attempted INTEGER null, ft_made INTEGER null, three_attempted INTEGER null, three_made INTEGER null, primary key (playerID, season_id), foreign key (playerID) references players (playerID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM player_allstar LIMIT 1; playerID || last_name ||first_name ||season_id ||conference ||league_id ||games_played ||minutes ||points ||o_rebounds ||d_rebounds ||rebounds ||assists ||steals ||blocks ||turnovers ||personal_fouls ||fg_attempted ||fg_made ||ft_attempted ||ft_made ||three_attempted ||three_made abdulka01 ||Abdul-Jabbar || Kareem || 1969 || East || NBA || 1 || 18 || 10 || None || None || 11 || 4 || None || None || None || None || 8 || 4 || 2 || 2 || None || None */ /* column definitions { "playerID": "ID number identifying the unique number of the player", "first_name": "the first name of the player", "last_name": "the last name of the player", "season_id": "the id number of the season", "conference": "which conference that players belong to", "league_id": "the league name", "games_played": "how many all star games that this player played in this season", "minutes": "minutes of attendance", "points": "points", "o_rebounds": "offense rebounds", "d_rebounds": "defense rebounds", "rebounds": "total rebounds", "assists": "assistants", "steals": "steals", "blocks": "blocks", "turnovers": "turnovers", "personal_fouls": "personal fouls", "fg_attempted": "field goal attempted", "fg_made": "field goal made", "ft_attempted": "free throw attempted", "ft_made": "free throw made", "three_attempted": "three point attempted", "three_made": "three point made " }*/ CREATE TABLE players ( playerID TEXT not null primary key, useFirst TEXT null, firstName TEXT null, middleName TEXT null, lastName TEXT null, nameGiven TEXT null, fullGivenName TEXT null, nameSuffix TEXT null, nameNick TEXT null, pos TEXT null, firstseason INTEGER null, lastseason INTEGER null, height REAL null, weight INTEGER null, college TEXT null, collegeOther TEXT null, birthDate DATE null, birthCity TEXT null, birthState TEXT null, birthCountry TEXT null, highSchool TEXT null, hsCity TEXT null, hsState TEXT null, hsCountry TEXT null, deathDate DATE null, race TEXT null ) /* 1 example row: SELECT * FROM players LIMIT 1; playerID ||useFirst ||firstName ||middleName || lastName ||nameGiven ||fullGivenName ||nameSuffix ||nameNick ||pos ||firstseason ||lastseason ||height ||weight ||college ||collegeOther || birthDate ||birthCity ||birthState ||birthCountry || highSchool || hsCity ||hsState ||hsCountry || deathDate ||race abdelal01 || Alaa || Alaa || None ||Abdelnaby || None || None || None || None ||F-C || 0 || 0 || 82.0 || 240 || Duke || None ||1968-06-24 || Cairo || None || EGY ||Bloomfield Senior ||Bloomfield || NJ || USA ||0000-00-00 || B */ /* column definitions { "playerID": "ID number identifying the unique number of the player", "useFirst": "", "firstName": "the first name of the player", "middleName": "the middle name of the player", "lastName": "the last name of the player", "nameGiven": "", "fullGivenName": "", "nameSuffix": "the suffix name of the player", "nameNick": "", "pos": "the position of the player", "firstseason": "", "lastseason": "", "height": "inch", "weight": "lb", "college": "college", "collegeOther": "the college that transferred from ", "birthDate": "birthdate", "birthCity": "birthcity", "birthState": "birth state", "birthCountry": "birth country", "highSchool": "high school", "hsCity": "high school city", "hsState": "high school state", "hsCountry": "high school country", "deathDate": "deathdate", "race": "" }*/ CREATE TABLE teams ( year INTEGER not null, lgID TEXT null, tmID TEXT not null, franchID TEXT null, confID TEXT null, divID TEXT null, `rank` INTEGER null, confRank INTEGER null, playoff TEXT null, name TEXT null, o_fgm INTEGER null, -- o_fga int null, o_ftm INTEGER null, -- o_fta int null, -- o_3pm int null, -- o_3pa int null, -- o_oreb int null, -- o_dreb int null, -- o_reb int null, -- o_asts int null, -- o_pf int null, -- o_stl int null, -- o_to int null, -- o_blk int null, o_pts INTEGER null, -- d_fgm int null, -- d_fga int null, -- d_ftm int null, -- d_fta int null, -- d_3pm int null, -- d_3pa int null, -- d_oreb int null, -- d_dreb int null, -- d_reb int null, -- d_asts int null, -- d_pf int null, -- d_stl int null, -- d_to int null, -- d_blk int null, d_pts INTEGER null, -- o_tmRebound int null, -- d_tmRebound int null, homeWon INTEGER null, homeLost INTEGER null, awayWon INTEGER null, awayLost INTEGER null, -- neutWon int null, -- neutLoss int null, -- confWon int null, -- confLoss int null, -- divWon int null, -- divLoss int null, -- pace int null, won INTEGER null, lost INTEGER null, games INTEGER null, -- min int null, arena TEXT null, -- attendance int null, -- bbtmID varchar(255) null, primary key (year, tmID) ) /* 1 example row: SELECT * FROM teams LIMIT 1; year ||lgID ||tmID ||franchID ||confID ||divID ||rank ||confRank ||playoff || name ||o_fgm ||o_ftm ||o_pts ||d_pts ||homeWon ||homeLost ||awayWon ||awayLost ||won ||lost ||games ||arena 1937 || NBL || AFS || AFS || None || EA || 1 || 0 || CF ||Akron Firestone Non-Skids || 249 || 183 || 681 || 578 || 8 || 1 || 5 || 3 || 14 || 4 || 18 || None */ /* column definitions { "year": "year", "lgID": "league name", "tmID": "team id", "franchID": "", "confID": "", "divID": "division ID", "rank": "rank", "confRank": "", "playoff": "another name: post season", "name": "full name of the team", "o_fgm": "how many offense field goal made by this team in this season", "o_ftm": "how many offense free throw made by this team in this season", "o_pts": "offense points", "d_pts": "defense points", "homeWon": "wins in the home", "homeLost": "loses in the home", "awayWon": "wins in the away", "awayLost": "loses in the away", "won": "", "lost": "", "games": "", "arena": "arena" }*/ CREATE TABLE "awards_coaches" ( id INTEGER primary key autoincrement, year INTEGER, coachID TEXT, award TEXT, lgID TEXT, note TEXT, foreign key (coachID, year) references coaches (coachID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM awards_coaches LIMIT 1; id ||year || coachID || award ||lgID ||note 1 ||1962 ||gallaha01 ||NBA Coach of the Year || NBA ||None */ /* column definitions { "id": "id of this row of data", "year": "which year did the coach receive the honor?", "coachID": "id number of the coaches", "award": "the award names", "lgID": "the name of the league", "note": "special notification" }*/ CREATE TABLE "players_teams" ( id INTEGER primary key autoincrement, playerID TEXT not null references players on update cascade on delete cascade, year INTEGER, stint INTEGER, tmID TEXT, lgID TEXT, GP INTEGER, GS INTEGER, minutes INTEGER, points INTEGER, oRebounds INTEGER, dRebounds INTEGER, rebounds INTEGER, assists INTEGER, steals INTEGER, blocks INTEGER, turnovers INTEGER, PF INTEGER, fgAttempted INTEGER, fgMade INTEGER, ftAttempted INTEGER, ftMade INTEGER, threeAttempted INTEGER, threeMade INTEGER, PostGP INTEGER, PostGS INTEGER, PostMinutes INTEGER, PostPoints INTEGER, PostoRebounds INTEGER, PostdRebounds INTEGER, PostRebounds INTEGER, PostAssists INTEGER, PostSteals INTEGER, PostBlocks INTEGER, PostTurnovers INTEGER, PostPF INTEGER, PostfgAttempted INTEGER, PostfgMade INTEGER, PostftAttempted INTEGER, PostftMade INTEGER, PostthreeAttempted INTEGER, PostthreeMade INTEGER, note TEXT, foreign key (tmID, year) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM players_teams LIMIT 1; id || playerID ||year ||stint ||tmID ||lgID ||GP ||GS ||minutes ||points ||oRebounds ||dRebounds ||rebounds ||assists ||steals ||blocks ||turnovers ||PF ||fgAttempted ||fgMade ||ftAttempted ||ftMade ||threeAttempted ||threeMade ||PostGP ||PostGS ||PostMinutes ||PostPoints ||PostoRebounds ||PostdRebounds ||PostRebounds ||PostAssists ||PostSteals ||PostBlocks ||PostTurnovers ||PostPF ||PostfgAttempted ||PostfgMade ||PostftAttempted ||PostftMade ||PostthreeAttempted ||PostthreeMade ||note 1 ||abdelal01 ||1990 || 1 || POR || NBA ||43 || 0 || 290 || 135 || 27 || 62 || 89 || 12 || 4 || 12 || 22 ||39 || 116 || 55 || 44 || 25 || 0 || 0 || 5 || 0 || 13 || 4 || 1 || 2 || 3 || 0 || 0 || 0 || 0 || 0 || 6 || 2 || 0 || 0 || 0 || 0 ||None */ /* column definitions { "id": "the unique number to identify this record", "playerID": "ID number identifying the unique number of the player", "year": "year", "stint": "the period of the time player spent played for this team", "tmID": "team name", "lgID": "", "GP": "game presentatons (attendance)", "GS": "game starting", "minutes": "minutes", "points": "points", "oRebounds": "offense rebounds", "dRebounds": "defense rebounds", "rebounds": "total rebounds", "assists": "assistants", "steals": "steals", "blocks": "blocks", "turnovers": "turnovers", "PF": "personal fouls", "fgAttempted": "field goal attempted", "fgMade": "field goal made", "ftAttempted": "free throw attempted", "ftMade": "free throw made", "threeAttempted": "three point attempted", "threeMade": "three point made", "PostGP": "post season game presentations", "PostGS": "post season game starting", "PostMinutes": "post season minutes", "PostPoints": "post season points", "PostoRebounds": "post season offense rebounds", "PostdRebounds": "post season defense rebounds", "PostRebounds": "post season defense rebounds", "PostAssists": "", "PostSteals": "", "PostBlocks": "", "PostTurnovers": "", "PostPF": "", "PostfgAttempted": "", "PostfgMade": "", "PostftAttempted": "", "PostftMade": "", "PostthreeAttempted": "", "PostthreeMade": "", "note": "" }*/ CREATE TABLE "series_post" ( id INTEGER primary key autoincrement, year INTEGER, round TEXT, series TEXT, tmIDWinner TEXT, lgIDWinner TEXT, tmIDLoser TEXT, lgIDLoser TEXT, W INTEGER, L INTEGER, foreign key (tmIDWinner, year) references teams (tmID, year) on update cascade on delete cascade, foreign key (tmIDLoser, year) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM series_post LIMIT 1; id ||year ||round ||series ||tmIDWinner ||lgIDWinner ||tmIDLoser ||lgIDLoser ||W ||L 1 ||1946 || F || O || PHW || NBA || CHS || NBA ||4 ||1 */ /* column definitions { "id": "unique number of this record", "year": "year", "round": "round", "series": "", "tmIDWinner": "team id winner", "lgIDWinner": "league id winner", "tmIDLoser": "team id loser", "lgIDLoser": "league id loser", "W": "wins", "L": "loses" }*/ ### Question List the team name and the total wins of the team in year 2005 which has greater winning from the previous year. Clarification: 2005 refers to year = 2005 ; previous year refers to year = 2004; team with greater winning than previous year refers to Won where year = 2005 > Won where year = 2004; team name refers to tmID
[query_database(**{'query': 'SELECT T1.name, T1.won FROM teams AS T1 INNER JOIN ( SELECT * FROM teams WHERE year = 2004 ) AS T2 on T1.tmID = T2.tmID WHERE T1.year = 2005 and T1.won > T2.won'})]
### Instruction 1. Given an SQL script to initialize a database of multiple tables under '### Database Schema' section. Each table is followed by one example row extracted from the database and a ditionary of definitions for further clarifying its column names meaning. 2. A user give you a question under '### Question' section. 3. Determine if the user question is 'Foo'. Base on the given definition of 'Foo'. 4. If the question is 'Foo', generate an SQL query for answering the question and store it in a variable named "sql". Make a function call to an external SQL engine by generating "[query_database(**{'query': sql})]" 5. If the question is not 'Foo'. Generate an answer based on your own reflection. If you don't know the answer, just be honest and don't make up a random answer. ### Database Schema CREATE TABLE awards_players ( playerID TEXT not null, award TEXT not null, year INTEGER not null, lgID TEXT null, note TEXT null, pos TEXT null, primary key (playerID, year, award), foreign key (playerID) references players (playerID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM awards_players LIMIT 1; playerID || award ||year ||lgID ||note || pos abdulka01 ||All-Defensive Second Team ||1969 || NBA ||None ||None */ /* column definitions { "playerID": "ID number identifying the unique number of the player", "award": "the name of the award", "year": "the time of this award", "lgID": "the name of the league", "note": "notification", "pos": "the position of the player" }*/ CREATE TABLE coaches ( coachID TEXT not null, year INTEGER not null, tmID TEXT not null, lgID TEXT null, stint INTEGER not null, won INTEGER null, lost INTEGER null, post_wins INTEGER null, post_losses INTEGER null, primary key (coachID, year, tmID, stint), foreign key (tmID, year) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM coaches LIMIT 1; coachID ||year ||tmID ||lgID ||stint ||won ||lost ||post_wins ||post_losses adelmri01 ||1988 || POR || NBA || 2 || 14 || 21 || 0 || 3 */ /* column definitions { "coachID": "ID number identifying the unique number of the coach", "year": "", "tmID": "team name", "lgID": "league name", "stint": "the period of the time coaching this team", "won": "the number of won games", "lost": "the number of lost games", "post_wins": "the number of games won in the post-season (playoffs) games", "post_losses": "the number of games lost in the post-season (playoffs) games" }*/ CREATE TABLE draft ( id INTEGER default 0 not null primary key, draftYear INTEGER null, draftRound INTEGER null, draftSelection INTEGER null, draftOverall INTEGER null, tmID TEXT null, firstName TEXT null, lastName TEXT null, suffixName TEXT null, playerID TEXT null, draftFrom TEXT null, lgID TEXT null, foreign key (tmID, draftYear) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM draft LIMIT 1; id ||draftYear ||draftRound ||draftSelection ||draftOverall ||tmID ||firstName ||lastName ||suffixName || playerID ||draftFrom ||lgID 1 || 1967 || 0 || 0 || 0 || ANA || Darrell || Hardy || None ||hardyda01 || Baylor || ABA */ /* column definitions { "id": "the unique number to determine one row of the data", "draftYear": "which year does this draft happens", "draftRound": "the Round number of this draft", "draftSelection": "the position that the player was picked", "draftOverall": "The player's overall draft position for the year", "tmID": "team name", "firstName": "the first name of the player", "lastName": "the last name of the player", "suffixName": "the suffix name of the player", "playerID": "ID number identifying the unique number of the player", "draftFrom": "the university that the drafted players come from", "lgID": "the league name" }*/ CREATE TABLE player_allstar ( playerID TEXT not null, last_name TEXT null, first_name TEXT null, season_id INTEGER not null, conference TEXT null, league_id TEXT null, games_played INTEGER null, minutes INTEGER null, points INTEGER null, o_rebounds INTEGER null, d_rebounds INTEGER null, rebounds INTEGER null, assists INTEGER null, steals INTEGER null, blocks INTEGER null, turnovers INTEGER null, personal_fouls INTEGER null, fg_attempted INTEGER null, fg_made INTEGER null, ft_attempted INTEGER null, ft_made INTEGER null, three_attempted INTEGER null, three_made INTEGER null, primary key (playerID, season_id), foreign key (playerID) references players (playerID) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM player_allstar LIMIT 1; playerID || last_name ||first_name ||season_id ||conference ||league_id ||games_played ||minutes ||points ||o_rebounds ||d_rebounds ||rebounds ||assists ||steals ||blocks ||turnovers ||personal_fouls ||fg_attempted ||fg_made ||ft_attempted ||ft_made ||three_attempted ||three_made abdulka01 ||Abdul-Jabbar || Kareem || 1969 || East || NBA || 1 || 18 || 10 || None || None || 11 || 4 || None || None || None || None || 8 || 4 || 2 || 2 || None || None */ /* column definitions { "playerID": "ID number identifying the unique number of the player", "first_name": "the first name of the player", "last_name": "the last name of the player", "season_id": "the id number of the season", "conference": "which conference that players belong to", "league_id": "the league name", "games_played": "how many all star games that this player played in this season", "minutes": "minutes of attendance", "points": "points", "o_rebounds": "offense rebounds", "d_rebounds": "defense rebounds", "rebounds": "total rebounds", "assists": "assistants", "steals": "steals", "blocks": "blocks", "turnovers": "turnovers", "personal_fouls": "personal fouls", "fg_attempted": "field goal attempted", "fg_made": "field goal made", "ft_attempted": "free throw attempted", "ft_made": "free throw made", "three_attempted": "three point attempted", "three_made": "three point made " }*/ CREATE TABLE players ( playerID TEXT not null primary key, useFirst TEXT null, firstName TEXT null, middleName TEXT null, lastName TEXT null, nameGiven TEXT null, fullGivenName TEXT null, nameSuffix TEXT null, nameNick TEXT null, pos TEXT null, firstseason INTEGER null, lastseason INTEGER null, height REAL null, weight INTEGER null, college TEXT null, collegeOther TEXT null, birthDate DATE null, birthCity TEXT null, birthState TEXT null, birthCountry TEXT null, highSchool TEXT null, hsCity TEXT null, hsState TEXT null, hsCountry TEXT null, deathDate DATE null, race TEXT null ) /* 1 example row: SELECT * FROM players LIMIT 1; playerID ||useFirst ||firstName ||middleName || lastName ||nameGiven ||fullGivenName ||nameSuffix ||nameNick ||pos ||firstseason ||lastseason ||height ||weight ||college ||collegeOther || birthDate ||birthCity ||birthState ||birthCountry || highSchool || hsCity ||hsState ||hsCountry || deathDate ||race abdelal01 || Alaa || Alaa || None ||Abdelnaby || None || None || None || None ||F-C || 0 || 0 || 82.0 || 240 || Duke || None ||1968-06-24 || Cairo || None || EGY ||Bloomfield Senior ||Bloomfield || NJ || USA ||0000-00-00 || B */ /* column definitions { "playerID": "ID number identifying the unique number of the player", "useFirst": "", "firstName": "the first name of the player", "middleName": "the middle name of the player", "lastName": "the last name of the player", "nameGiven": "", "fullGivenName": "", "nameSuffix": "the suffix name of the player", "nameNick": "", "pos": "the position of the player", "firstseason": "", "lastseason": "", "height": "inch", "weight": "lb", "college": "college", "collegeOther": "the college that transferred from ", "birthDate": "birthdate", "birthCity": "birthcity", "birthState": "birth state", "birthCountry": "birth country", "highSchool": "high school", "hsCity": "high school city", "hsState": "high school state", "hsCountry": "high school country", "deathDate": "deathdate", "race": "" }*/ CREATE TABLE teams ( year INTEGER not null, lgID TEXT null, tmID TEXT not null, franchID TEXT null, confID TEXT null, divID TEXT null, `rank` INTEGER null, confRank INTEGER null, playoff TEXT null, name TEXT null, o_fgm INTEGER null, -- o_fga int null, o_ftm INTEGER null, -- o_fta int null, -- o_3pm int null, -- o_3pa int null, -- o_oreb int null, -- o_dreb int null, -- o_reb int null, -- o_asts int null, -- o_pf int null, -- o_stl int null, -- o_to int null, -- o_blk int null, o_pts INTEGER null, -- d_fgm int null, -- d_fga int null, -- d_ftm int null, -- d_fta int null, -- d_3pm int null, -- d_3pa int null, -- d_oreb int null, -- d_dreb int null, -- d_reb int null, -- d_asts int null, -- d_pf int null, -- d_stl int null, -- d_to int null, -- d_blk int null, d_pts INTEGER null, -- o_tmRebound int null, -- d_tmRebound int null, homeWon INTEGER null, homeLost INTEGER null, awayWon INTEGER null, awayLost INTEGER null, -- neutWon int null, -- neutLoss int null, -- confWon int null, -- confLoss int null, -- divWon int null, -- divLoss int null, -- pace int null, won INTEGER null, lost INTEGER null, games INTEGER null, -- min int null, arena TEXT null, -- attendance int null, -- bbtmID varchar(255) null, primary key (year, tmID) ) /* 1 example row: SELECT * FROM teams LIMIT 1; year ||lgID ||tmID ||franchID ||confID ||divID ||rank ||confRank ||playoff || name ||o_fgm ||o_ftm ||o_pts ||d_pts ||homeWon ||homeLost ||awayWon ||awayLost ||won ||lost ||games ||arena 1937 || NBL || AFS || AFS || None || EA || 1 || 0 || CF ||Akron Firestone Non-Skids || 249 || 183 || 681 || 578 || 8 || 1 || 5 || 3 || 14 || 4 || 18 || None */ /* column definitions { "year": "year", "lgID": "league name", "tmID": "team id", "franchID": "", "confID": "", "divID": "division ID", "rank": "rank", "confRank": "", "playoff": "another name: post season", "name": "full name of the team", "o_fgm": "how many offense field goal made by this team in this season", "o_ftm": "how many offense free throw made by this team in this season", "o_pts": "offense points", "d_pts": "defense points", "homeWon": "wins in the home", "homeLost": "loses in the home", "awayWon": "wins in the away", "awayLost": "loses in the away", "won": "", "lost": "", "games": "", "arena": "arena" }*/ CREATE TABLE "awards_coaches" ( id INTEGER primary key autoincrement, year INTEGER, coachID TEXT, award TEXT, lgID TEXT, note TEXT, foreign key (coachID, year) references coaches (coachID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM awards_coaches LIMIT 1; id ||year || coachID || award ||lgID ||note 1 ||1962 ||gallaha01 ||NBA Coach of the Year || NBA ||None */ /* column definitions { "id": "id of this row of data", "year": "which year did the coach receive the honor?", "coachID": "id number of the coaches", "award": "the award names", "lgID": "the name of the league", "note": "special notification" }*/ CREATE TABLE "players_teams" ( id INTEGER primary key autoincrement, playerID TEXT not null references players on update cascade on delete cascade, year INTEGER, stint INTEGER, tmID TEXT, lgID TEXT, GP INTEGER, GS INTEGER, minutes INTEGER, points INTEGER, oRebounds INTEGER, dRebounds INTEGER, rebounds INTEGER, assists INTEGER, steals INTEGER, blocks INTEGER, turnovers INTEGER, PF INTEGER, fgAttempted INTEGER, fgMade INTEGER, ftAttempted INTEGER, ftMade INTEGER, threeAttempted INTEGER, threeMade INTEGER, PostGP INTEGER, PostGS INTEGER, PostMinutes INTEGER, PostPoints INTEGER, PostoRebounds INTEGER, PostdRebounds INTEGER, PostRebounds INTEGER, PostAssists INTEGER, PostSteals INTEGER, PostBlocks INTEGER, PostTurnovers INTEGER, PostPF INTEGER, PostfgAttempted INTEGER, PostfgMade INTEGER, PostftAttempted INTEGER, PostftMade INTEGER, PostthreeAttempted INTEGER, PostthreeMade INTEGER, note TEXT, foreign key (tmID, year) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM players_teams LIMIT 1; id || playerID ||year ||stint ||tmID ||lgID ||GP ||GS ||minutes ||points ||oRebounds ||dRebounds ||rebounds ||assists ||steals ||blocks ||turnovers ||PF ||fgAttempted ||fgMade ||ftAttempted ||ftMade ||threeAttempted ||threeMade ||PostGP ||PostGS ||PostMinutes ||PostPoints ||PostoRebounds ||PostdRebounds ||PostRebounds ||PostAssists ||PostSteals ||PostBlocks ||PostTurnovers ||PostPF ||PostfgAttempted ||PostfgMade ||PostftAttempted ||PostftMade ||PostthreeAttempted ||PostthreeMade ||note 1 ||abdelal01 ||1990 || 1 || POR || NBA ||43 || 0 || 290 || 135 || 27 || 62 || 89 || 12 || 4 || 12 || 22 ||39 || 116 || 55 || 44 || 25 || 0 || 0 || 5 || 0 || 13 || 4 || 1 || 2 || 3 || 0 || 0 || 0 || 0 || 0 || 6 || 2 || 0 || 0 || 0 || 0 ||None */ /* column definitions { "id": "the unique number to identify this record", "playerID": "ID number identifying the unique number of the player", "year": "year", "stint": "the period of the time player spent played for this team", "tmID": "team name", "lgID": "", "GP": "game presentatons (attendance)", "GS": "game starting", "minutes": "minutes", "points": "points", "oRebounds": "offense rebounds", "dRebounds": "defense rebounds", "rebounds": "total rebounds", "assists": "assistants", "steals": "steals", "blocks": "blocks", "turnovers": "turnovers", "PF": "personal fouls", "fgAttempted": "field goal attempted", "fgMade": "field goal made", "ftAttempted": "free throw attempted", "ftMade": "free throw made", "threeAttempted": "three point attempted", "threeMade": "three point made", "PostGP": "post season game presentations", "PostGS": "post season game starting", "PostMinutes": "post season minutes", "PostPoints": "post season points", "PostoRebounds": "post season offense rebounds", "PostdRebounds": "post season defense rebounds", "PostRebounds": "post season defense rebounds", "PostAssists": "", "PostSteals": "", "PostBlocks": "", "PostTurnovers": "", "PostPF": "", "PostfgAttempted": "", "PostfgMade": "", "PostftAttempted": "", "PostftMade": "", "PostthreeAttempted": "", "PostthreeMade": "", "note": "" }*/ CREATE TABLE "series_post" ( id INTEGER primary key autoincrement, year INTEGER, round TEXT, series TEXT, tmIDWinner TEXT, lgIDWinner TEXT, tmIDLoser TEXT, lgIDLoser TEXT, W INTEGER, L INTEGER, foreign key (tmIDWinner, year) references teams (tmID, year) on update cascade on delete cascade, foreign key (tmIDLoser, year) references teams (tmID, year) on update cascade on delete cascade ) /* 1 example row: SELECT * FROM series_post LIMIT 1; id ||year ||round ||series ||tmIDWinner ||lgIDWinner ||tmIDLoser ||lgIDLoser ||W ||L 1 ||1946 || F || O || PHW || NBA || CHS || NBA ||4 ||1 */ /* column definitions { "id": "unique number of this record", "year": "year", "round": "round", "series": "", "tmIDWinner": "team id winner", "lgIDWinner": "league id winner", "tmIDLoser": "team id loser", "lgIDLoser": "league id loser", "W": "wins", "L": "loses" }*/