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-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- Which Asian country gave its agricultural sector the largest share of its gross domestic product?
| SELECT T2.Country FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T2.Country = T3.Code INNER JOIN economy AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Asia' ORDER BY T4.Agriculture DESC LIMIT 1; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- What form of governance does the least prosperous nation in the world have?
| SELECT T3.Government FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country INNER JOIN politics AS T3 ON T3.Country = T2.Country WHERE T2.GDP IS NOT NULL ORDER BY T2.GDP ASC LIMIT 1; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- What year saw the greatest number of organizations created on the European continent?
| SELECT STRFTIME('%Y', T4.Established) FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T2.Country = T3.Code INNER JOIN organization AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Europe' GROUP BY STRFTIME('%Y', T4.Established) ORDER BY COUNT(T4.Name) DESC LIMIT 1; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- What other country does the most populated nation in the world share a border with and how long is the border between the two nations?
| SELECT T2.Country2, T2.Length FROM country AS T1 INNER JOIN borders AS T2 ON T1.Code = T2.Country1 INNER JOIN country AS T3 ON T3.Code = T2.Country2 WHERE T1.Name = ( SELECT Name FROM country ORDER BY Population DESC LIMIT 1 ); |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- What is the population density of the nation whose capital city is in the Distrito Federal province, and what portion of its gross domestic product is devoted to its industries?
| SELECT T1.Population / T1.Area, T2.Industry FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Province = 'Distrito Federal'; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- Lists all governments with a parliamentary democracy that achieved their independence between 01/01/1950 and 12/31/1999.
| SELECT * FROM politics WHERE STRFTIME('%Y', Independence) BETWEEN '1950' AND '1999' AND Government = 'parliamentary democracy'; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- What percentage of countries became independent during the year 1960?
| SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Independence) = '1960' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(Country) FROM politics; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- List all deserts that are not between latitudes 30 and 40.
| SELECT Name FROM desert WHERE Latitude < 30 OR Latitude > 40; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- Indicate the coordinates of all the deserts whose area is in more than one country.
| SELECT T1.Latitude, T1.Longitude FROM desert AS T1 INNER JOIN geo_desert AS T2 ON T1.Name = T2.Desert GROUP BY T1.Name, T1.Latitude, T1.Longitude HAVING COUNT(T1.Name) > 1; |
-- Database schema
| borders : Country1 [ TEXT ] , Country2 [ TEXT ] , Length [ REAL ] | city : Name [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Population [ INTEGER ] , Longitude [ REAL ] , Latitude [ REAL ] | continent : Name [ TEXT ] primary_key , Area [ REAL ] | country : Name [ TEXT ] , Code [ TEXT ] primary_key , Capital [ TEXT ] , Province [ TEXT ] , Area [ REAL ] , Population [ INTEGER ] | desert : Name [ TEXT ] primary_key , Area [ REAL ] , Longitude [ REAL ] , Latitude [ REAL ] | economy : Country [ TEXT ] primary_key , GDP [ REAL ] , Agriculture [ REAL ] , Service [ REAL ] , Industry [ REAL ] , Inflation [ REAL ] | encompasses : Country [ TEXT ] , Continent [ TEXT ] , Percentage [ REAL ] | ethnicGroup : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | geo_desert : Desert [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_estuary : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_island : Island [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_lake : Lake [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_mountain : Mountain [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_river : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_sea : Sea [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | geo_source : River [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] | island : Name [ TEXT ] primary_key , Islands [ TEXT ] , Area [ REAL ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | islandIn : Island [ TEXT ] , Sea [ TEXT ] , Lake [ TEXT ] , River [ TEXT ] | isMember : Country [ TEXT ] , Organization [ TEXT ] , Type [ TEXT ] | lake : Name [ TEXT ] primary_key , Area [ REAL ] , Depth [ REAL ] , Altitude [ REAL ] , Type [ TEXT ] , River [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | language : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | located : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] | locatedOn : City [ TEXT ] , Province [ TEXT ] , Country [ TEXT ] , Island [ TEXT ] | mergesWith : Sea1 [ TEXT ] , Sea2 [ TEXT ] | mountain : Name [ TEXT ] primary_key , Mountains [ TEXT ] , Height [ REAL ] , Type [ TEXT ] , Longitude [ REAL ] , Latitude [ REAL ] | mountainOnIsland : Mountain [ TEXT ] , Island [ TEXT ] | organization : Abbreviation [ TEXT ] primary_key , Name [ TEXT ] , City [ TEXT ] , Country [ TEXT ] , Province [ TEXT ] , Established [ DATE ] | politics : Country [ TEXT ] primary_key , Independence [ DATE ] , Dependent [ TEXT ] , Government [ TEXT ] | population : Country [ TEXT ] primary_key , Population_Growth [ REAL ] , Infant_Mortality [ REAL ] | province : Name [ TEXT ] , Country [ TEXT ] , Population [ INTEGER ] , Area [ REAL ] , Capital [ TEXT ] , CapProv [ TEXT ] | religion : Country [ TEXT ] , Name [ TEXT ] , Percentage [ REAL ] | river : Name [ TEXT ] primary_key , River [ TEXT ] , Lake [ TEXT ] , Sea [ TEXT ] , Length [ REAL ] , SourceLongitude [ REAL ] , SourceLatitude [ REAL ] , Mountains [ TEXT ] , SourceAltitude [ REAL ] , EstuaryLongitude [ REAL ] , EstuaryLatitude [ REAL ] | sea : Name [ TEXT ] primary_key , Depth [ REAL ] | target : Country [ TEXT ] primary_key , Target [ TEXT ] |
-- -- What is the provincial capital of the province with a population of less than 80,000 that has the highest average population per area?
| SELECT CapProv FROM province WHERE Population < 80000 ORDER BY Population / Area DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many customers have never married?
| SELECT COUNT(ID) FROM Customers WHERE MARITAL_STATUS = 'Never-married'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among all the customers, how many of them are teenagers?
| SELECT COUNT(ID) FROM Customers WHERE age >= 13 AND age <= 19; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Please list the occupations of the customers with an education level of 11.
| SELECT DISTINCT OCCUPATION FROM Customers WHERE EDUCATIONNUM = 11; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Of the first 60,000 customers' responses to the incentive mailing sent by the marketing department, how many of them are considered a true response?
| SELECT COUNT(REFID) custmoer_number FROM Mailings1_2 WHERE RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the customers over 30, how many of them are Machine-op-inspcts?
| SELECT COUNT(ID) FROM Customers WHERE OCCUPATION = 'Machine-op-inspct' AND age > 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many female customers have an education level of over 11?
| SELECT COUNT(ID) FROM Customers WHERE EDUCATIONNUM > 11 AND SEX = 'Female'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are female?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.SEX = 'Female' AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Please list the occupations of the customers over 40 and have sent a true response to the incentive mailing sent by the marketing department.
| SELECT DISTINCT T1.OCCUPATION FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.age > 40 AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the male customers, how many of them come from a place with over 30,000 inhabitants?
| SELECT COUNT(T1.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Male' AND T2.INHABITANTS_K > 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many customers are from the place with the highest average income per month?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INCOME_K DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the customers from a place with more than 20,000 and less than 30,000 inhabitants, how many of them are Machine-op-inspcts?
| SELECT COUNT(T1.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Machine-op-inspct' AND T2.INHABITANTS_K > 20 AND T2.INHABITANTS_K < 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Which customer come from a place with more inhabitants, customer no.0 or customer no.1?
| SELECT T1.ID FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.ID = 0 OR T1.ID = 1 ORDER BY INHABITANTS_K DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are from a place with more than 30,000 inhabitants?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T3.INHABITANTS_K > 30 AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are divorced males?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.SEX = 'Male' AND T1.MARITAL_STATUS = 'Divorced' AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many of the first 60,000 customers from the place with the highest average income per month have sent a true response to the incentive mailing sent by the marketing department?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T2.RESPONSE = 'true' ORDER BY T3.INCOME_K DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the number of inhabitants of the place the most customers are from?
| SELECT DISTINCT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INHABITANTS_K DESC; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the customers who come from the place with 25746 inhabitants, how many of them are male?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INHABITANTS_K = 25.746 AND T1.SEX = 'Male'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are teenagers?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.age >= 13 AND T1.age <= 19 AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the average education level of customers from the place with the highest average income per month?
| SELECT AVG(T1.EDUCATIONNUM) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INCOME_K DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the average age of first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department?
| SELECT AVG(T1.age) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many of the customers are male?
| SELECT COUNT(ID) FROM Customers WHERE SEX = 'Male'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List down the customer's geographic identifier who are handlers or cleaners.
| SELECT GEOID FROM Customers WHERE OCCUPATION = 'Handlers-cleaners'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the total number of customers with an age below 30?
| SELECT COUNT(ID) FROM Customers WHERE age < 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List down the geographic identifier with an income that ranges from 2100 to 2500.
| SELECT GEOID FROM Demog WHERE INCOME_K >= 2100 AND INCOME_K <= 2500; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In geographic identifier from 20 to 50, how many of them has a number of inhabitants below 20?
| SELECT COUNT(GEOID) FROM Demog WHERE INHABITANTS_K < 20 AND GEOID >= 20 AND GEOID <= 50; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the number of inhabitants and income of geographic identifier 239?
| SELECT INHABITANTS_K FROM Demog WHERE GEOID = 239; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Give the level of education and occupation of customers ages from 20 to 35 with an income K of 2000 and below.
| SELECT T1.EDUCATIONNUM, T1.OCCUPATION FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INCOME_K < 2000 AND T1.age >= 20 AND T1.age <= 35; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List down the number of inhabitants of customers with a divorced marital status and older than 50 years old.
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.MARITAL_STATUS = 'Divorced' AND T1.age < 50; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the geographic identifier and income of the oldest customer?
| SELECT T1.GEOID, T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T1.age DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the male customers with an level of education of 4 and below, list their income K.
| SELECT INCOME_K FROM Demog WHERE GEOID IN ( SELECT GEOID FROM Customers WHERE EDUCATIONNUM < 4 AND SEX = 'Male' ); |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the occupation and income of male customers with an level of education of 4 to 6.
| SELECT T1.OCCUPATION, T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.EDUCATIONNUM >= 4 AND T1.EDUCATIONNUM <= 6 AND T1.SEX = 'Male'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In widowed male customers ages from 40 to 60, how many of them has an income ranges from 3000 and above?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.age >= 40 AND T1.age <= 60 AND T1.MARITAL_STATUS = 'Widowed' AND T1.SEX = 'Male' AND T2.INCOME_K >= 2000 AND T2.INCOME_K <= 3000; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the occupation of customers within number of inhabitants ranges of 30 to 40?
| SELECT DISTINCT T1.OCCUPATION FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INHABITANTS_K >= 30 AND T2.INHABITANTS_K <= 40; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the widowed female customers, give the income of those who has an level of education of 5 and below.
| SELECT INCOME_K FROM Demog WHERE GEOID IN ( SELECT GEOID FROM Customers WHERE EDUCATIONNUM < 5 AND SEX = 'Female' AND MARITAL_STATUS = 'Widowed' ); |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the marital status of customers within the age of 40 to 60 that has the highest income among the group.
| SELECT T1.MARITAL_STATUS FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.age >= 40 AND T1.age <= 60 ORDER BY T2.INCOME_K DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the number of inhabitants of male customers ages from 20 to 30 years old who are farming or fishing?
| SELECT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Farming-fishing' AND T1.SEX = 'Male' AND T1.age >= 20 AND T1.age <= 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the customers with a marital status of married-civ-spouse, list the number of inhabitants and age of those who are machine-op-inspct.
| SELECT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Farming-fishing' AND T1.SEX = 'Male' AND T1.age >= 20 AND T1.age <= 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In female customers ages from 50 to 60, how many of them has an number of inhabitants ranges from 19 to 24?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.age >= 50 AND T1.age <= 60 AND T2.INHABITANTS_K >= 19 AND T2.INHABITANTS_K <= 24; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the income and number of inhabitants of customers with an age greater than the 80% of average age of all customers?
| SELECT T2.INCOME_K, T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID GROUP BY T2.INCOME_K, T2.INHABITANTS_K HAVING T1.age > 0.8 * AVG(T1.age); |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In customers with marital status of never married, what is the percentage of customers with income of 2500 and above?
| SELECT CAST(SUM(CASE WHEN T2.INCOME_K > 2500 THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.MARITAL_STATUS = 'Never-married'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Find and list the id and geographic ID of the elderly customers with an education level below 3.
| SELECT ID, GEOID FROM Customers WHERE EDUCATIONNUM < 3 AND age > 65; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the geographic id of places where the income is above average.
| SELECT AVG(INCOME_K) FROM Demog; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Calculate the number of customers who did not respond in February of 2007.
| SELECT COUNT(REFID) custmoer_number FROM Mailings1_2 WHERE RESPONSE = 'false' AND REF_DATE BETWEEN '2007-02-01' AND '2007-02-28'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many teenagers are working as Machine-op-inspct?
| SELECT COUNT(ID) teenager_number FROM Customers WHERE OCCUPATION = 'Machine-op-inspct' AND age >= 13 AND age <= 19; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Of customers who provide other services, how many are from places where inhabitants are more than 20000?
| SELECT COUNT(T2.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Other-service' AND T2.INHABITANTS_K > 20; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the male customer in their twenties, how many are from places where the average income is more than 3000?
| SELECT COUNT(T2.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Male' AND T2.INCOME_K > 3000 AND T1.age >= 20 AND T1.age <= 29; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What percentage of elderly customers who are never married in the place with geographic ID 24?
| SELECT CAST(SUM(CASE WHEN T1.MARITAL_STATUS = 'never married' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.GEOID = 24; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the customers with an average income per inhabitant above 3000, what percentage are in their eighties?
| SELECT CAST(SUM(CASE WHEN T1.age BETWEEN 80 AND 89 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INCOME_K > 3000; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- How many of the customer's reference ID that has a TRUE response?
| SELECT COUNT(REFID) FROM Mailings1_2 WHERE RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List down the customer's reference ID with true response.
| SELECT REFID FROM Mailings1_2 WHERE RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the total number of widowed customers with an age below 50?
| SELECT COUNT(ID) FROM Customers WHERE MARITAL_STATUS = 'Widowed' AND age < 50; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List down the geographic identifier with an number of inhabitants less than 30.
| SELECT GEOID FROM Demog WHERE INHABITANTS_K < 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In geographic identifier from 10 to 30, how many of them has an income below 2000?
| SELECT COUNT(GEOID) FROM Demog WHERE INCOME_K < 2000 AND GEOID >= 10 AND GEOID <= 30; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the marital status of the customer ages 62 with an level of education of 7?
| SELECT DISTINCT MARITAL_STATUS FROM Customers WHERE EDUCATIONNUM = 7 AND age = 62; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List down the number of inhabitants of customers with a widowed marital status and false response .
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.MARITAL_STATUS = 'Widowed' AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the response and number of inhabitants of the oldest female customer?
| SELECT T2.RESPONSE, T3.INHABITANTS_K FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.SEX = 'Female' ORDER BY T1.age DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the female customers with an level of education of 3 and below, list their income.
| SELECT INCOME_K FROM Demog WHERE GEOID IN ( SELECT GEOID FROM Customers WHERE EDUCATIONNUM < 3 AND SEX = 'Female' ); |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the level of education and income of customers ages from 30 to 55 with a true response.
| SELECT T1.EDUCATIONNUM, T3.INCOME_K FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.age >= 30 AND T1.age <= 55 AND T2.RESPONSE = 'true'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In male customers ages from 30 to 50, how many of them has an income ranges from 2000 to 2300?
| SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Male' AND T1.age >= 30 AND T1.age <= 50 AND T2.INCOME_K >= 2000 AND T2.INCOME_K <= 2300; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the educationnum and response of customers within the age of 20 to 30 that has the highest number of inhabitants among the group.
| SELECT T1.EDUCATIONNUM, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.age >= 20 AND T1.age <= 30 ORDER BY T3.INHABITANTS_K DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the income of female customers ages from 30 to 55 years old and has an occupation of machine-op-inspct?
| SELECT T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.age >= 30 AND T1.age <= 55 AND T1.OCCUPATION = 'Machine-op-inspct'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the marital status and response of female customers with an level of education of 8 and above.
| SELECT DISTINCT T1.MARITAL_STATUS, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.EDUCATIONNUM > 8 AND T1.SEX = 'Female'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the age of female customers within the number of inhabitants below 30?
| SELECT age FROM Customers WHERE GEOID IN ( SELECT GEOID FROM Demog WHERE INHABITANTS_K < 30 ) AND SEX = 'Female'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the divorced male customers, give the income and response of those who has an level of education of 6 and above.
| SELECT DISTINCT T3.INCOME_K, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.EDUCATIONNUM > 6 AND T1.SEX = 'Male' AND T1.MARITAL_STATUS = 'Divorced'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the occupation and response of female customers within the number of inhabitants range of 20 to 25?
| SELECT DISTINCT T1.OCCUPATION, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.SEX = 'Female' AND T3.INHABITANTS_K >= 20 AND T3.INHABITANTS_K <= 25; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- In male customers with an occupation handlers or cleaners, what is the percentage of customers with a true response?
| SELECT CAST(SUM(CASE WHEN T2.RESPONSE = 'true' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(T2.REFID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.OCCUPATION = 'Handlers-cleaners' AND T1.SEX = 'Male'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- List the income and number of inhabitants of customers with a reference ID greater than the 50% of average of number of false response?
| SELECT T2.INCOME_K, T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID INNER JOIN Mailings1_2 AS T3 ON T1.ID = T3.REFID WHERE T3.REFID > ( SELECT 0.5 * COUNT(CASE WHEN RESPONSE = 'false' THEN 1 ELSE NULL END) / COUNT(RESPONSE) FROM Mailings1_2 ); |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the ratio of male and female among the age of teenager when the education is above 10?
| SELECT CAST(SUM(CASE WHEN SEX = 'Male' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN SEX = 'Female' THEN 1 ELSE 0 END) FROM Customers WHERE age BETWEEN 13 AND 19 AND EDUCATIONNUM > 10; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- What is the geographic ID and total income per year when the average income is above 3300 dollar.
| SELECT GEOID, INHABITANTS_K * INCOME_K * 12 FROM Demog WHERE INCOME_K > 3300; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Point out the greater one between the number of actual responding and not responding to mailing.
| SELECT RESPONSE FROM Mailings1_2 GROUP BY RESPONSE ORDER BY COUNT(RESPONSE) DESC LIMIT 1; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Find out the yearly income of geographic ID when the customer is female and occupation as sales.
| SELECT T2.INHABITANTS_K * T2.INCOME_K * 12 FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.OCCUPATION = 'Sales'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the geographic ID which has 33.658K of inhabitants, describe the education, occupation and age of female widow.
| SELECT T1.EDUCATIONNUM, T1.OCCUPATION, T1.age FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INHABITANTS_K = 33.658 AND T1.SEX = 'Female' AND T1.MARITAL_STATUS = 'Widowed'; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Find the response status to customer whose geographic ID of 134.
| SELECT T2.RESPONSE FROM Customers AS T1 INNER JOIN mailings3 AS T2 ON T1.ID = T2.REFID WHERE T1.GEOID = 134; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Describe the average income per month and yearly income of the geographic ID in which customer of ID "209556" and "290135".
| SELECT T2.INCOME_K, T2.INHABITANTS_K * T2.INCOME_K * 12 FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.ID = 209556 OR T1.ID = 290135; |
-- Database schema
| Demog : GEOID [ INTEGER ] primary_key , INHABITANTS_K [ REAL ] , INCOME_K [ REAL ] , A_VAR1 [ REAL ] , A_VAR2 [ REAL ] , A_VAR3 [ REAL ] , A_VAR4 [ REAL ] , A_VAR5 [ REAL ] , A_VAR6 [ REAL ] , A_VAR7 [ REAL ] , A_VAR8 [ REAL ] , A_VAR9 [ REAL ] , A_VAR10 [ REAL ] , A_VAR11 [ REAL ] , A_VAR12 [ REAL ] , A_VAR13 [ REAL ] , A_VAR14 [ REAL ] , A_VAR15 [ REAL ] , A_VAR16 [ REAL ] , A_VAR17 [ REAL ] , A_VAR18 [ REAL ] | mailings3 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Customers : ID [ INTEGER ] primary_key , SEX [ TEXT ] , MARITAL_STATUS [ TEXT ] , GEOID [ INTEGER ] , EDUCATIONNUM [ INTEGER ] , OCCUPATION [ TEXT ] , age [ INTEGER ] | Mailings1_2 : REFID [ INTEGER ] primary_key , REF_DATE [ DATETIME ] , RESPONSE [ TEXT ] | Sales : EVENTID [ INTEGER ] primary_key , REFID [ INTEGER ] , EVENT_DATE [ DATETIME ] , AMOUNT [ REAL ] |
-- -- Among the reference ID of under 10 who got response by marketing department, compare their education status.
| SELECT T1.EDUCATIONNUM FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T2.REFID < 10 AND T2.RESPONSE = 'true'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- How many community areas are there in Central Chicago?
| SELECT COUNT(*) FROM Community_Area WHERE side = 'Central'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Which district is the community area Lincoln Square grouped into?
| SELECT side FROM Community_Area WHERE community_area_name = 'Lincoln Square'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Which district in Chicago has the most community areas?
| SELECT side FROM Community_Area GROUP BY side ORDER BY COUNT(side) DESC LIMIT 1; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Which community area has the least population?
| SELECT community_area_name FROM Community_Area ORDER BY population ASC LIMIT 1; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Who is the person responsible for the crime cases in Central Chicago?
| SELECT commander FROM District WHERE district_name = 'Central'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- What is the email address to contact the administrator of Central Chicago?
| SELECT email FROM District WHERE district_name = 'Central'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- To which community area does the neighborhood Albany Park belong?
| SELECT T2.community_area_name FROM Neighborhood AS T1 INNER JOIN Community_Area AS T2 ON T1.community_area_no = T2.community_area_no WHERE T1.neighborhood_name = 'Albany Park'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- How many neighborhoods are there in the community area of Lincoln Square?
| SELECT COUNT(T3.community_area_no) FROM ( SELECT T1.community_area_no FROM Community_Area AS T1 INNER JOIN Neighborhood AS T2 ON T1.community_area_no = T2.community_area_no WHERE community_area_name = 'Lincoln Square' GROUP BY T1.community_area_no ) T3; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Please list the names of all the neighborhoods in the community area with the most population.
| SELECT T1.neighborhood_name FROM Neighborhood AS T1 INNER JOIN Community_Area AS T2 ON T2.community_area_no = T2.community_area_no ORDER BY T2.population DESC LIMIT 1; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Please list the names of all the neighborhoods in Central Chicago.
| SELECT T2.neighborhood_name FROM Community_Area AS T1 INNER JOIN Neighborhood AS T2 ON T1.community_area_no = T2.community_area_no WHERE T1.side = 'Central'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Please list the precise location coordinates of all the crimes in Central Chicago.
| SELECT T2.latitude, T2.longitude FROM District AS T1 INNER JOIN Crime AS T2 ON T1.district_no = T2.district_no WHERE T1.district_name = 'Central'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- How many crimes had happened in Central Chicago?
| SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Among all the crimes that had happened in Central Chicago, how many of them were cases of domestic violence?
| SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central' AND T1.domestic = 'TRUE'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- Please list the case numbers of all the crimes with no arrest made in Central Chicago.
| SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central' AND T1.arrest = 'FALSE'; |
-- Database schema
| Community_Area : community_area_no [ INTEGER ] primary_key , community_area_name [ TEXT ] , side [ TEXT ] , population [ TEXT ] | District : district_no [ INTEGER ] primary_key , district_name [ TEXT ] , address [ TEXT ] , zip_code [ INTEGER ] , commander [ TEXT ] , email [ TEXT ] , phone [ TEXT ] , fax [ TEXT ] , tty [ TEXT ] , twitter [ TEXT ] | FBI_Code : fbi_code_no [ TEXT ] primary_key , title [ TEXT ] , description [ TEXT ] , crime_against [ TEXT ] | IUCR : iucr_no [ TEXT ] primary_key , primary_description [ TEXT ] , secondary_description [ TEXT ] , index_code [ TEXT ] | Neighborhood : neighborhood_name [ TEXT ] primary_key , community_area_no [ INTEGER ] Neighborhood.community_area_no = Community_Area.community_area_no | Ward : ward_no [ INTEGER ] primary_key , alderman_first_name [ TEXT ] , alderman_last_name [ TEXT ] , alderman_name_suffix [ TEXT ] , ward_office_address [ TEXT ] , ward_office_zip [ TEXT ] , ward_email [ TEXT ] , ward_office_phone [ TEXT ] , ward_office_fax [ TEXT ] , city_hall_office_room [ INTEGER ] , city_hall_office_phone [ TEXT ] , city_hall_office_fax [ TEXT ] , Population [ INTEGER ] | Crime : report_no [ INTEGER ] primary_key , case_number [ TEXT ] , date [ TEXT ] , block [ TEXT ] , iucr_no [ TEXT ] Crime.iucr_no = IUCR.iucr_no , location_description [ TEXT ] , arrest [ TEXT ] , domestic [ TEXT ] , beat [ INTEGER ] , district_no [ INTEGER ] Crime.district_no = District.district_no , ward_no [ INTEGER ] Crime.ward_no = Ward.ward_no , community_area_no [ INTEGER ] Crime.community_area_no = Community_Area.community_area_no , fbi_code_no [ TEXT ] Crime.fbi_code_no = FBI_Code.fbi_code_no , latitude [ TEXT ] , longitude [ TEXT ] |
-- -- How many crimes had happened in the community area with the most population?
| SELECT COUNT(T2.report_no) FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T1.community_area_no = T2.community_area_no GROUP BY T1.community_area_name ORDER BY T1.population DESC LIMIT 1; |
Subsets and Splits