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-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the precise locations of the cities with an area code of 787?
| SELECT T2.latitude, T2.longitude FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = '787' GROUP BY T2.latitude, T2.longitude; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- In California, how many delivery receptacles are there in the community post office that has the highest number of delivery receptacles?
| SELECT COUNT(*) FROM state AS T1 INNER JOIN zip_data AS T2 ON T1.abbreviation = T2.state WHERE T1.abbreviation = 'CA' AND T2.type LIKE '%Community Post Office%' AND T1.name = 'California' AND T2.state = 'CA'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- In which county can you find the city with the highest number of females?
| SELECT T4.county FROM zip_data AS T3 INNER JOIN country AS T4 ON T3.zip_code = T4.zip_code GROUP BY T4.county ORDER BY T3.female_population DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the names of the states whose postal point is not affiliated with any organization?
| SELECT DISTINCT T2.name FROM zip_data AS T1 INNER JOIN state AS T2 ON T1.state = T2.abbreviation WHERE T1.division IS NULL; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the difference in the most populated city of Allentown-Bethlehem-Easton, PA-NJ in 2020 against its population in 2010?
| SELECT T1.population_2020 - T1.population_2010 AS result_data FROM zip_data AS T1 INNER JOIN CBSA AS T2 ON T1.CBSA = T2.CBSA WHERE T2.CBSA_name = 'Allentown-Bethlehem-Easton, PA-NJ' ORDER BY T1.population_2020 DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List all the zip codes in the county of New Castle in Delaware.
| SELECT DISTINCT T2.zip_code FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state WHERE T2.county = 'NEW CASTLE' AND T1.name = 'Delaware'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- How many representatives are there in the state with the highest monthly benefit payments for retired workers?
| SELECT COUNT(T3.cognress_rep_id) FROM zip_data AS T1 INNER JOIN state AS T2 ON T1.state = T2.abbreviation INNER JOIN congress AS T3 ON T2.abbreviation = T3.abbreviation ORDER BY T1.monthly_benefits_retired_workers DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- In the state where Lisa Murkowski is the representative, how many cities have zero employees?
| SELECT COUNT(T3.city) FROM congress AS T1 INNER JOIN state AS T2 ON T1.abbreviation = T2.abbreviation INNER JOIN zip_data AS T3 ON T2.abbreviation = T3.state WHERE T1.first_name = 'Murkowski' AND T1.last_name = 'Lisa' AND T3.employees = 0; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the top 3 states with the highest Asian population? List the full names of all the representatives in the said states.
| SELECT t.state, T1.first_name, T1.last_name FROM zip_data AS T INNER JOIN congress AS T1 ON t.state = T1.abbreviation GROUP BY t.state ORDER BY SUM(t.asian_population) DESC LIMIT 3; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which state is Outagamie County in? Give the full name of the state.
| SELECT DISTINCT T2.name FROM country AS T1 INNER JOIN state AS T2 ON T1.state = T2.abbreviation WHERE T1.county = 'OUTAGAMIE'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What party does the area with the zip code 91701 belong to?
| SELECT T1.party FROM congress AS T1 INNER JOIN state AS T2 ON T1.abbreviation = T2.abbreviation INNER JOIN zip_data AS T3 ON T2.abbreviation = T3.state WHERE T3.zip_code = 91701 GROUP BY T1.party; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- How many males are there in New Haven County's residential areas?
| SELECT SUM(T1.male_population) FROM zip_data AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T2.county = 'NEW HAVEN'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Show the alias for the county at coordinate (18.090875, -66.867756).
| SELECT T2.alias FROM zip_data AS T1 INNER JOIN alias AS T2 ON T1.zip_code = T2.zip_code WHERE T1.latitude = 18.090875 AND T1.longitude = -66.867756; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- For the city with the most elders, what's its area code?
| SELECT T2.area_code FROM zip_data AS T1 INNER JOIN area_code AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.area_code ORDER BY T1.over_65 DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- For the county represented by Thompson Bennie G, how many bad aliases does it have?
| SELECT COUNT(DISTINCT T2.bad_alias) FROM zip_congress AS T1 INNER JOIN avoid AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T1.district = T3.cognress_rep_id WHERE T3.first_name = 'Thompson' AND T3.last_name = 'Bennie G'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Give the location coordinates of the city with area code 636.
| SELECT T2.latitude, T2.longitude FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 636; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Show the zip code of the county represented by Buchanan Vernon.
| SELECT T2.zip_code FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.first_name = 'Buchanan' AND T1.last_name = 'Vernon'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which state is area code 878 in? Give the name of the state.
| SELECT T2.state FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 878; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- How many counties are there in Virginia State?
| SELECT COUNT(T2.county) FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'Virginia'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Give the name and the position of the cbsa officer from the area with the zip code 45503.
| SELECT T1.CBSA_name, T2.latitude, T2.longitude FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.zip_code = 45503 GROUP BY T1.CBSA_name, T2.latitude, T2.longitude; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Tell the name of the county which is represented by Hartzler Vicky.
| SELECT T1.county FROM country AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T3.first_name = 'Hartzler' AND T3.last_name = 'Vicky' GROUP BY T1.county; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Calculate the average male median age of all the residential areas in Windham county.
| SELECT SUM(T2.male_median_age) / COUNT(T2.median_age) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.county = 'WINDHAM'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- For the county where DeSantis Ron is from, what is the average female median age?
| SELECT SUM(T4.female_median_age) / COUNT(T1.county) FROM country AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id INNER JOIN zip_data AS T4 ON T1.zip_code = T4.zip_code WHERE T3.first_name = 'DeSantis' AND T3.last_name = 'Ron'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the area code of Bishopville, SC?
| SELECT T1.area_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Bishopville' AND T2.state = 'SC'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Name the bad alias of Geneva, AL.
| SELECT T1.bad_alias FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Geneva' AND T2.state = 'AL'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which city and state has the bad alias of Lawrenceville?
| SELECT T2.city, T2.state FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.bad_alias = 'Lawrenceville' GROUP BY T2.city, T2.state; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Name both the alias and the bad alias of zip code 38015.
| SELECT T1.alias, T2.bad_alias FROM alias AS T1 INNER JOIN avoid AS T2 ON T1.zip_code = T2.zip_code WHERE T1.zip_code = 38015; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the zip code of the district represented by Steven A King?
| SELECT T2.zip_code FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.first_name = 'King' AND T1.last_name = 'Steven A'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the CBSA name and type in York, ME?
| SELECT T1.CBSA_name, T1.CBSA_type FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.city = 'York' AND T2.state = 'ME'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List 10 cities with a median age over 40. Include their zip codes and area codes.
| SELECT T2.city, T2.zip_code, T1.area_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.median_age >= 40 LIMIT 10; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Name the county that has the bad alias of Druid Hills.
| SELECT T2.county FROM avoid AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T1.bad_alias = 'Druid Hills'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the area code of Phillips county in Montana?
| SELECT DISTINCT T1.area_code FROM area_code AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code INNER JOIN state AS T3 ON T2.state = T3.abbreviation WHERE T2.county = 'PHILLIPS' AND T3.name = 'Montana'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which district has the largest land area in Wisconsin? Write the full name of the congress representative and include the postal codes.
| SELECT T2.zip_code, T1.first_name, T1.last_name FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.state = 'Wisconsin' ORDER BY T1.land_area DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- How many states are in the central time zone? Write their full names.
| SELECT SUM(CASE WHEN T1.time_zone = 'Central' THEN 1 ELSE 0 END) AS count FROM zip_data AS T1 INNER JOIN state AS T2 ON T2.abbreviation = T1.state WHERE T1.time_zone = 'Central'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Name 10 cities with their states that are under the Lexington-Fayette, KY office of the Canada Border Services Agency.
| SELECT DISTINCT T2.city, T2.state FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_name = 'Lexington-Fayette, KY' LIMIT 10; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the percentage ratio between Democrats and Republicans in Indiana? List the zip codes belonging to Democrats.
| SELECT CAST(COUNT(CASE WHEN T2.party = 'Democrat' THEN 1 ELSE NULL END) AS REAL) / COUNT(CASE WHEN T2.party = 'Republican' THEN 1 ELSE NULL END)FROM zip_congress AS T1 INNER JOIN congress AS T2 ON T2.cognress_rep_id = T1.district; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Calculate the ratio between the number of representatives in Alabama and the number of representatives in Illinois.
| SELECT CAST(COUNT(CASE WHEN state = 'Alabama' THEN cognress_rep_id ELSE NULL END) AS REAL) / COUNT(CASE WHEN state = 'Illinois' THEN cognress_rep_id ELSE NULL END) FROM congress; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Calculate the average of 2020's population in each zip code.
| SELECT CAST(SUM(population_2020) AS REAL) / COUNT(zip_code) FROM zip_data; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- State the male population for all zip code which were under the Berlin, NH CBSA.
| SELECT T2.male_population FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_name = 'Berlin, NH' GROUP BY T2.male_population; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which CBSAs have more than 10 zip codes?
| SELECT T1.CBSA_name FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA GROUP BY T1.CBSA HAVING COUNT(T2.zip_code) > 10; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List all the bad alias for zip codes in Puerto Rico.
| SELECT T1.bad_alias FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.state = 'PR'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the longitude and latitude for the district represented by Grayson Alan?
| SELECT T1.latitude, T1.longitude FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T3.first_name = 'Grayson' AND T3.last_name = 'Alan'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the state for area code of 787?
| SELECT DISTINCT T2.state FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 787; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List all representatives of districts which have more than 30 000 population in 2020.
| SELECT T3.first_name, T3.last_name FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T1.population_2020 > 30000 GROUP BY T3.first_name, T3.last_name; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which zip code in Massachusetts that have more than 1 area code?
| SELECT T1.zip_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.state = 'MA' GROUP BY T1.zip_code HAVING COUNT(T1.area_code) > 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- State the county for Arecibo City.
| SELECT DISTINCT T1.county FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Arecibo'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- How many zip codes are under Barre, VT?
| SELECT COUNT(T2.zip_code) FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_name = 'Barre, VT'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the zip code under Saint Croix county, which zip code has the biggest land area?
| SELECT T1.zip_code FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.county = 'SAINT CROIX' ORDER BY T2.land_area DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Calculate the difference between the 2020 population and the 2010 population for the districts represented by Griffin Tim.
| SELECT T1.population_2020 - T1.population_2010 FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T3.first_name = 'Griffin' AND T3.last_name = 'Tim'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Based on the population in 2020, calculate the percentage for the population of Asian in the zip code where the CBSA was Atmore, AL.
| SELECT CAST(T2.asian_population AS REAL) * 100 / T2.population_2010 FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_name = 'Atmore, AL'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the cities with an area code 939, which city has the highest Asian population?
| SELECT T2.city FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 939 ORDER BY T2.asian_population DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Give the name of the country and state of the city with elevation of 1039.
| SELECT DISTINCT T1.name, T2.state FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state INNER JOIN zip_data AS T3 ON T2.zip_code = T3.zip_code WHERE T3.elevation = 1039; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the alias and elevation of the city with zip code 1028.
| SELECT T1.alias, T2.elevation FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.zip_code = 1028; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the area code of the city with the largest land area?
| SELECT T1.area_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.land_area = ( SELECT MAX(land_area) FROM zip_data ); |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Give the area code of the city with the white population ranging between 1700 to 2000.
| SELECT T1.area_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.white_population BETWEEN 1700 AND 2000; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the Asian population in the city with the alias Leeds?
| SELECT SUM(T2.asian_population) FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'Leeds'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List down the area code and country of the city named Savoy.
| SELECT T1.area_code, T2.county FROM area_code AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code INNER JOIN zip_data AS T3 ON T1.zip_code = T3.zip_code WHERE T3.city = 'Savoy'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the alias of the cities with 0 population in 2010?
| SELECT DISTINCT T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.population_2010 = 0; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the cities with area code 608, how many cities implement daylight savings?
| SELECT COUNT(T2.city) FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 608 AND T2.daylight_savings = 'Yes'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the average elevation of the cities with alias Amherst.
| SELECT AVG(T2.elevation) FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'Amherst'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the country and state of the city named Dalton?
| SELECT T2.county FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state INNER JOIN zip_data AS T3 ON T2.zip_code = T3.zip_code WHERE T3.city = 'Dalton' GROUP BY T2.county; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Give at least five alias of cities with a postal point of post office.
| SELECT T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.type = 'Post Office' LIMIT 5; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the difference in the number of cities with P.O. box only and cities with Post Office among the cities with area code 787?
| SELECT COUNT(CASE WHEN T2.type = 'P.O. Box Only' THEN 1 ELSE NULL END) - COUNT(CASE WHEN T2.type = 'Post Office' THEN 1 ELSE NULL END) AS DIFFERENCE FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 787; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the cities belonging to the country named Arroyo, calculate the percentage of increase in the population in these cities from 2010 to 2020.
| SELECT CAST((SUM(T2.population_2020) - SUM(T2.population_2010)) AS REAL) * 100 / SUM(T2.population_2010) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Arroyo'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the postal points in Texas, provide the zip codes and cities of postal points which have total beneficiaries of above 10000.
| SELECT T2.zip_code, T2.city FROM state AS T1 INNER JOIN zip_data AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'Texas' AND T2.total_beneficiaries > 10000; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the postal points in the District of Columbia, how many of them have an area with above 20000 black population?
| SELECT COUNT(T1.zip_code) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.county = 'DISTRICT OF COLUMBIA' AND T2.black_population > 20000; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the city where zip code 19019 is located and the alias of that city.
| SELECT T2.city, T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.zip_code = 19019; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List the bad alias of the postal point located in Camuy.
| SELECT T1.bad_alias FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Camuy'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the zip code, city, and congress representative's full names of the area which has highest population in 2020.
| SELECT T1.zip_code, T1.city, T3.first_name, T3.last_name FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id GROUP BY T2.district ORDER BY T1.population_2020 DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the daylight savings areas in the Midwest region, how many postal points are there in Illinois?
| SELECT COUNT(T2.zip_code) FROM state AS T1 INNER JOIN zip_data AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'Illinois' AND T2.daylight_savings = 'Yes' AND T2.region = 'Midwest'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the countries and the zip codes in the Virgin Islands.
| SELECT T2.county, T2.zip_code FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'Virgin Islands'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the zip codes and the alias of Greeneville.
| SELECT T2.zip_code, T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Greeneville'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Compare the numbers of postal points under Smith Adrian and Heck Joe.
| SELECT CASE WHEN COUNT(CASE WHEN T1.first_name = 'Smith' AND T1.last_name = 'Adrian' THEN T2.zip_code ELSE NULL END) > COUNT(CASE WHEN T1.first_name = 'Heck' AND T1.last_name = 'Joe' THEN T2.zip_code ELSE NULL END) THEN 'Smith Adrian>Heck Joe' ELSE 'Smith Adrian<=Heck Joe' END AS COMPARE FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the zip codes and CBSA officers of the postal point in Oxford.
| SELECT T2.zip_code, T1.CBSA_name FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.city = 'Oxford'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the zip codes and their affiliated organization for the postal point under Kingsport-Bristol, TN-VA.
| SELECT T2.zip_code, T2.organization FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_name = 'Kingsport-Bristol, TN-VA'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the zip codes and the congress representatives' names of the postal points which are affiliated with Readers Digest.
| SELECT T1.zip_code, T3.first_name, T3.last_name FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T1.organization = 'Readers Digest'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Among the postal points in California, calculate the percentage of them in post office types.
| SELECT CAST(COUNT(CASE WHEN T2.type = 'Post Office' THEN T2.zip_code ELSE NULL END) AS REAL) * 100 / COUNT(T2.zip_code) FROM state AS T1 INNER JOIN zip_data AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'California'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the zip code for the Senate house?
| SELECT T2.zip_code FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.House = 'House of Repsentatives' GROUP BY T2.zip_code; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which city has the most bad aliases?
| SELECT T2.city FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code GROUP BY T1.bad_alias ORDER BY COUNT(T1.zip_code) DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List all the counties in Georgia.
| SELECT T2.county FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state WHERE T1.name = 'Georgia' GROUP BY T2.county; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List all the locations of postal points with the area code "410".
| SELECT T2.latitude, T2.longitude FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 410; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the name of the CBSA of the city with the highest average house value?
| SELECT DISTINCT T1.CBSA_name FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.avg_house_value = ( SELECT MAX(avg_house_value) FROM zip_data ) LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the bad aliases of the postal points from East Setauket?
| SELECT T1.bad_alias FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'East Setauket'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What was the population of Wilcox County in 2010?
| SELECT SUM(T2.population_2010) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.county = 'WILCOX'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the code of the area with the largest Asian population?
| SELECT T1.zip_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.asian_population ORDER BY T2.asian_population DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- List all the cities with micro CBSA.
| SELECT T2.city FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_type = 'Micro'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the name of the state with the most counties?
| SELECT T1.name FROM state AS T1 INNER JOIN country AS T2 ON T1.abbreviation = T2.state GROUP BY T2.state ORDER BY COUNT(T2.county) DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the number of households in the "FL-10" district?
| SELECT SUM(CASE WHEN T2.district = 'FL-10' THEN 1 ELSE 0 END) FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the average household income in the city known as "Danzig"?
| SELECT T2.avg_income_per_household FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.bad_alias = 'Danzig'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What are the states with an above-average female population?
| SELECT DISTINCT T2.state FROM state AS T1 INNER JOIN zip_data AS T2 ON T1.abbreviation = T2.state WHERE T2.female_population > ( SELECT AVG(female_population) FROM zip_data ); |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What percentage of households are in "Coroyell" out of its state?
| SELECT CAST(SUM(CASE WHEN T1.county = 'CORYELL' THEN T2.households ELSE 0 END) AS REAL) * 100 / SUM(T2.households) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the name and the position of the CBSA officer in the city of Cabo Rojo?
| SELECT T1.CBSA_name, T1.CBSA_type FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T2.city = 'Cabo Rojo' GROUP BY T1.CBSA_name, T1.CBSA_type; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Indicate the country name of the city Las Marias.
| SELECT T1.county FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Las Marias'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- How many cities does congressman Pierluisi Pedro represent?
| SELECT COUNT(DISTINCT T1.city) FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T3.first_name = 'Pierluisi' AND T3.last_name = 'Pedro'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the names of bad aliases in the city of Aguadilla.
| SELECT T1.bad_alias FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Aguadilla'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Indicate the name of the congressman represent in Guanica.
| SELECT T3.first_name, T3.last_name FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T1.city = 'Guanica'; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which state has the most bad aliases?
| SELECT T2.state FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.state ORDER BY COUNT(T1.bad_alias) DESC LIMIT 1; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- What is the difference in the number of bad alias between Aguada city and Aguadilla city?
| SELECT COUNT(CASE WHEN T2.city = 'Aguada' THEN T1.bad_alias ELSE NULL END) - COUNT(CASE WHEN T2.city = 'Aguadilla' THEN T1.bad_alias ELSE NULL END) AS DIFFERENCE FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Which state has greater than 50 CBSA officers of metro type?
| SELECT T2.state FROM CBSA AS T1 INNER JOIN zip_data AS T2 ON T1.CBSA = T2.CBSA WHERE T1.CBSA_type = 'Metro' GROUP BY T2.state HAVING COUNT(T1.CBSA_type) > 50; |
-- Database schema
| CBSA : CBSA [ INTEGER ] primary_key , CBSA_name [ TEXT ] , CBSA_type [ TEXT ] | state : abbreviation [ TEXT ] primary_key , name [ TEXT ] | congress : cognress_rep_id [ TEXT ] primary_key , first_name [ TEXT ] , last_name [ TEXT ] , CID [ TEXT ] , party [ TEXT ] , state [ TEXT ] , abbreviation [ TEXT ] congress.abbreviation = state.abbreviation , House [ TEXT ] , District [ INTEGER ] , land_area [ REAL ] | zip_data : zip_code [ INTEGER ] primary_key , city [ TEXT ] , state [ TEXT ] zip_data.state = state.abbreviation , multi_county [ TEXT ] , type [ TEXT ] , organization [ TEXT ] , time_zone [ TEXT ] , daylight_savings [ TEXT ] , latitude [ REAL ] , longitude [ REAL ] , elevation [ INTEGER ] , state_fips [ INTEGER ] , county_fips [ INTEGER ] , region [ TEXT ] , division [ TEXT ] , population_2020 [ INTEGER ] , population_2010 [ INTEGER ] , households [ INTEGER ] , avg_house_value [ INTEGER ] , avg_income_per_household [ INTEGER ] , persons_per_household [ REAL ] , white_population [ INTEGER ] , black_population [ INTEGER ] , hispanic_population [ INTEGER ] , asian_population [ INTEGER ] , american_indian_population [ INTEGER ] , hawaiian_population [ INTEGER ] , other_population [ INTEGER ] , male_population [ INTEGER ] , female_population [ INTEGER ] , median_age [ REAL ] , male_median_age [ REAL ] , female_median_age [ REAL ] , residential_mailboxes [ INTEGER ] , business_mailboxes [ INTEGER ] , total_delivery_receptacles [ INTEGER ] , businesses [ INTEGER ] , 1st_quarter_payroll [ INTEGER ] , annual_payroll [ INTEGER ] , employees [ INTEGER ] , water_area [ REAL ] , land_area [ REAL ] , single_family_delivery_units [ INTEGER ] , multi_family_delivery_units [ INTEGER ] , total_beneficiaries [ INTEGER ] , retired_workers [ INTEGER ] , disabled_workers [ INTEGER ] , parents_and_widowed [ INTEGER ] , spouses [ INTEGER ] , children [ INTEGER ] , over_65 [ INTEGER ] , monthly_benefits_all [ INTEGER ] , monthly_benefits_retired_workers [ INTEGER ] , monthly_benefits_widowed [ INTEGER ] , CBSA [ INTEGER ] zip_data.CBSA = CBSA.CBSA | alias : zip_code [ INTEGER ] primary_key alias.zip_code = zip_data.zip_code , alias [ TEXT ] | area_code : zip_code [ INTEGER ] area_code.zip_code = zip_data.zip_code , area_code [ INTEGER ] | avoid : zip_code [ INTEGER ] avoid.zip_code = zip_data.zip_code , bad_alias [ TEXT ] | country : zip_code [ INTEGER ] country.zip_code = zip_data.zip_code , county [ TEXT ] , state [ TEXT ] country.state = state.abbreviation | zip_congress : zip_code [ INTEGER ] zip_congress.zip_code = zip_data.zip_code , district [ TEXT ] zip_congress.district = congress.cognress_rep_id |
-- -- Provide the population of Arecibo in 2020.
| SELECT SUM(T2.population_2020) FROM country AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.county = 'ARECIBO'; |
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