1sf/bird-sql-train-with-schema huggingface dataset:
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Among the types of postal points in Saint Croix, what percentage of postal points is the post office?
Evidence: DIVIDE(COUNT(type = 'Post Office' ), COUNT(type)) as percentage where county = 'SAINT CROIX';
SQL: SELECT CAST(COUNT(CASE WHEN T2.type = 'Post Office' THEN T1.zip_code ELSE NULL END) AS REAL) * 100 / COUNT(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'
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Among the area code 787, list the country of the cities with a postal point type of unique postal office.
Evidence: postal point type of unique postal office refers to type = 'Unique Post Office';
SQL: SELECT DISTINCT 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 T1.area_code = '787' AND T3.type = 'Unique Post Office'
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: What is the elevation of the city with the alias East Longmeadow?
SQL: SELECT T2.elevation FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'East Longmeadow'
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: In cities that do not implement daylight savings, what is the total number of cities?
Evidence: do not implement daylight savings refers to daylight_savings = 'No';
SQL: SELECT COUNT(T1.area_code) FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.daylight_savings = 'No'
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Give the country and area code of the city with zip code 1116.
SQL: SELECT T2.county, T1.area_code FROM area_code AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T1.zip_code = 1116
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Among the cities with alias St Thomas, provide the type of postal point for each city.
SQL: SELECT DISTINCT T2.type FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'St Thomas'
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: List down the names of the cities belonging to Noble, Oklahoma.
Evidence: the county of Noble is located in the state of Oklahoma;
SQL: SELECT T3.city 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 T1.name = 'Oklahoma' AND T2.county = 'NOBLE'
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Among the listed cities, provide the area code of the city with the largest water area.
Evidence: the largest water area refers to MAX(water_area);
SQL: SELECT T1.area_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.water_area = ( SELECT MAX(water_area) FROM zip_data )
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Provide the alias of the city with the highest population in year 2020.
Evidence: the highest population in year 2020 refers to MAX(population_2020);
SQL: SELECT T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.population_2020 = ( SELECT MAX(population_2020) FROM zip_data )
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: What is the elevation of the city belonging to Hampden, Massachusetts?
Evidence: the county of Hampden is located in the state of Massachusetts.
SQL: SELECT T3.elevation 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 T1.name = 'Massachusetts' AND T2.county = 'HAMPDEN' GROUP BY T3.elevation
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: List the area code of the city with the highest Hispanic population.
Evidence: the highest Hispanic population refers to MAX(hispanic_population);
SQL: SELECT T1.area_code FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.hispanic_population = ( SELECT MAX(hispanic_population) FROM zip_data )
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: Give the alias of the cities with an Asian population of 7.
Evidence: Asian population of 7 refers to asian_population = 7;
SQL: SELECT T1.alias FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.asian_population = 7
Database: address
Tables: CBSA, state, congress, zip_data, alias, area_code, avoid, country, zip_congress
Columns (table index, column name): -1, *, 0, CBSA, 0, CBSA_name, 0, CBSA_type, 1, abbreviation, 1, name, 2, cognress_rep_id, 2, first_name, 2, last_name, 2, CID, 2, party, 2, state, 2, abbreviation, 2, House, 2, District, 2, land_area, 3, zip_code, 3, city, 3, state, 3, multi_county, 3, type, 3, organization, 3, time_zone, 3, daylight_savings, 3, latitude, 3, longitude, 3, elevation, 3, state_fips, 3, county_fips, 3, region, 3, division, 3, population_2020, 3, population_2010, 3, households, 3, avg_house_value, 3, avg_income_per_household, 3, persons_per_household, 3, white_population, 3, black_population, 3, hispanic_population, 3, asian_population, 3, american_indian_population, 3, hawaiian_population, 3, other_population, 3, male_population, 3, female_population, 3, median_age, 3, male_median_age, 3, female_median_age, 3, residential_mailboxes, 3, business_mailboxes, 3, total_delivery_receptacles, 3, businesses, 3, 1st_quarter_payroll, 3, annual_payroll, 3, employees, 3, water_area, 3, land_area, 3, single_family_delivery_units, 3, multi_family_delivery_units, 3, total_beneficiaries, 3, retired_workers, 3, disabled_workers, 3, parents_and_widowed, 3, spouses, 3, children, 3, over_65, 3, monthly_benefits_all, 3, monthly_benefits_retired_workers, 3, monthly_benefits_widowed, 3, CBSA, 4, zip_code, 4, alias, 5, zip_code, 5, area_code, 6, zip_code, 6, bad_alias, 7, zip_code, 7, county, 7, state, 8, zip_code, 8, district
Question: What is the average of the white population in the cities with area code 920?
Evidence: AVG(white_population) where area_code = 920;
SQL: SELECT AVG(T2.white_population) FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 920