1sf/bird-sql-train-with-schema huggingface dataset:
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: Please calculate the average duration of trips started at South Van Ness at Market in 2015.
Evidence: started at refers to start_station_name; start_station_name = 'South Van Ness at Market'; average duration = DIVIDE(SUM(duration), COUNT(duration));
SQL: SELECT AVG(duration) FROM trip WHERE start_date LIKE '%2015%' AND start_station_name = 'South Van Ness at Market'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: How many trips which start station and end station are the same?
Evidence: start station refers to start_station_id; end station refers to end_station_id; start station and end station are the same refers to start_station_id = end_station_id;
SQL: SELECT SUM(IIF(start_station_id = end_station_id, 1, 0)) FROM trip
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: Please list trips id started on the hottest day.
Evidence: started refers to start_date; the hottest day refers to max_temperature_f;
SQL: SELECT T1.id FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code ORDER BY T2.max_temperature_f DESC LIMIT 1
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: Which were the trips that started at Mountain View City Hall and ended on a rainy day?
Evidence: started at refers to start_station_name; start_station_name = 'Mountain View City Hall'; ended on a rainy day refers to end_date where events = 'rain';
SQL: SELECT T1.id FROM trip AS T1 INNER JOIN weather AS T2 WHERE T2.events = 'Rain' AND T1.start_station_name = 'Mountain View City Hall'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: What is the average duration of trips that ended on a foggy day?
Evidence: ended on a foggy day refers to end_date where events = 'fog'; average duration = DIVIDE(SUM(duration), COUNT(duration));
SQL: SELECT AVG(T1.duration) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.events = 'Fog'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: What was duration of the longest trip started on the day that has a maximum wind speed of 30 mph?
Evidence: longest trip refers to MAX(duration); started on the day refers to start_date; maximum wind speed refers to max_wind_speed_mph; max_wind_speed_mph = 30;
SQL: SELECT T1.duration FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.max_wind_Speed_mph = 30 ORDER BY T1.duration DESC LIMIT 1
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: Please calculate the average temperature of those trips that started at Market at 4th in 2013.
Evidence: started at refers to start_station_name; start station_name = 'Market at 4th'; in 2013 refers to start_date like '%2013%'; temperature refers to mean_temperature_f; average temperature = DIVIDE(SUM(mean_temperature_f), COUNT(mean_temperature_f));
SQL: SELECT AVG(T2.mean_temperature_f) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE SUBSTR(CAST(T2.date AS TEXT), -4) = '2013' AND T1.start_station_name = 'Market at 4th'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: What was the mean humidity of a trip with id 4275?
Evidence: mean humidity refers to mean_humidity;
SQL: SELECT T2.mean_humidity FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T1.id = 4275
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: In 2015, what percentage of trips that had the subscription type was Customer and ended on a rainy day?
Evidence: in 2015 refers to end_date like '%2015%'; percentage = DIVIDE(COUNT(events = 'Rain'), COUNT(events));
SQL: SELECT CAST(SUM(CASE WHEN T2.events = 'Rain' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE SUBSTR(CAST(T2.date AS TEXT), -4) = '2015' AND T1.subscription_type = 'Customer'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: How many bike stations are installed after August, 2013 in San Jose?
Evidence: installed after August, 2013 refers to year(installation_date)>2013; in San Jose refers to city = 'San Jose';
SQL: SELECT COUNT(installation_date) FROM station WHERE city = 'San Jose' AND (SUBSTR(CAST(installation_date AS TEXT), 1, INSTR(installation_date, '/') - 1) IN ('8', '9', '10', '11', '12') AND SUBSTR(CAST(installation_date AS TEXT), -4) = '2013') OR SUBSTR(CAST(installation_date AS TEXT), -4) > '2013'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: What is the mean temperature in Fahrenheit on 8/29/2013 for the area where the zip code is 94107?
Evidence: mean temperature in Fahrenheit refers to mean_temperature_f; on 8/29/2013 refers to date = '8/29/2013';
SQL: SELECT SUM(IIF(zip_code = 94107 AND date = '8/29/2013', mean_temperature_f, 0)) FROM weather
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: What is the difference between the hottest temperature and the coldest temperature in in Fahrenheit on 8/29/2013 for the area where the zip code is 94107?
Evidence: hottest temperature refers to max_temperatutre_f; coldest temperature refers to min_temperature_f; difference = SUBTRACT(max_temperature_f, min_temperature_f); date = '8/29/2013'
SQL: SELECT SUM(IIF(zip_code = 94107 AND date = '8/29/2013', max_temperature_f - min_temperature_f, 0)) FROM weather
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: How many bikes can be borrowed in San Jose Diridon Caltrain Station at 12:06:01 on 2013/8/29?
Evidence: number of bikes that can be borrowed refers to bikes_available; San Jose Diridon Caltrain Station refers to name = 'San Jose Diridon Caltrain Station'; time = '2013/8/29 12:06:01'
SQL: SELECT T2.bikes_available FROM station AS T1 INNER JOIN status AS T2 ON T1.id = T2.station_id WHERE T1.name = 'San Jose Diridon Caltrain Station' AND T2.time = '2013/08/29 12:06:01'
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: In which city's station is a bike borrowed on trip ID4069?
Evidence: bike is borrowed from refers to start_station_id;
SQL: SELECT T2.city FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.id = 4069
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: How many bike trips started on the days in September, 2013 with the hottest temperature over 70 degrees Fahrenheit in the area where the zip code is 94107?
Evidence: started on the days in September, 2013 refers to date LIKE'9%'AND date LIKE'%2013' hottest temperature over 70 degrees Fahrenheit refers to max_temperature_f>70;
SQL: SELECT COUNT(T1.id) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.date LIKE '9/%/2013' AND T2.zip_code = 94107 AND T2.max_temperature_f > 70
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: Please list the starting stations of the bike trips made on a day with a max humidity over 80 in 2013 in the area where the zip code is 94107.
Evidence: starting stations refers to start_station_name; day with a max humidity over 80 refers to max_humidity>80; in 2013 refers to date LIKE'%2013';
SQL: SELECT DISTINCT T1.start_station_name FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE SUBSTR(CAST(T2.date AS TEXT), -4) = '2013' AND T2.zip_code = 94107 AND T2.max_temperature_f > 80
Database: bike_share_1
Tables: station, status, trip, weather
Columns (table index, column name): -1, *, 0, id, 0, name, 0, lat, 0, long, 0, dock_count, 0, city, 0, installation_date, 1, station_id, 1, bikes_available, 1, docks_available, 1, time, 2, id, 2, duration, 2, start_date, 2, start_station_name, 2, start_station_id, 2, end_date, 2, end_station_name, 2, end_station_id, 2, bike_id, 2, subscription_type, 2, zip_code, 3, date, 3, max_temperature_f, 3, mean_temperature_f, 3, min_temperature_f, 3, max_dew_point_f, 3, mean_dew_point_f, 3, min_dew_point_f, 3, max_humidity, 3, mean_humidity, 3, min_humidity, 3, max_sea_level_pressure_inches, 3, mean_sea_level_pressure_inches, 3, min_sea_level_pressure_inches, 3, max_visibility_miles, 3, mean_visibility_miles, 3, min_visibility_miles, 3, max_wind_Speed_mph, 3, mean_wind_speed_mph, 3, max_gust_speed_mph, 3, precipitation_inches, 3, cloud_cover, 3, events, 3, wind_dir_degrees, 3, zip_code
Question: How many trips made by a subscriber started in August, 2013 from a station that can hold more than 20 bikes?
Evidence: subscriber refers to subscription_type = 'Subscriber'; in August 2013 refers to start_date LIKE'8%' AND start_date LIKE'%2013%'; station that can hold more than 20 bikes refers to dock_count>20;
SQL: SELECT COUNT(T2.id) FROM station AS T1 INNER JOIN trip AS T2 ON T1.id = T2.start_station_id WHERE T2.subscription_type = 'Subscriber' AND T2.start_date LIKE '8/%/2013%' AND T1.dock_count > 20