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: What is the location coordinates of the bike station from which the bike for the trip that last the longest was borrowed?
Evidence: location coordinates refers to (lat, long); bike that was borrowed the longest refers to MAX(duration);
SQL: SELECT T2.lat, T2.long FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.duration = ( SELECT MAX(T1.duration) FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name )
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 docks were left at the end station for trip ID4069?
Evidence: end station refers to end_station_id; docks that were left refers to docks_available;
SQL: SELECT SUM(T2.docks_available) FROM trip AS T1 INNER JOIN status AS T2 ON T2.station_id = T1.end_station_id 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: Among the bike trips started on the days with a fog in 2013, how many of those trips started from the station "2nd at Townsend"?
Evidence: started on the days with a fog refers to start_date where events = 'fog'; in 2013 refers to date LIKE '%2013'; started from station refers to start_station_name; start_station_name = '2nd at Townsend';
SQL: SELECT COUNT(T1.start_station_name) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.date LIKE '%2013%' AND T2.events = 'Fog' AND T1.start_station_name = '2nd at Townsend' AND T2.zip_code = 94107
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 longest duration for a bike trip starting on a day with a fog in 2013?
Evidence: longest duration refers to MAX(duration); starting on a day with a fog refers to start_date where events = 'fog'; in 2013 refers to date LIKE '%2013';
SQL: SELECT MAX(T1.duration) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.date LIKE '%2013%' AND T2.events = 'Fog' AND T2.zip_code = 94107
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: When was the bike station from which the bike was borrowed on trip ID4069 installed?
Evidence: bike was borrowed from refers to start_station_id; when the bike station was installed refers to installation_date;
SQL: SELECT T2.installation_date 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 trips with a bike borrowed from the stations in San Francisco were made by a subscriber?
Evidence: bike was borrowed from refers to start_station_id; San Francisco refers to city = 'San Francisco'; subscriber refers to subscription_type = 'Subscriber';
SQL: SELECT COUNT(T1.id) FROM trip AS T1 INNER JOIN station AS T2 ON T2.ID = T1.start_station_id WHERE T2.city = 'San Francisco' AND T1.subscription_type = 'Subscriber'
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: On the day with the hottest temperature ever in 2014, how many bike trips started from the station 2nd at Folsom?
Evidence: hottest temperature refers to max_temperatutre_f; in 2014 refers to date LIKE '%2014'; started from station refers to start_station_name; start_station_name = '2nd at Folsom';
SQL: SELECT COUNT(T1.start_station_name) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.date LIKE '%2014%' AND T2.zip_code = 94107 AND T1.start_station_name = '2nd at Folsom' 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: What is the average duration of a bike trip made on the day with the hottest temperature ever in 2014?
Evidence: average duration = DIVIDE(SUM(duration), COUNT(id)); hottest temperature refers to max_temperature_f; in 2014 refers to date LIKE '%2014';
SQL: SELECT AVG(T1.duration) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.date LIKE '%2014%' AND T1.start_station_name = '2nd at Folsom' AND T2.max_temperature_f = ( SELECT max_temperature_f FROM weather ORDER BY 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: List out all end stations for a bicycle that were making a trip starting from 2nd at South Park station? Only retain the unique value.
Evidence: end station refers to end_station_name; starting from refers to start_station_name; start_station_name = '2nd at South Park';
SQL: SELECT DISTINCT end_station_name FROM trip WHERE start_station_name = '2nd at South Park'
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 rainy days were recorded in Mountain View?
Evidence: rainy days refers to events = 'rain'; Mountain View refers to zip_code = 94041;
SQL: SELECT SUM(IIF(zip_code = 94041 AND events = 'Rain', 1, 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 total number of bikes that can be hold in Redwood City before 2014.
Evidence: total number of bikes that can be hold = MAX(dock_count); before 2014 refers to year(installation_date)<2014;
SQL: SELECT SUM(CASE WHEN city = 'Redwood City' AND SUBSTR(installation_date, -4) < '2014' THEN dock_count ELSE 0 END) NUM FROM station
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 longest trip duration according? Convert the it to number of days.
Evidence: longest trip duration refers to MAX(duration); days conversion = DIVIDE(duration, 86400);
SQL: SELECT MAX(duration), CAST(MAX(duration) AS REAL) / 86400 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: Convert all temperature recorded at San Francisco city during August 2013 into degree Celsius.
Evidence: temperature refers to max_temperature_f; March 2013 refers to date like '3/%/2013'; conversion to Celcius = DIVIDE(SUBTRACT(max_temperature_f, 32), 1.800) as Celsius1; DIVIDE(SUBTRACT(mean_temperature_f, 32), 1.800) as Celsius2; DIVIDE(SUBTRACT(min_temperature_f, 32), 1.800) as Celcius3;
SQL: SELECT (max_temperature_f - 32) / 1.8000 , (mean_temperature_f - 32) / 1.8000 , (min_temperature_f - 32) / 1.8000 FROM weather WHERE SUBSTR(CAST(date AS TEXT), 1, INSTR(date, '/') - 1) = '8' AND SUBSTR(CAST(date AS TEXT), -4) = '2013' AND zip_code = 94107
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 ratio for subscriber to customer given that the starting and the ending stations is 2nd at South Park?
Evidence: subscriber refers to subscription_type = 'Subscriber'; customer refers to subscription_type = 'customer';starting station refers to start_station_name; ending station refers to end_statio_name; start_station_name = '2nd at South Park' AND end_station_name = '2nd at South Park'
SQL: SELECT CAST(SUM(IIF(subscription_type = 'Subscriber', 1, 0)) AS REAL) / SUM(IIF(subscription_type = 'Customer', 1, 0)) FROM trip WHERE start_station_name = '2nd at South Park' AND end_station_name = '2nd at South Park'
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: Are all stations with zip code 94107 located in San Francisco city?
Evidence: station refers to name;
SQL: SELECT DISTINCT T2.city FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.zip_code = 94107
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: List out all stations name that having a mean temperature 20 degree Celsius in year 2014.
Evidence: mean temperature refers to mean_temperature_f; mean temperature of 20 degree Celsius refers to DIVIDE(SUBTRACT(mean_temperature_f, 32), 1.8) = 20; in 2014 refers to date LIKE'%2015%';
SQL: SELECT DISTINCT T2.start_station_name, T2.end_station_name FROM weather AS T1 INNER JOIN trip AS T2 ON T1.zip_code = T2.zip_code WHERE T1.date LIKE '%2014' AND T1.mean_temperature_f = 20 * 1.8 + 32
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 bicycle trip were made within San Jose city during August 2013?
Evidence: during August 2013 refers to start_date like '8/%/2013%';
SQL: SELECT COUNT(T2.id) FROM station AS T1 INNER JOIN trip AS T2 ON T2.start_station_name = T1.name WHERE T1.city = 'San Jose' AND T2.start_date LIKE '8/%/2013%' AND T2.start_station_name LIKE 'San Jose%' AND T2.end_station_name LIKE 'San Jose%'