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: Calculate the difference between the number of customers and the number of subscribers who did the trip in June 2013.
Evidence: customer refers to subscription_type = 'Customer'; subscribers refers to subscription_type = 'Subscriber'; difference = SUBTRACT(SUM(subscription_type = 'Subscriber' t), SUM(subscription_type = 'Customer')); trip in June 2013 refers to start_date BETWEEN '6/1/2013 0:00'AND '6/31/2013 12:59';
SQL: SELECT SUM(IIF(subscription_type = 'Subscriber', 1, 0)) - SUM(IIF(subscription_type = 'Customer', 1, 0)) FROM trip WHERE start_date LIKE '6/%/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: List the days in 2013 when rain and fog occurred together and find the id of bikes borrowed on these days.
Evidence: in 2013 refers to year(date) = 2013; rain and fog ocurred together refers to events = 'Fog-Rain'; id of bikes refers to biked_id;
SQL: SELECT T2.date, T1.bike_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) = '2013' AND T2.events = 'Fog-Rain'
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: Find the longest ride on foggy day. What were the mean visibility, mean wind speed, and weather event during that ride? Also, list the coordinates and names of the start and end stations.
Evidence: foggy day refers to events = 'fog'; longest ride on a foggy day refers to MAX(duration) where events = 'fog'; mean visibility refers to mean_visibility_miles; mean wind speed refers to mean_wind_speed_mph; weather event refers to events; coordinates refers to (lat, long); start station refers to start_station_id; end station refers to end_station_id;
SQL: SELECT T3.mean_visibility_miles, T3.mean_wind_speed_mph, T3.events, T1.lat, T1.long , T2.start_station_name, T2.end_station_name FROM station AS T1 INNER JOIN trip AS T2 ON T2.start_station_name = T1.name INNER JOIN weather AS T3 ON T3.zip_code = T2.zip_code WHERE T3.events = 'Fog' ORDER BY T2.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: For the rides that started at Market at 10th station and ended at South Van Ness at Market station in August of 2013, which day had the coldest temperature?
Evidence: started at refers to start_station_name; start_station_name = 'Market at 10th'; ended at refers to end_station_name; end_station_name = 'South Van Ness at Market'; in August of 2013 refers to start_date BETWEEN '8/1/2013 0:00' AND '8/31/2013 12:59'; day that had the coldest temperature refers to MIN(min_temperature_f);
SQL: SELECT T1.start_date FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code AND T2.date = SUBSTR(CAST(T1.start_date AS TEXT), 1, INSTR(T1.start_date, ' ') - 1) WHERE T2.date LIKE '8/%/2013' AND T1.start_station_name = 'Market at 10th' AND T1.end_station_name = 'South Van Ness at Market' AND T2.min_temperature_f = ( SELECT MIN(T2.min_temperature_f) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code AND T2.date = SUBSTR(CAST(T1.start_date AS TEXT), 1, INSTR(T1.start_date, ' ') - 1) WHERE T2.date LIKE '8/%/2013' AND T1.start_station_name = 'Market at 10th' AND T1.end_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: Among the rides during the rainy days, which ride was the longest? List the start station, end station, and duration of this ride.
Evidence: rainy days refers to events = 'rain'; longest ride refers to MAX(duration); start station refers to start_station_name; end station refers to end_station_name; duration of the ride refers to duration;
SQL: SELECT T1.start_station_name, T1.end_station_name, T1.duration FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.events = 'Rain' OR T2.events = 'rain' 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: Find the average ride duration during the rain of more than 0.8 inches.
Evidence: rain of more than 0.8 inches refers to events = rain where precipitation_inches>0.8; average ride 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 = 'Rain' AND T2.precipitation_inches > 0.8) OR (T2.events = 'rain' AND T2.precipitation_inches > 0.8)
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 the name and city of starting stations which has an above-average duration trips.
Evidence: starting stations refers to start_station_name; above average duration trips = DIVIDE(SUM(duration), COUNT(main_trip.id))<duration;
SQL: SELECT DISTINCT T1.start_station_name, T2.city FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T1.duration > ( SELECT AVG(T1.duration) FROM trip AS T1 LEFT 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 stations in San Francisco are installed in 2014?
Evidence: stations refers to name; San Francisco refers to city = 'San Francisco'; installed in 2004 refers to installation_date like'%2014';
SQL: SELECT SUM(CASE WHEN city = 'San Francisco' AND SUBSTR(installation_date, -4) = '2014' THEN 1 ELSE 0 END) 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: In 2006, how many trips ended at stations in Mountain View?
Evidence: in 2006 refers to start_date LIKE'%2006%'; ended at station refers to end_station_name; Mountain View refers to city = 'Mountain View';
SQL: SELECT COUNT(T2.city) FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.end_station_name WHERE T2.city = 'Mountain View' AND T1.start_date LIKE '%2006%'
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 trip id had the longest duration and the start station is in Redwood City?
Evidence: longest duration refers to MAX(duration); start station refers to start_station_name;
SQL: SELECT T1.id FROM trip AS T1 LEFT JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.city = 'Redwood City' AND T1.duration = ( SELECT MAX(T1.duration) FROM trip AS T1 LEFT JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.city = 'Redwood City' )
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 bikes id were used in trips which start station were installed in 2013.
Evidence: start station refers to start_station_name; installed in 2013 refers to installation_date LIKE '%2013';
SQL: SELECT DISTINCT T1.bike_id FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.installation_date LIKE '%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: How many trips which subscription types were Subscriber and ended in San Jose city?
Evidence: ended in refers to end_station_name;
SQL: SELECT COUNT(T1.subscription_type) FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.end_station_name WHERE T1.subscription_type = 'Subscriber' AND T2.city = 'San Jose'
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 trip had the shortest duration and started at the station that can hold 15 bikes?
Evidence: shortest duration refers to MIN(duration); started at the station refers to start_station_name; can hold 15 bikes refers to dock_count = 15;
SQL: SELECT T1.id FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.dock_count = 15 AND T1.duration = ( SELECT MIN(T1.duration) FROM trip AS T1 LEFT JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.dock_count = 15 )
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 year had the most number of trips that started at stations in San Francisco?
Evidence: started at station refers to start_station_name; San Francisco refers to city = 'San Francisco'; year that had the most number of trips refers to MAX(year(start_date));
SQL: SELECT SUBSTR(CAST(T1.start_date AS TEXT), INSTR(T1.start_date, ' '), -4) FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.city = 'San Francisco' GROUP BY T1.start_station_name ORDER BY COUNT(T1.id) 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 percentage of trips that started in San Jose and durations were longer than 800 seconds?
Evidence: percentage of trips = DIVIDE(COUNT(duration>800), COUNT(duration)) as percentage; San Jose refers to city = 'San Jose'; duration>800;
SQL: SELECT CAST(SUM(CASE WHEN T1.duration > 800 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM trip AS T1 INNER JOIN station AS T2 ON T2.name = T1.start_station_name WHERE T2.city = 'San Jose'
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 in 2013 had durations longer than 1000 seconds?
Evidence: trips in 2013 refers to start_date like'%2013%'; duration>1000;
SQL: SELECT COUNT(duration) FROM trip WHERE start_date LIKE '%/%/2013%' AND duration > 1000