QIAN-ME/bird_schema_data huggingface dataset:
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    Which is the most fuel efficient car in 1975? car's name refers to car_name; the most fuel efficient refers to max(mpg); in 1975 refers to model_year = 1975

    【Evidence】
    car's name refers to car_name; the most fuel efficient refers to max(mpg); in 1975 refers to model_year = 1975

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.car_name FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T2.model_year = '1975' ORDER BY T1.mpg DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    Which car consumes fuel the most and has the highest price? consumes fuel the most refers to min(mpg); has the highest price refers to max(price)

    【Evidence】
    consumes fuel the most refers to min(mpg); has the highest price refers to max(price)

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.car_name FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID ORDER BY T1.mpg DESC, T2.price DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    How many American cars have an acceleration time of less than 12 seconds? American car refers to country = 'USA'; an acceleration time of less than 12 seconds refers to acceleration < 12

    【Evidence】
    American car refers to country = 'USA'; an acceleration time of less than 12 seconds refers to acceleration < 12

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(*) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country WHERE T3.country = 'USA' AND T1.acceleration < 12
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    How many Japanese cars weigh more than 2000 lbs? Japanese car refers to country = 'Japan'; weigh more than 2000 lbs refers to weight > 2000

    【Evidence】
    Japanese car refers to country = 'Japan'; weigh more than 2000 lbs refers to weight > 2000

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(*) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country WHERE T3.country = 'Japan' AND T1.weight > 2000
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    List the name of the most expensive car. car's name refers to car_name; the most expensive refers to max(price)

    【Evidence】
    car's name refers to car_name; the most expensive refers to max(price)

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.car_name FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID ORDER BY T2.price DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    What years did the Buick Skylark 320 get in production? year refers to model_year; Buick Skylark 320 refers to car_name = 'buick skylark 320'

    【Evidence】
    year refers to model_year; Buick Skylark 320 refers to car_name = 'buick skylark 320'

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T2.model_year FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T1.car_name = 'buick skylark 320'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    Which country produced the most expensive car in 1970? the most expensive refers to max(price); in 1970 refers to model_year = 1970

    【Evidence】
    the most expensive refers to max(price); in 1970 refers to model_year = 1970

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T3.country FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country INNER JOIN price AS T4 ON T4.ID = T1.ID WHERE T2.model_year = 1970 ORDER BY T4.price DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    How many cars with horsepower greater than 200 were produced in 1975? horsepower greater than 200 refers to horsepower > 200; in 1975 refers to model_year = 1975

    【Evidence】
    horsepower greater than 200 refers to horsepower > 200; in 1975 refers to model_year = 1975

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T2.model_year) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T1.horsepower > 200 AND T2.model_year = 1975
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    Calculate the percentage of American cars among all cars. American car refers to country = 'USA'; percentage = divide(count(ID where country = 'USA'), count(ID)) * 100%

    【Evidence】
    American car refers to country = 'USA'; percentage = divide(count(ID where country = 'USA'), count(ID)) * 100%

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(CASE WHEN T3.country = 'USA' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cars
【Schema】
# Table: data
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(mpg:REAL, Examples: [18.0, 15.0, 16.0]),
(cylinders:INTEGER, Examples: [8, 4, 6]),
(displacement:REAL, Examples: [307.0, 350.0, 318.0]),
(horsepower:INTEGER, Examples: [130, 165, 150]),
(weight:INTEGER, Examples: [3504, 3693, 3436]),
(acceleration:REAL, Examples: [12.0, 11.5, 11.0]),
(model:INTEGER, Examples: [70, 71, 72]),
(car_name:TEXT, Examples: [chevrolet chevelle malibu])
]
# Table: country
[
(origin:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country:TEXT, Examples: [USA, Europe, Japan])
]
# Table: price
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(price:REAL, Examples: [25561.59078, 24221.42273, 27240.84373])
]
# Table: production
[
(ID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(model_year:INTEGER, Primary Key, Examples: [1970, 1971, 1972]),
(country:INTEGER, Examples: [1, 3, 2])
]
【Foreign keys】
data.ID=price.ID
production.country=country.origin
production.ID=data.ID
production.ID=price.ID

    【Question】
    What is the average weight of Japanese cars with 4 cylinders that were produced from 1975 to 1980? Japanese car refers to country = 'Japan'; with 4 cylinders refers to cylinders = 4; produced from 1975 to 1980 refers to model_year BETWEEN 1975 AND 1980; average weight = avg(weight)

    【Evidence】
    Japanese car refers to country = 'Japan'; with 4 cylinders refers to cylinders = 4; produced from 1975 to 1980 refers to model_year BETWEEN 1975 AND 1980; average weight = avg(weight)

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT AVG(T1.weight) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country WHERE T2.model_year BETWEEN 1975 AND 1980 AND T1.cylinders = 4 AND T3.country = 'Japan'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 video_games
【Schema】
# Table: region_sales
[
(region_id:INTEGER, Examples: [1, 2, 3]),
(game_platform_id:INTEGER, Examples: [50, 51, 52]),
(num_sales:REAL, Examples: [3.5, 1.43, 0.51])
]
# Table: game
[
(id:INTEGER, Primary Key, Examples: [44, 45, 46]),
(genre_id:INTEGER, Examples: [4, 5, 11]),
(game_name:TEXT, Examples: [2 Games in 1: Sonic Advance & ChuChu Rocket!])
]
# Table: game_platform
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(game_publisher_id:INTEGER, Examples: [8564, 9852, 11063]),
(platform_id:INTEGER, Examples: [4, 7, 15]),
(release_year:INTEGER, Examples: [2007, 2006, 2011])
]
# Table: game_publisher
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(game_id:INTEGER, Examples: [10866, 9244, 5464]),
(publisher_id:INTEGER, Examples: [369, 328, 498])
]
# Table: platform
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(platform_name:TEXT, Examples: [Wii, NES, GB])
]
# Table: publisher
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(publisher_name:TEXT, Examples: [10TACLE Studios])
]
# Table: genre
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(genre_name:TEXT, Examples: [Action, Adventure, Fighting])
]
# Table: region
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(region_name:TEXT, Examples: [North America, Europe, Japan])
]
【Foreign keys】
region_sales.game_platform_id=game_platform.id
region_sales.region_id=region.id
game.genre_id=genre.id
game_platform.game_publisher_id=game_publisher.id
game_platform.platform_id=platform.id
game_publisher.game_id=game.id
game_publisher.publisher_id=publisher.id

    【Question】
    How many more games were sold on game platform ID 50 than on game platform ID 51 in region ID 1? result = subtract(sum(num_sales where game_platform_id = 50), sum(num_sales where game_platform_id = 51))

    【Evidence】
    result = subtract(sum(num_sales where game_platform_id = 50), sum(num_sales where game_platform_id = 51))

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT (SUM(CASE WHEN T.game_platform_id = 50 THEN T.num_sales ELSE 0 END) - SUM(CASE WHEN T.game_platform_id = 51 THEN T.num_sales ELSE 0 END)) * 100000 AS nums FROM region_sales AS T WHERE T.region_id = 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 video_games
【Schema】
# Table: region_sales
[
(region_id:INTEGER, Examples: [1, 2, 3]),
(game_platform_id:INTEGER, Examples: [50, 51, 52]),
(num_sales:REAL, Examples: [3.5, 1.43, 0.51])
]
# Table: game
[
(id:INTEGER, Primary Key, Examples: [44, 45, 46]),
(genre_id:INTEGER, Examples: [4, 5, 11]),
(game_name:TEXT, Examples: [2 Games in 1: Sonic Advance & ChuChu Rocket!])
]
# Table: game_platform
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(game_publisher_id:INTEGER, Examples: [8564, 9852, 11063]),
(platform_id:INTEGER, Examples: [4, 7, 15]),
(release_year:INTEGER, Examples: [2007, 2006, 2011])
]
# Table: game_publisher
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(game_id:INTEGER, Examples: [10866, 9244, 5464]),
(publisher_id:INTEGER, Examples: [369, 328, 498])
]
# Table: platform
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(platform_name:TEXT, Examples: [Wii, NES, GB])
]
# Table: publisher
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(publisher_name:TEXT, Examples: [10TACLE Studios])
]
# Table: genre
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(genre_name:TEXT, Examples: [Action, Adventure, Fighting])
]
# Table: region
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(region_name:TEXT, Examples: [North America, Europe, Japan])
]
【Foreign keys】
region_sales.game_platform_id=game_platform.id
region_sales.region_id=region.id
game.genre_id=genre.id
game_platform.game_publisher_id=game_publisher.id
game_platform.platform_id=platform.id
game_publisher.game_id=game.id
game_publisher.publisher_id=publisher.id

    【Question】
    Please list all the games that have the same game genre as 3D Lemmings. game refers to game_name; 3D Lemmings refers to game_name = '3D Lemmings'

    【Evidence】
    game refers to game_name; 3D Lemmings refers to game_name = '3D Lemmings'

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.game_name FROM game AS T1 WHERE T1.genre_id = ( SELECT T.genre_id FROM game AS T WHERE T.game_name = '3D Lemmings' )
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 video_games
【Schema】
# Table: region_sales
[
(region_id:INTEGER, Examples: [1, 2, 3]),
(game_platform_id:INTEGER, Examples: [50, 51, 52]),
(num_sales:REAL, Examples: [3.5, 1.43, 0.51])
]
# Table: game
[
(id:INTEGER, Primary Key, Examples: [44, 45, 46]),
(genre_id:INTEGER, Examples: [4, 5, 11]),
(game_name:TEXT, Examples: [2 Games in 1: Sonic Advance & ChuChu Rocket!])
]
# Table: game_platform
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(game_publisher_id:INTEGER, Examples: [8564, 9852, 11063]),
(platform_id:INTEGER, Examples: [4, 7, 15]),
(release_year:INTEGER, Examples: [2007, 2006, 2011])
]
# Table: game_publisher
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(game_id:INTEGER, Examples: [10866, 9244, 5464]),
(publisher_id:INTEGER, Examples: [369, 328, 498])
]
# Table: platform
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(platform_name:TEXT, Examples: [Wii, NES, GB])
]
# Table: publisher
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(publisher_name:TEXT, Examples: [10TACLE Studios])
]
# Table: genre
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(genre_name:TEXT, Examples: [Action, Adventure, Fighting])
]
# Table: region
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(region_name:TEXT, Examples: [North America, Europe, Japan])
]
【Foreign keys】
region_sales.game_platform_id=game_platform.id
region_sales.region_id=region.id
game.genre_id=genre.id
game_platform.game_publisher_id=game_publisher.id
game_platform.platform_id=platform.id
game_publisher.game_id=game.id
game_publisher.publisher_id=publisher.id

    【Question】
    How many action games are there in total? action game refers to genre_name = 'Action'

    【Evidence】
    action game refers to genre_name = 'Action'

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T1.id) FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T2.genre_name = 'Action'