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】
    Provide the name and model of the car with the highest price. car's name refers to car_name; the highest price refers to max(price)

    【Evidence】
    car's name refers to car_name; 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, T1.model 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 is the price of a Chevrolet Bel Air? Chevrolet Bel Air refers to car_name = 'chevrolet bel air'

    【Evidence】
    Chevrolet Bel Air refers to car_name = 'chevrolet bel air'

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

SQL: SELECT T2.price FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.car_name = 'chevrolet bel air'
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 price per car produced in Japan? produced in Japan refers to country = 'Japan'; average price per car = avg(price) where country = 'Japan'

    【Evidence】
    produced in Japan refers to country = 'Japan'; average price per car = avg(price) where country = 'Japan'

    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.price) FROM price 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'
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 car with the lowest price? the lowest price refers to min(price)

    【Evidence】
    the lowest price refers to min(price)

    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 price AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country ORDER BY T1.price ASC 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】
    Among the cars produced in 1975, provide IDs, names, and producing countries of the cars with the maximum number of cylinders. produced in 1975 refers to model_year = 1975; names refers to car_name; producing countries refers to country; the maximum number of cylinders refers to max(cylinders)

    【Evidence】
    produced in 1975 refers to model_year = 1975; names refers to car_name; producing countries refers to country; the maximum number of cylinders refers to max(cylinders)

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

SQL: SELECT T1.ID, T1.car_name, 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 WHERE T2.model_year = 1975 ORDER BY T1.cylinders 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 is the cheapest? Provide its acceleration, number of cylinders, and producing year. the cheapest refers to min(price); number of cylinders refers to cylinders; producing year refers to model_year

    【Evidence】
    the cheapest refers to min(price); number of cylinders refers to cylinders; producing year refers to model_year

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

SQL: SELECT T1.acceleration, T1.cylinders, T2.model_year FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN price AS T3 ON T3.ID = T2.ID ORDER BY T3.price ASC 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】
    List the names and prices of the cars with model 82 and mileage per gallon of greater than 30. car's name refers to car_name; model 82 refers to model = 82; mileage per gallon of greater than 30 refers to mpg > 30

    【Evidence】
    car's name refers to car_name; model 82 refers to model = 82; mileage per gallon of greater than 30 refers to mpg > 30

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

SQL: SELECT T2.car_name, T1.price FROM price AS T1 INNER JOIN data AS T2 ON T1.ID = T2.ID WHERE T2.model = 82 AND T2.mpg > 30
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 models of Ford Maverick were produced? Ford Maverick refers to car_name = 'ford maverick'

    【Evidence】
    Ford Maverick refers to car_name = 'ford maverick'

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

SQL: SELECT COUNT(DISTINCT T2.model_year) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T1.car_name = 'ford maverick'
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 cars that belong to the USA. belong to the USA refers to country = 'USA'; percentage = divide(count(ID where country = 'USA'), count(ID)) * 100%

    【Evidence】
    belong to the USA 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 T2.country = 'USA' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM production AS T1 INNER JOIN country AS T2 ON T1.country = T2.origin
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 average production rate per year from 1971 to 1980. Among them, name the cars with a weight of fewer than 1800 lbs. from 1971 to 1980 refers to model_year between 1971 and 1980; average production rate per year = divide(count(ID where model_year between 1971 and 1980), 9); car's name refers to car_name; a weight of fewer than 1800 lbs refers to weight < 1800

    【Evidence】
    from 1971 to 1980 refers to model_year between 1971 and 1980; average production rate per year = divide(count(ID where model_year between 1971 and 1980), 9); car's name refers to car_name; a weight of fewer than 1800 lbs refers to weight < 1800

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

SQL: SELECT CAST(COUNT(T1.ID) AS REAL) / 9 FROM production AS T1 INNER JOIN data AS T2 ON T2.ID = T1.ID WHERE T1.model_year BETWEEN 1971 AND 1980 UNION ALL SELECT DISTINCT T2.car_name FROM production AS T1 INNER JOIN data AS T2 ON T2.ID = T1.ID WHERE T1.model_year BETWEEN 1971 AND 1980 AND T2.weight < 1800
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 price of model 70 cars? model 70 refers to model = 70; average price = avg(price) where model = 70

    【Evidence】
    model 70 refers to model = 70; average price = avg(price) where model = 70

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

SQL: SELECT AVG(T2.price) FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.model = 70
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 price of Chevrolet Vega 2300? Chevrolet Vega 2300 refers to car_name = 'chevrolet vega 2300'

    【Evidence】
    Chevrolet Vega 2300 refers to car_name = 'chevrolet vega 2300'

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

SQL: SELECT T2.price FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.car_name = 'chevrolet vega 2300'
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 does Chevy C20 come from? Chevy C20 refers to car_name = 'chevy c20'

    【Evidence】
    Chevy C20 refers to car_name = 'chevy c20'

    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 WHERE T1.car_name = 'chevy c20'
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 price of Ford cars from model 1970 to 1980. Ford cars refers to car_name LIKE 'ford%'; from model 1970 to 1980 refers to model_year BETWEEN 1970 AND 1980

    【Evidence】
    Ford cars refers to car_name LIKE 'ford%'; from model 1970 to 1980 refers to model_year BETWEEN 1970 AND 1980

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

SQL: SELECT DISTINCT T3.price FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN price AS T3 ON T3.ID = T2.ID WHERE T1.car_name LIKE 'ford%' AND T2.model_year BETWEEN 1970 AND 1980