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】
    How many times was Ford Maverick introduced to the market? 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(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】
    Which country produced the most fuel-efficient car? the most fuel-efficient refers to max(mpg)

    【Evidence】
    the most fuel-efficient refers to max(mpg)

    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 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 Dodge car is the cheapest? Dodge car refers to car_name LIKE 'dodge%'; the cheapest refers to min(price); name of the car refers to car_name

    【Evidence】
    Dodge car refers to car_name LIKE 'dodge%'; the cheapest refers to min(price); name of the car refers to car_name

    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 WHERE T1.car_name LIKE 'dodge%' ORDER BY T2.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】
    What is the name of the most expensive car that was produced by the USA? name of the car refers to car_name; the most expensive refers to max(price); produced by the USA refers to country = 'USA'

    【Evidence】
    name of the car refers to car_name; the most expensive refers to max(price); produced by the USA refers to country = 'USA'

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

SQL: SELECT T4.car_name FROM price AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country INNER JOIN data AS T4 ON T4.ID = T1.ID WHERE T3.country = 'USA' ORDER BY T1.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】
    Among the cars with an engine displacement of no less than 400 cubic millimeter, how many cars cost at least 30,000? engine displacement of no less than 400 cubic millimeter refers to displacement > 400; cost at least 30,000 refers to price > 30000

    【Evidence】
    engine displacement of no less than 400 cubic millimeter refers to displacement > 400; cost at least 30,000 refers to price > 30000

    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 price AS T2 ON T1.ID = T2.ID WHERE T1.displacement > 400 AND T2.price > 30000
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 year did Europe produce the most cars? year refers to model_year; Europe refers to country = 'Europe'; the most cars refers to max(model_year)

    【Evidence】
    year refers to model_year; Europe refers to country = 'Europe'; the most cars refers to max(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.model_year FROM production AS T1 INNER JOIN country AS T2 ON T1.country = T2.origin WHERE T2.country = 'Europe' GROUP BY T1.model_year ORDER BY COUNT(T1.model_year) 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 much is the Peugeot 505s Turbo Diesel? cost refers to price; Peugeot 505s Turbo Diesel refers to car_name = 'peugeot 505s turbo diesel'

    【Evidence】
    cost refers to price; Peugeot 505s Turbo Diesel refers to car_name = 'peugeot 505s turbo diesel'

    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 = 'peugeot 505s turbo diesel'
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 miles per square hour of the cheapest car produced by the USA? miles per square hour refers to acceleration; the cheapest refers to min(price); produced by the USA refers to country = 'USA'

    【Evidence】
    miles per square hour refers to acceleration; the cheapest refers to min(price); produced by the USA refers to country = 'USA'

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

SQL: SELECT T4.acceleration FROM price AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country INNER JOIN data AS T4 ON T4.ID = T1.ID WHERE T3.country = 'USA' 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】
    Which country produced the highest number of cars? Calculate the annual average number of cars that the said country produced from the very start to the present. the highest number of cars refers to max(country); annual average number = divide(count(ID), count(model_year))

    【Evidence】
    the highest number of cars refers to max(country); annual average number = divide(count(ID), count(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 T2.country, CAST(COUNT(T1.ID) AS REAL) / COUNT(DISTINCT T1.model_year) FROM production AS T1 INNER JOIN country AS T2 ON T1.country = T2.origin GROUP BY T2.country ORDER BY COUNT(T2.country) 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 percentage of cars that was produced by Japan among those that have a sweep volume of no less than 30? produced by Japan refers to country = 'Japan'; a sweep volume of no less than 30 refers to divide(displacement, cylinders) > 30; percentage = divide(count(ID where country = 'Japan'), count(ID)) * 100% where divide(displacement, cylinders) > 30

    【Evidence】
    produced by Japan refers to country = 'Japan'; a sweep volume of no less than 30 refers to divide(displacement, cylinders) > 30; percentage = divide(count(ID where country = 'Japan'), count(ID)) * 100% where divide(displacement, cylinders) > 30

    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 = 'Japan' 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 WHERE T1.displacement / T1.cylinders > 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】
    List the name of the cars with model year 1975. name of the car refers to car_name; model year 1975 refers to model_year = 1975

    【Evidence】
    name of the car refers to car_name; model year 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
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 price of cars from Europe. from Europe refers to country = 'Europe'; average price = avg(price) where country = 'Europe'

    【Evidence】
    from Europe refers to country = 'Europe'; average price = avg(price) where country = 'Europe'

    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 = 'Europe'
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 the car ID 15?

    【Evidence】
    

    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.ID = 15
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 of the cars from Japan weighed less than 3000? from Japan refers to country = 'Japan'; weighed less than 3000 refers to weight < 3000

    【Evidence】
    from Japan refers to country = 'Japan'; weighed less than 3000 refers to weight < 3000

    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 price AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country INNER JOIN data AS T4 ON T4.ID = T1.ID WHERE T3.country = 'Japan' AND T4.weight < 3000