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】
    Among the cars produced in year 1973, how many of the cars have horsepower less than 100? produced in year 1973 refers to model_year = 1973; have horsepower less than 100 refers to horsepower < 100

    【Evidence】
    produced in year 1973 refers to model_year = 1973; have horsepower less than 100 refers to horsepower < 100

    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 WHERE T2.model_year = 1973 AND T1.horsepower < 100
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 ID of cars from Japan worth greater than 35000 and have an acceleration of 14. from Japan refers to country = 'Japan'; worth greater than 35000 refers to price > 35000; have an acceleration of 14 refers to acceleration = 14

    【Evidence】
    from Japan refers to country = 'Japan'; worth greater than 35000 refers to price > 35000; have an acceleration of 14 refers to acceleration = 14

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

SQL: SELECT T4.ID 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 T1.price > 3500 AND T4.acceleration = 14
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】
    Give the model year of the heaviest car. the heaviest refers to max(weight)

    【Evidence】
    the heaviest refers to max(weight)

    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 ORDER BY T1.weight 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 horsepower and model year of the car named Subaru Dl? the car named Subaru Dl refers to car_name = 'subaru dl'

    【Evidence】
    the car named Subaru Dl refers to car_name = 'subaru dl'

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

SQL: SELECT T1.horsepower, T2.model_year FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T1.car_name = 'subaru dl'
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 originated from Japan, what is the name of the car with the highest price? from Japan refers to country = 'Japan'; name of the car refers to car_name; the highest price refers to max(price)

    【Evidence】
    from Japan refers to country = 'Japan'; name of the car 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 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 = 'Japan' 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】
    What are the names of the cars worth 20000? name of the car refers to car_name; worth 20000 refers to price = 20000

    【Evidence】
    name of the car refers to car_name; worth 20000 refers to price = 20000

    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 T2.price = 20000
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 worth greater than 40000 were from the USA? worth greater than 40000 refers to price > 40000; from the USA refers to country = 'USA'

    【Evidence】
    worth greater than 40000 refers to price > 40000; from 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 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 WHERE T3.country = 'USA' AND T1.price > 40000
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 price and country origin of the car named Ford Maverick. country origin refers to country; Ford Maverick refers to car_name = 'ford maverick'

    【Evidence】
    country origin refers to country; 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 DISTINCT T1.price, 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 INNER JOIN data AS T4 ON T4.ID = T1.ID WHERE T4.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】
    List the car's name with a price worth greater than 85% of the average price of all cars. car's name refers to car_name; a price worth greater than 85% of the average price of all cars refers to price > multiply(avg(price), 0.85)

    【Evidence】
    car's name refers to car_name; a price worth greater than 85% of the average price of all cars refers to price > multiply(avg(price), 0.85)

    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 T2.price * 100 > ( SELECT AVG(price) * 85 FROM price )
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 difference between the number of cars that has a horsepower of 130 with the model year 1970 and model year 1976 a horsepower of 130 refers to horsepower = 130; difference = subtract(count(ID where model_year = 1970), count(ID where model_year = 1976)) where horsepower = 130

    【Evidence】
    a horsepower of 130 refers to horsepower = 130; difference = subtract(count(ID where model_year = 1970), count(ID where model_year = 1976)) where horsepower = 130

    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 T2.model_year = 1970 THEN 1 ELSE 0 END) - SUM(CASE WHEN T2.model_year = 1976 THEN 1 ELSE 0 END) FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T1.horsepower = 130
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 from Asia, list the IDs of cars that were introduced in 1979. from Asia refers to country = 'Japan'; introduced in 1979 refers to model_year = 1979

    【Evidence】
    from Asia refers to country = 'Japan'; introduced in 1979 refers to model_year = 1979

    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 FROM production AS T1 INNER JOIN country AS T2 ON T1.country = T2.origin WHERE T2.country = 'Japan' AND T1.model_year = 1979
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 mileage per gallon? the lowest mileage per gallon refers to min(mpg)

    【Evidence】
    the lowest mileage per gallon refers to min(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 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】
    Provide the name, model, sweep volume, and introduced year of the car with the best crash protection. car's name refers to car_name; sweep volume = divide(displacement, cylinders); introduced year refers to model_year; the best crash protection refers to max(weight)

    【Evidence】
    car's name refers to car_name; sweep volume = divide(displacement, cylinders); introduced year refers to model_year; the best crash protection refers to max(weight)

    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, T1.displacement / T1.cylinders, T2.model_year FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID ORDER BY T1.weight 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 introduced in 1977, provide the names and the horse powers of cars from Europe. introduced in 1977 refers to model_year = 1977; car's name refers to car_name; from Europe refers to country = 'Europe'

    【Evidence】
    introduced in 1977 refers to model_year = 1977; car's name refers to car_name; from Europe refers to 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 T1.car_name, T1.horsepower 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 = 1977 AND T3.country = 'Europe'