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】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    What is the percentage calories protein of Raspberry Chiffon Pie? Raspberry Chiffon Pie refers title; percentage calories protein refers to pcnt_cal_prot

    【Evidence】
    Raspberry Chiffon Pie refers title; percentage calories protein refers to pcnt_cal_prot

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

SQL: SELECT pcnt_cal_prot FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Raspberry Chiffon Pie'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    How many ingredients are required to make the Raspberry Chiffon Pie? Raspberry Chiffon Pie refer to title

    【Evidence】
    Raspberry Chiffon Pie refer to title

    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 Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T1.title = 'Raspberry Chiffon Pie'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    List the names of alcohol free recipes. alcohol free refers to alcohol = 0

    【Evidence】
    alcohol free refers to alcohol = 0

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

SQL: SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T2.alcohol = 0
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    What is the average vitamin C amount of all cakes? average vitamin C refers to AVG(vitamin_c); all cakes refers to title LIKE '%cake%'

    【Evidence】
    average vitamin C refers to AVG(vitamin_c); all cakes refers to title LIKE '%cake%'

    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.vitamin_c) FROM Nutrition AS T1 INNER JOIN Recipe AS T2 ON T2.recipe_id = T1.recipe_id WHERE T2.title LIKE '%cake%'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    How many dairy recipes can serve more than 10 people? dairy recipes refers to category = 'dairy'; serve more than 10 people refers to servings > 10

    【Evidence】
    dairy recipes refers to category = 'dairy'; serve more than 10 people refers to servings > 10

    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 Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T3.category = 'dairy' AND T1.servings > 10
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    List the names of recipes that can lead to constipation. lead to constipation refers to iron > 20

    【Evidence】
    lead to constipation refers to iron > 20

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

SQL: SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T2.iron > 20
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    Which recipe has the highest calories? the highest calories refers to MAX(calories)

    【Evidence】
    the highest calories refers to MAX(calories)

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

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

    【Schema】
    【DB_ID】 cookbook
【Schema】
# Table: Quantity
[
(quantity_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(recipe_id:INTEGER, Examples: [214, 215, 216]),
(ingredient_id:INTEGER, Examples: [1613, 3334, 2222]),
(max_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(min_qty:REAL, Examples: [2.0, 0.25, 0.5]),
(unit:TEXT, Examples: [cup(s), teaspoon(s), 14 oz. can(s)]),
(preparation:TEXT, Examples: [melted, or water, divided]),
(optional:TEXT, Examples: [FALSE, TRUE])
]
# Table: Nutrition
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(protein:REAL, Examples: [5.47, 5.7, 4.9]),
(carbo:REAL, Examples: [41.29, 23.75, 26.88]),
(alcohol:REAL, Examples: [0.0, 1.93, 2.7]),
(total_fat:REAL, Examples: [11.53, 1.08, 1.1]),
(sat_fat:REAL, Examples: [2.21, 0.58, 0.06]),
(cholestrl:REAL, Examples: [1.39, 3.48, 3.46]),
(sodium:REAL, Examples: [260.78, 46.17, 41.79]),
(iron:REAL, Examples: [0.81, 0.57, 0.37]),
(vitamin_c:REAL, Examples: [8.89, 13.02, 6.13]),
(vitamin_a:REAL, Examples: [586.2, 2738.24, 1521.1]),
(fiber:REAL, Examples: [0.87, 0.62, 0.34]),
(pcnt_cal_carb:REAL, Examples: [56.8, 67.38, 78.45]),
(pcnt_cal_fat:REAL, Examples: [35.68, 6.89, 7.24]),
(pcnt_cal_prot:REAL, Examples: [7.53, 16.17, 14.3]),
(calories:REAL, Examples: [290.79, 141.01, 137.06])
]
# Table: Recipe
[
(recipe_id:INTEGER, Primary Key, Examples: [214, 215, 216]),
(title:TEXT, Examples: [Raspberry Chiffon Pie]),
(subtitle:TEXT, Examples: [with Banana Cream Whip]),
(servings:INTEGER, Examples: [10, 4, 8]),
(yield_unit:TEXT, Examples: [1 pie, 8 tarts, 2 quarts]),
(prep_min:INTEGER, Examples: [20, 5, 10]),
(cook_min:INTEGER, Examples: [8, 2, 13]),
(stnd_min:INTEGER, Examples: [305, 65, 0]),
(source:TEXT, Examples: [The California Tree Fruit Agreement]),
(intro:TEXT),
(directions:TEXT)
]
# Table: Ingredient
[
(ingredient_id:INTEGER, Primary Key, Examples: [1, 6, 10]),
(category:TEXT, Examples: [dairy, Mexican products, cereals]),
(name:TEXT, Examples: [1% lowfat cottage cheese]),
(plural:TEXT, Examples: [s, #NAME?, es])
]
【Foreign keys】
Quantity.recipe_id=Recipe.recipe_id
Quantity.ingredient_id=Ingredient.ingredient_id
Quantity.recipe_id=Nutrition.recipe_id
Nutrition.recipe_id=Recipe.recipe_id

    【Question】
    How many recipes are non-dairy? non-dairy refers to category NOT LIKE '%dairy"

    【Evidence】
    non-dairy refers to category NOT LIKE '%dairy"

    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.recipe_id) FROM Ingredient AS T1 INNER JOIN Quantity AS T2 ON T2.ingredient_id = T1.ingredient_id INNER JOIN Nutrition AS T3 ON T3.recipe_id = T2.recipe_id WHERE T1.category NOT LIKE '%dairy%'