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】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    What is the location and number of female students in university ID 23 in 2011? in 2011 refers to year 2011; female students refers to DIVIDE(MULTIPLY(num_students, pct_female_students), 100); location refers to country_name

    【Evidence】
    in 2011 refers to year 2011; female students refers to DIVIDE(MULTIPLY(num_students, pct_female_students), 100); location refers to country_name

    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_name, CAST(T2.num_students * T2.pct_female_students AS REAL) / 100 FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T2.year = 2011 AND T1.id = 23
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    How many universities scored 40 in teaching criteria? scored 40 refers to score = 40; in teaching refers to criteria_name = 'Teaching'

    【Evidence】
    scored 40 refers to score = 40; in teaching refers to criteria_name = 'Teaching'

    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 ranking_criteria AS T1 INNER JOIN university_ranking_year AS T2 ON T1.id = T2.ranking_criteria_id WHERE T2.score = 40 AND T1.criteria_name = 'Teaching' AND T2.score = 40
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    Among the universities in United States of America, what is the percentage of female students in year 2016? female students refers to DIVIDE(MULTIPLY(num_students, pct_female_students), 100); in United States of America refers to country_name = 'United States of America'; percentage refers to DIVIDE(SUM(DIVIDE(MULTIPLY(num_students, pct_female_students), 100)), SUM(num_students))

    【Evidence】
    female students refers to DIVIDE(MULTIPLY(num_students, pct_female_students), 100); in United States of America refers to country_name = 'United States of America'; percentage refers to DIVIDE(SUM(DIVIDE(MULTIPLY(num_students, pct_female_students), 100)), SUM(num_students))

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

SQL: SELECT SUM(CAST(T2.pct_female_students * T2.num_students AS REAL) / 100) * 100 / SUM(T2.num_students) FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id INNER JOIN country AS T3 ON T3.id = T1.country_id WHERE T3.country_name = 'United States of America' AND T2.year = 2016
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    Calculate the difference between the total number of students and the number of international international students in Univeristy of Tokyo from 2011 to 2014. international students refers to DIVIDE(MULTIPLY(num_students, pct_international_students), 100); difference refers to SUBTRACT(SUM(num_students), SUM(DIVIDE(MULTIPLY(num_students, pct_international_students), 100))); in University of Tokyo refers to university_name = 'University of Tokyo'; from 2011 to 2014 refers to year BETWEEN 2011 AND 2014

    【Evidence】
    international students refers to DIVIDE(MULTIPLY(num_students, pct_international_students), 100); difference refers to SUBTRACT(SUM(num_students), SUM(DIVIDE(MULTIPLY(num_students, pct_international_students), 100))); in University of Tokyo refers to university_name = 'University of Tokyo'; from 2011 to 2014 refers to year BETWEEN 2011 AND 2014

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

SQL: SELECT SUM(T1.num_students) - SUM(CAST(T1.num_students * T1.pct_international_students AS REAL) / 100) FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.year BETWEEN 2011 AND 2014 AND T2.university_name = 'University of Tokyo'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 university
【Schema】
# Table: university_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(num_students:INTEGER, Examples: [20152, 2243, 11074]),
(student_staff_ratio:REAL, Examples: [8.9, 6.9, 9.0]),
(pct_international_students:INTEGER, Examples: [25, 27, 33]),
(pct_female_students:INTEGER, Examples: [33, 37, 42])
]
# Table: country
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_name:TEXT, Examples: [Argentina, Australia, Austria])
]
# Table: university
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(country_id:INTEGER, Examples: [73, 72, 33]),
(university_name:TEXT, Examples: [Harvard University])
]
# Table: university_ranking_year
[
(university_id:INTEGER, Examples: [1, 5, 2]),
(ranking_criteria_id:INTEGER, Examples: [1, 2, 3]),
(year:INTEGER, Examples: [2011, 2012, 2013]),
(score:INTEGER, Examples: [100, 98, 91])
]
# Table: ranking_system
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(system_name:TEXT, Examples: [Times Higher Education World University Ranking])
]
# Table: ranking_criteria
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(ranking_system_id:INTEGER, Examples: [1, 2, 3]),
(criteria_name:TEXT, Examples: [Teaching, International, Research])
]
【Foreign keys】
university_year.university_id=university.id
university.country_id=country.id
university_ranking_year.ranking_criteria_id=ranking_criteria.id
university_ranking_year.university_id=university.id
ranking_criteria.ranking_system_id=ranking_system.id

    【Question】
    List the names of universities with a score less than 28% of the average score of all universities in 2015. in 2015 refers to year = 2015; score less than 28% refers to score < MULTIPLY(avg(score), 0.28) where year = 2015; names of universities refers to university_name

    【Evidence】
    in 2015 refers to year = 2015; score less than 28% refers to score < MULTIPLY(avg(score), 0.28) where year = 2015; names of universities refers to university_name

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

SQL: SELECT T2.university_name FROM university_ranking_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.year = 2015 AND T1.score * 100 < ( SELECT AVG(score) * 28 FROM university_ranking_year WHERE year = 2015 )
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 sales_in_weather
【Schema】
# Table: sales_in_weather
[
(date:DATE, Primary Key, Examples: [2012-01-01]),
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(item_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(units:INTEGER, Examples: [0, 29, 2])
]
# Table: relation
[
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(station_nbr:INTEGER, Examples: [1, 14, 7])
]
# Table: weather
[
(station_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(date:DATE, Primary Key, Examples: [2012-01-01]),
(tmax:INTEGER, Examples: [52, 50, 32]),
(tmin:INTEGER, Examples: [31, 11, 9]),
(tavg:INTEGER, Examples: [42, 41, 22]),
(depart:INTEGER, Examples: [16, 12, -6]),
(dewpoint:INTEGER, Examples: [36, 26, 4]),
(wetbulb:INTEGER, Examples: [40, 35, 18]),
(heat:INTEGER, Examples: [23, 24, 43]),
(cool:INTEGER, Examples: [0, 5, 6]),
(sunrise:TEXT, Examples: [07:16:00, 07:15:00, 07:14:00]),
(sunset:TEXT, Examples: [16:26:00, 16:27:00, 16:28:00]),
(codesum:TEXT, Examples: [RA FZFG BR,  , SN]),
(snowfall:REAL, Examples: [0.0, 0.05, 0.2]),
(preciptotal:REAL, Examples: [0.05, 0.01, 0.0]),
(stnpressure:REAL, Examples: [29.78, 29.44, 29.67]),
(sealevel:REAL, Examples: [29.92, 29.62, 29.87]),
(resultspeed:REAL, Examples: [3.6, 9.8, 10.8]),
(resultdir:INTEGER, Examples: [20, 24, 31]),
(avgspeed:REAL, Examples: [4.6, 10.3, 11.6])
]
【Foreign keys】
relation.store_nbr=sales_in_weather.store_nbr
relation.station_nbr=weather.station_nbr

    【Question】
    How many units of item no.9 were sold in store no.1 on 2012/1/1? store no. 1 refers to store_nbr = 1; item no. 9 refers to item_nbr = 9; on 2012/1/1 refers to date = '2012-01-01'

    【Evidence】
    store no. 1 refers to store_nbr = 1; item no. 9 refers to item_nbr = 9; on 2012/1/1 refers to date = '2012-01-01'

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

SQL: SELECT units FROM sales_in_weather WHERE `date` = '2012-01-01' AND store_nbr = 1 AND item_nbr = 9
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 sales_in_weather
【Schema】
# Table: sales_in_weather
[
(date:DATE, Primary Key, Examples: [2012-01-01]),
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(item_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(units:INTEGER, Examples: [0, 29, 2])
]
# Table: relation
[
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(station_nbr:INTEGER, Examples: [1, 14, 7])
]
# Table: weather
[
(station_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(date:DATE, Primary Key, Examples: [2012-01-01]),
(tmax:INTEGER, Examples: [52, 50, 32]),
(tmin:INTEGER, Examples: [31, 11, 9]),
(tavg:INTEGER, Examples: [42, 41, 22]),
(depart:INTEGER, Examples: [16, 12, -6]),
(dewpoint:INTEGER, Examples: [36, 26, 4]),
(wetbulb:INTEGER, Examples: [40, 35, 18]),
(heat:INTEGER, Examples: [23, 24, 43]),
(cool:INTEGER, Examples: [0, 5, 6]),
(sunrise:TEXT, Examples: [07:16:00, 07:15:00, 07:14:00]),
(sunset:TEXT, Examples: [16:26:00, 16:27:00, 16:28:00]),
(codesum:TEXT, Examples: [RA FZFG BR,  , SN]),
(snowfall:REAL, Examples: [0.0, 0.05, 0.2]),
(preciptotal:REAL, Examples: [0.05, 0.01, 0.0]),
(stnpressure:REAL, Examples: [29.78, 29.44, 29.67]),
(sealevel:REAL, Examples: [29.92, 29.62, 29.87]),
(resultspeed:REAL, Examples: [3.6, 9.8, 10.8]),
(resultdir:INTEGER, Examples: [20, 24, 31]),
(avgspeed:REAL, Examples: [4.6, 10.3, 11.6])
]
【Foreign keys】
relation.store_nbr=sales_in_weather.store_nbr
relation.station_nbr=weather.station_nbr

    【Question】
    How many units of item no.9 were sold in store no.1 in total in January, 2012? store no. 1 refers to store_nbr = 1; item no. 9 refers to item_nbr = 9; in January refers to SUBSTR(date, 1, 4) = '2012' and SUBSTR(date, 6, 2) = '01'

    【Evidence】
    store no. 1 refers to store_nbr = 1; item no. 9 refers to item_nbr = 9; in January refers to SUBSTR(date, 1, 4) = '2012' and SUBSTR(date, 6, 2) = '01'

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

SQL: SELECT SUM(units) FROM sales_in_weather WHERE SUBSTR(`date`, 6, 2) = '01' AND SUBSTR(`date`, 1, 4) = '2012' AND item_nbr = 9 AND store_nbr = 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 sales_in_weather
【Schema】
# Table: sales_in_weather
[
(date:DATE, Primary Key, Examples: [2012-01-01]),
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(item_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(units:INTEGER, Examples: [0, 29, 2])
]
# Table: relation
[
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(station_nbr:INTEGER, Examples: [1, 14, 7])
]
# Table: weather
[
(station_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(date:DATE, Primary Key, Examples: [2012-01-01]),
(tmax:INTEGER, Examples: [52, 50, 32]),
(tmin:INTEGER, Examples: [31, 11, 9]),
(tavg:INTEGER, Examples: [42, 41, 22]),
(depart:INTEGER, Examples: [16, 12, -6]),
(dewpoint:INTEGER, Examples: [36, 26, 4]),
(wetbulb:INTEGER, Examples: [40, 35, 18]),
(heat:INTEGER, Examples: [23, 24, 43]),
(cool:INTEGER, Examples: [0, 5, 6]),
(sunrise:TEXT, Examples: [07:16:00, 07:15:00, 07:14:00]),
(sunset:TEXT, Examples: [16:26:00, 16:27:00, 16:28:00]),
(codesum:TEXT, Examples: [RA FZFG BR,  , SN]),
(snowfall:REAL, Examples: [0.0, 0.05, 0.2]),
(preciptotal:REAL, Examples: [0.05, 0.01, 0.0]),
(stnpressure:REAL, Examples: [29.78, 29.44, 29.67]),
(sealevel:REAL, Examples: [29.92, 29.62, 29.87]),
(resultspeed:REAL, Examples: [3.6, 9.8, 10.8]),
(resultdir:INTEGER, Examples: [20, 24, 31]),
(avgspeed:REAL, Examples: [4.6, 10.3, 11.6])
]
【Foreign keys】
relation.store_nbr=sales_in_weather.store_nbr
relation.station_nbr=weather.station_nbr

    【Question】
    What is the ID of the item that sold the best on 2012/1/1 in store no.1? sold on 2012/1/1 refers to date = '2012-01-01'; in store no.1 refers to store_nbr = 1; item sold the best refers to Max(units)

    【Evidence】
    sold on 2012/1/1 refers to date = '2012-01-01'; in store no.1 refers to store_nbr = 1; item sold the best refers to Max(units)

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

SQL: SELECT item_nbr FROM sales_in_weather WHERE `date` = '2012-01-01' AND store_nbr = 1 ORDER BY units DESC LIMIT 1
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 sales_in_weather
【Schema】
# Table: sales_in_weather
[
(date:DATE, Primary Key, Examples: [2012-01-01]),
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(item_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(units:INTEGER, Examples: [0, 29, 2])
]
# Table: relation
[
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(station_nbr:INTEGER, Examples: [1, 14, 7])
]
# Table: weather
[
(station_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(date:DATE, Primary Key, Examples: [2012-01-01]),
(tmax:INTEGER, Examples: [52, 50, 32]),
(tmin:INTEGER, Examples: [31, 11, 9]),
(tavg:INTEGER, Examples: [42, 41, 22]),
(depart:INTEGER, Examples: [16, 12, -6]),
(dewpoint:INTEGER, Examples: [36, 26, 4]),
(wetbulb:INTEGER, Examples: [40, 35, 18]),
(heat:INTEGER, Examples: [23, 24, 43]),
(cool:INTEGER, Examples: [0, 5, 6]),
(sunrise:TEXT, Examples: [07:16:00, 07:15:00, 07:14:00]),
(sunset:TEXT, Examples: [16:26:00, 16:27:00, 16:28:00]),
(codesum:TEXT, Examples: [RA FZFG BR,  , SN]),
(snowfall:REAL, Examples: [0.0, 0.05, 0.2]),
(preciptotal:REAL, Examples: [0.05, 0.01, 0.0]),
(stnpressure:REAL, Examples: [29.78, 29.44, 29.67]),
(sealevel:REAL, Examples: [29.92, 29.62, 29.87]),
(resultspeed:REAL, Examples: [3.6, 9.8, 10.8]),
(resultdir:INTEGER, Examples: [20, 24, 31]),
(avgspeed:REAL, Examples: [4.6, 10.3, 11.6])
]
【Foreign keys】
relation.store_nbr=sales_in_weather.store_nbr
relation.station_nbr=weather.station_nbr

    【Question】
    What was the temperature range of station no.1 on 2012/1/1? on 2012/1/1 refers to date = '2012-01-01'; temperature range refers to Subtract (tmax, tmin); station no.1 refers to station_nbr = 1

    【Evidence】
    on 2012/1/1 refers to date = '2012-01-01'; temperature range refers to Subtract (tmax, tmin); station no.1 refers to station_nbr = 1

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

SQL: SELECT tmax - tmin AS temrange FROM weather WHERE station_nbr = 1 AND `date` = '2012-01-01'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 sales_in_weather
【Schema】
# Table: sales_in_weather
[
(date:DATE, Primary Key, Examples: [2012-01-01]),
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(item_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(units:INTEGER, Examples: [0, 29, 2])
]
# Table: relation
[
(store_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(station_nbr:INTEGER, Examples: [1, 14, 7])
]
# Table: weather
[
(station_nbr:INTEGER, Primary Key, Examples: [1, 2, 3]),
(date:DATE, Primary Key, Examples: [2012-01-01]),
(tmax:INTEGER, Examples: [52, 50, 32]),
(tmin:INTEGER, Examples: [31, 11, 9]),
(tavg:INTEGER, Examples: [42, 41, 22]),
(depart:INTEGER, Examples: [16, 12, -6]),
(dewpoint:INTEGER, Examples: [36, 26, 4]),
(wetbulb:INTEGER, Examples: [40, 35, 18]),
(heat:INTEGER, Examples: [23, 24, 43]),
(cool:INTEGER, Examples: [0, 5, 6]),
(sunrise:TEXT, Examples: [07:16:00, 07:15:00, 07:14:00]),
(sunset:TEXT, Examples: [16:26:00, 16:27:00, 16:28:00]),
(codesum:TEXT, Examples: [RA FZFG BR,  , SN]),
(snowfall:REAL, Examples: [0.0, 0.05, 0.2]),
(preciptotal:REAL, Examples: [0.05, 0.01, 0.0]),
(stnpressure:REAL, Examples: [29.78, 29.44, 29.67]),
(sealevel:REAL, Examples: [29.92, 29.62, 29.87]),
(resultspeed:REAL, Examples: [3.6, 9.8, 10.8]),
(resultdir:INTEGER, Examples: [20, 24, 31]),
(avgspeed:REAL, Examples: [4.6, 10.3, 11.6])
]
【Foreign keys】
relation.store_nbr=sales_in_weather.store_nbr
relation.station_nbr=weather.station_nbr

    【Question】
    Please list the dates on which the temperature of station no.2 was above the 30-year normal. temperature above the 30-year normal refers to depart > 0; station no.2 refers to station_nbr = 2

    【Evidence】
    temperature above the 30-year normal refers to depart > 0; station no.2 refers to station_nbr = 2

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

SQL: SELECT `date` FROM weather WHERE station_nbr = 2 AND depart > 0