Database: shooting
Question: In how many cases where the subject was a female was the subject's status listed as Deceased?
Evidence:  female refers to gender = 'F'; subject's status listed as Deceased refers to subject_statuses = 'Deceased'
SQL: SELECT COUNT(T1.case_number) FROM incidents AS T1 INNER JOIN subjects AS T2 ON T1.case_number = T2.case_number WHERE T2.gender = 'F' AND T1.subject_statuses = 'Deceased'

Database: talkingdata
Question: Identify by their id all the devices that are used by women who are in the age range of 29 to 31 years.
Evidence: id refers to device_id; women refers to gender = 'F'; age range of 29 to 31 years refers to age between 29 and 31;
SQL: SELECT device_id FROM gender_age_train WHERE age BETWEEN 29 AND 31 AND gender = 'F'

Database: simpson_episodes
Question: What is the percentage of star score 5 that was collected by title "Sex, Pies and Idiot Scrapes"?
Evidence: percentage = DIVIDE(SUM(stars = 5), COUNT(stars)) as percentage
SQL: SELECT CAST(SUM(CASE WHEN T2.stars = 5 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T1.title = 'Sex, Pies and Idiot Scrapes';

Database: retails
Question: How many orders in 1998 had a total price under 950?
Evidence: 1998 refers to year(o_orderdate) = '1998'; a total price under 950 refers to o_totalprice < 950
SQL: SELECT COUNT(o_orderkey) AS countorders FROM orders WHERE STRFTIME('%Y', o_orderdate) = '1998' AND o_totalprice < 950

Database: language_corpus
Question: What are the titles of the top 5 Catalan language Wikipedia page with the least number of different words? Indicate each title's word id that has appeared the most in the said pages.
Evidence: least number of different words refers to min(words); word id refers to wid; appeared the most refers to max(occurrences)
SQL: SELECT T1.title FROM pages AS T1 INNER JOIN pages_words AS T2 ON T1.pid = T2.pid ORDER BY T1.words LIMIT 5

Database: legislator
Question: What are the Facebook, Twitter and YouTube usernames of Adam Kinzinger?
Evidence: Facebook, Twitter and YouTube usernames refers to facebook, twitter, youtube; Adam Kinzinger is an official_full_name
SQL: SELECT T2.facebook FROM current AS T1 INNER JOIN `social-media` AS T2 ON T2.bioguide = T1.bioguide_id WHERE T1.official_full_name = 'Adam Kinzinger'

Database: restaurant
Question: In which counties are there A&W Root Beer Restaurants?
Evidence: A&W Root Beer Restaurant refers to label = 'a & w root beer'
SQL: SELECT DISTINCT T2.county FROM generalinfo AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T1.label = 'a & w root beer'

Database: professional_basketball
Question: How many players with the first name Joe were drafted in 1970?
Evidence: drafted in 1970 refers to draftYear = 1970
SQL: SELECT COUNT(DISTINCT playerID) FROM draft WHERE firstName = 'Joe' AND draftYear = 1970

Database: cookbook
Question: What is the percentage calories protein of Raspberry Chiffon Pie?
Evidence: Raspberry Chiffon Pie refers title; percentage calories protein refers to pcnt_cal_prot
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'

Database: student_loan
Question: Calculate the number of students who are not disabled.
Evidence: students who are not disabled refers to person.name who are NOT in disabled.name;
SQL: SELECT COUNT(CASE  WHEN T2.name IS NULL THEN T1.name END) AS "number" FROM person AS T1 LEFT JOIN disabled AS T2 ON T2.name = T1.name

Database: world_development_indicators
Question: List the East Asia & Pacific countries which are under the High income: nonOECD group. Please include their alpha code.
Evidence: the East Asia & Pacific countries are where Region = 'East Asia & Pacific'; High income: nonOECD group is where IncomeGroup = 'High income: nonOECD'
SQL: SELECT CountryCode, Alpha2Code FROM Country WHERE Region = 'East Asia & Pacific' AND IncomeGroup = 'High income: nonOECD'

Database: retail_world
Question: Please name any two products that have the highest satisfaction levels among users of Heli Swaren GmbH & Co. KG.
Evidence: High reorder level generally means high user satisfaction; the highest satisfaction levels refer to MAX(ReorderLevel); two products refer to ProductName LIMIT 2; CompanyName = 'Heli Swaren GmbH & Co. KG';
SQL: SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Heli Swaren GmbH & Co. KG' ORDER BY T1.ReorderLevel DESC LIMIT 2

Database: movie_platform
Question: Who was the earliest user created a list but didn't get any followers? Give the user ID.
Evidence: earliest user created a list refers to MIN(list_creation_date_utc); didn't get any followers refers to user_subscriber = 0
SQL: SELECT user_id FROM lists_users WHERE user_subscriber = 0 ORDER BY list_creation_date_utc LIMIT 1

Database: app_store
Question: How many negative comments are there in all the apps with 100,000,000+ installs?
Evidence: negative comment refers to Sentiment = 'Negative'; Installs = '100,000,000+';
SQL: SELECT COUNT(T2.Sentiment) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Installs = '100,000,000+' AND T2.Sentiment = 'Negative'

Database: movie_3
Question: What language was the most used in movies released in 2006?
Evidence: released in 2006 refers to release_year = 2006; the most used language refers to MAX(COUNT(language_id))
SQL: SELECT T.language_id FROM ( SELECT T1.language_id, COUNT(T1.language_id) AS num FROM film AS T1 INNER JOIN language AS T2 ON T1.language_id = T2.language_id WHERE STRFTIME('%Y',T1.release_year) = '2006' GROUP BY T1.language_id ) AS T ORDER BY T.num DESC LIMIT 1

Database: retail_world
Question: What are the names of the suppliers whose products have the highest user satisfaction?
Evidence: name of the supplier refers to SupplierID; highest user satisfaction refers to max(ReorderLevel)
SQL: SELECT DISTINCT T2.CompanyName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.ReorderLevel = ( SELECT MAX(ReorderLevel) FROM Products )

Database: university
Question: Calculate the average score of university ID 79 between year 2013 to 2015.
Evidence: average score refers to avg(score); between year 2013 to 2015 refers to year BETWEEN 2013 AND 2015
SQL: SELECT AVG(score) FROM university_ranking_year WHERE year BETWEEN 2013 AND 2015 AND university_id = 79

Database: video_games
Question: What is the genre of the game titled '999: Nine Hours, Nine Persons, Nine Doors' ?
Evidence: genre of the game refers to genre_name; '999: Nine Hours, Nine Persons, Nine Doors' refers to game_name = '999: Nine Hours, Nine Persons, Nine Doors';
SQL: SELECT T2.genre_name FROM game AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.id WHERE T1.game_name = '999: Nine Hours, Nine Persons, Nine Doors'

Database: world_development_indicators
Question: What is the average value of Adjusted net enrolment rate, primary, both sexes (%) indicator in Algeria from 1975 to 1980?
Evidence: the average value of Adjusted net enrolment rate, primary, both sexes (%) is DIVIDE(SUM(Value), SUM(IndicatorName = 'Adjusted net enrolment rate, primary, both sexes (%)')); Year BETWEEN 1975 AND 1980; Algeria is the name of country where CountryName = 'Algeria'
SQL: SELECT CAST(SUM(Value) AS REAL) / COUNT(CountryCode) FROM Indicators WHERE CountryName = 'Algeria' AND Year > 1974 AND Year < 1981 AND IndicatorName = 'Adjusted net enrolment rate, primary, both sexes (%)'