Database: codebase_comments
Question: How many XML format does the github address "https://github.com/dogeth/vss2git.git" have?
Evidence: Xml format refers to CommentisXml, github address refers to Url; Url = 'https://github.com/dogeth/vss2git.git';
SQL: SELECT COUNT(T3.CommentIsXml) FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId INNER JOIN Method AS T3 ON T2.Id = T3.SolutionId WHERE T1.Url = 'https://github.com/dogeth/vss2git.git' AND T3.CommentIsXml = 1

Database: book_publishing_company
Question: List all the titles and year to date sales by author who are not on contract.
Evidence: year to date sales refers to ytd_sales; not on contract refers to contract = 0
SQL: SELECT T1.title_id, T1.ytd_sales FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T3.contract = 0

Database: movies_4
Question: What is the percentage of romance films among films produced in India in 2015?
Evidence: romance films refers to genre_name = 'Romance'; in India refers to country_name = 'India'; 2015 refers to release_date BETWEEN '2015-01-01' AND '2015-01-31'; percentage = divide(sum(movie_id) when genre_name = 'Romance', count(movie_id)) as percentage
SQL: SELECT CAST(COUNT(CASE WHEN T4.genre_name = 'Romance' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_COUNTry AS T3 ON T1.movie_id = T3.movie_id INNER JOIN genre AS T4 ON T2.genre_id = T4.genre_id INNER JOIN COUNTry AS T5 ON T3.COUNTry_id = T5.COUNTry_id WHERE T5.COUNTry_name = 'India' AND T1.release_date BETWEEN '2015-01-01' AND '2015-12-31'

Database: talkingdata
Question: What are the categories that app user ID7324884708820020000 belongs to?
Evidence: app user ID refers to app_id; app_id = 7324884708820020000;
SQL: SELECT T1.category FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T2.app_id = 7324884708820020000

Database: address
Question: List the bad alias of the postal point located in Camuy.
Evidence: postal points refer to zip_code; Camuy is the city;
SQL: SELECT T1.bad_alias FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.city = 'Camuy'

Database: retail_world
Question: Which supplier supplies the most amount of products?
Evidence: supplier refers to SupplierID; most amount refers to max(count(ProductID))
SQL: SELECT T2.CompanyName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID GROUP BY T2.SupplierID, T2.CompanyName ORDER BY COUNT(T1.ProductName) DESC LIMIT 1

Database: beer_factory
Question: How many Henry Weinhard's were bought by Nicholas Sparks?
Evidence: Henry Weinhard's refers to BrandName = 'Henry Weinhard''s';
SQL: SELECT COUNT(T1.CustomerID) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeer AS T3 ON T2.RootBeerID = T3.RootBeerID INNER JOIN rootbeerbrand AS T4 ON T3.BrandID = T4.BrandID WHERE T1.First = 'Nicholas' AND T1.Last = 'Sparks' AND T4.BrandName LIKE 'Henry Weinhard%s'

Database: european_football_1
Question: For all the games ended up with 1-1, what percentage of them are from Liga NOS division?
Evidence: 1-1 is a score where FTHG = '1' and FTAG = '1'; Liga NOS is the name of division; DIVIDE(COUNT(Div where FTHG = '1', FTAG = '1', name = 'Liga NOS'), COUNT(Div where FTHG = '1' and FTAG = '1')) as percentage;
SQL: SELECT CAST(COUNT(CASE WHEN T2.name = 'Liga NOS' THEN T1.Div ELSE NULL END) AS REAL) * 100 / COUNT(T1.Div) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.FTHG = 1 AND FTAG = 1

Database: authors
Question: List all the paper that were under the conference homepage URL "http://www.irma-international.org/".
Evidence: paper refers to Paper.Title; http://www.irma-international.org/ is the HomePage
SQL: SELECT T1.Title FROM Paper AS T1 INNER JOIN Conference AS T2 ON T1.ConferenceId = T2.Id WHERE T2.HomePage = 'http://www.irma-international.org/'

Database: book_publishing_company
Question: Which title is about helpful hints on how to use your electronic resources, which publisher published it and what is the price of this book?
Evidence: publisher refers to pub_name; about the title refers to notes
SQL: SELECT T1.title, T2.pub_name, T1.price FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.notes = 'Helpful hints on how to use your electronic resources to the best advantage.'

Database: movie_3
Question: What is the postal code of the address 692 Joliet Street?
SQL: SELECT postal_code FROM address WHERE address = '692 Joliet Street'

Database: world_development_indicators
Question: What are the indicator codes for the Republic of Albania in the year 1960?
Evidence: the Republic of Albania refers to LongName = 'Republic of Albania'; in the year 1960 refers to Year = '1960'
SQL: SELECT DISTINCT T1.IndicatorCode FROM Indicators AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.Year = 1960 AND T2.LongName = 'Republic of Albania'

Database: regional_sales
Question: Between 2018 to 2020, what is the average amount of shipped orders per year under Carl Nguyen?
Evidence: shipped refers to ShipDate; between 2018 and 2020 refers to SUBSTR(ShipDate, -2) IN ('18', '19', '20'); 'Carl Nguyen' is the name of Sales Team; average shipped orders per year = Divide (Count(OrderNumber), 3)
SQL: SELECT CAST(COUNT(T1.OrderNumber) AS REAL) / 3 FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE (T2.`Sales Team` = 'Carl Nguyen' AND ShipDate LIKE '%/%/18') OR (T2.`Sales Team` = 'Carl Nguyen' AND ShipDate LIKE '%/%/19') OR (T2.`Sales Team` = 'Carl Nguyen' AND ShipDate LIKE '%/%/20')

Database: beer_factory
Question: How many root beers of the Bulldog were purchased in August, 2014?
Evidence: Bulldog refers to BrandName = 'Bulldog'; purchased in August, 2014 refers to SUBSTR(TransactionDate, 1, 4) = '2014' AND SUBSTR(TransactionDate, 6, 2) = '08';
SQL: SELECT COUNT(T1.BrandID) FROM rootbeer AS T1 INNER JOIN `transaction` AS T2 ON T1.RootBeerID = T2.RootBeerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID WHERE T2.TransactionDate LIKE '2014-08%' AND T3.BrandName = 'Bulldog'

Database: retail_world
Question: Identify the total number of orders placed by the customer 'Laughing Bacchus Wine Cellars' and it's average value.
Evidence: 'Laughing Bacchus Wine Cellars' refers to CompanyName; calculation = DIVIDE(SUM(UnitPrice * Quantity * SUBTRACT(1, Discount)), COUNT(OrderID))
SQL: SELECT COUNT(T2.OrderID) , SUM(T3.UnitPrice * T3.Quantity * (1 - T3.Discount)) / COUNT(T2.OrderID) FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN `Order Details` AS T3 ON T2.OrderID = T3.OrderID WHERE T1.CompanyName = 'Laughing Bacchus Wine Cellars'

Database: simpson_episodes
Question: How many people were considered as prospective recipients of the "Animation" award?
Evidence: prospective recipients refers to result = 'Nominee'
SQL: SELECT COUNT(*) FROM Award WHERE award = 'Animation' AND result = 'Nominee';

Database: coinmarketcap
Question: Name the coins that have three tags.
Evidence: have three tags refers to length(tag_names)-length(replace(tag_names,',','')) = 2
SQL: SELECT name FROM coins WHERE LENGTH(tag_names) - LENGTH(replace(tag_names, ',', '')) = 2