1sf/bird-sql-train-with-schema huggingface dataset:
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What is the difference in the average number of sales per day of root beer brands that contain honey and that don’t contain honey.
Evidence: difference in the average = SUBTRACT(DIVIDE(MULTIPLY(SUM(Honey = 'TRUE'), 1.0), COUNT(TransactionDate)), DIVIDE(MULTIPLY(SUM(Honey = 'FALSE'), 1.0), COUNT(TransactionDate))); contain honey refers to Honey = 'TRUE'; don’t contain honey refers to Honey = 'FALSE'
SQL: SELECT (CAST(SUM(CASE WHEN T1.Honey = 'TRUE' THEN 1 ELSE 0 END) AS REAL) / COUNT(DISTINCT T3.TransactionDate)) - (CAST(SUM(CASE WHEN T1.Honey <> 'TRUE' THEN 1 ELSE 0 END) AS REAL) / COUNT(DISTINCT T3.TransactionDate)) FROM rootbeerbrand AS T1 INNER JOIN rootbeer AS T2 ON T1.BrandID = T2.BrandID INNER JOIN `transaction` AS T3 ON T2.RootBeerID = T3.RootBeerID
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: Find and list the full name and email of the customers who used American Express cards in Sac State Union.
Evidence: full name = First, Last; American Express cards refers to CreditCardType = 'American Express'; Sac State Union refers to LocationName = 'Sac State Union';
SQL: SELECT DISTINCT T1.First, T1.Last, T1.Email FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN location AS T3 ON T2.LocationID = T3.LocationID WHERE T3.LocationName = 'Sac State Union' AND T2.CreditCardType = 'American Express'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: In the reviews of September 2014. Which brand of beers obtained the highest star ratings?
Evidence: September 2014 refers to ReviewDate LIKE '2014-09%'; brand of beers refers to BrandName; highest star ratings refers to MAX(StarRating);
SQL: SELECT DISTINCT T1.BrandName FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T1.BrandID = T2.BrandID WHERE T2.StarRating = 5 AND T2.ReviewDate BETWEEN '2014-09-01' AND '2014-09-30'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What is the precise location of all paying customers with American Express?
Evidence: precise location refers to Latitude, Longitude; American Express refers to CreditCardType = 'American Express';
SQL: SELECT DISTINCT T2.Latitude, T2.Longitude FROM `transaction` AS T1 INNER JOIN geolocation AS T2 ON T1.LocationID = T2.LocationID WHERE T1.CreditCardType = 'American Express'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: How many Folsom customers prefer to pay with Visa?
Evidence: Folsom refers to City = 'Folsom'; Visa refers to CreditCardType = 'Visa';
SQL: SELECT COUNT(T1.CustomerID) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.City = 'Folsom' AND T2.CreditCardType = 'Visa'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: From which cities are the customers who gave 5 stars in their reviews in November 2012?
Evidence: 5 stars refers to StarRating = 5; in November 2012 refers to ReviewDate LIKE '2012-11%';
SQL: SELECT DISTINCT T1.City FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.StarRating = 5 AND T2.ReviewDate BETWEEN '2012-11-01' AND '2012-11-30'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What brands of beer has Peg Winchester consumed?
Evidence: brands of beer refers to BrandName;
SQL: SELECT T3.BrandName FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeerbrand AS T3 ON T2.BrandID = T3.BrandID WHERE T1.First = 'Peg' AND T1.Last = 'Winchester'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What brand of beer has been the worst rated most times?
Evidence: brand of beer refers to BrandName; worst rated most times refers to MAX(COUNT(StarRating = 1));
SQL: SELECT T1.BrandName FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T2.BrandID = T1.BrandID WHERE T2.StarRating = 1 GROUP BY T1.BrandName ORDER BY COUNT(T1.BrandName) DESC LIMIT 1
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What credit card is the most used in the purchase of non-alcoholic beer?
Evidence: credit card that is the most used refers to MAX(COUNT(CreditCardType)); non-alcoholic beer refers to Alcoholic = 'FALSE';
SQL: SELECT T2.CreditCardType 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 T3.Alcoholic = 'FALSE' GROUP BY T2.CreditCardType ORDER BY COUNT(T2.CreditCardType) DESC LIMIT 1
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What is the name of all the customers who have ever given a 5-star review?
Evidence: name of the customer = First, Last; 5-star review refers to StarRating = 5;
SQL: SELECT T1.First, T1.Last FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.StarRating = 5
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: At what latitude is the Thomas Kemper brand beer consumed the most?
Evidence: Thomas Kemper refers to BrandName = 'Thomas Kemper';  latitude the beer is consumed the most refers to MAX(COUNT(Latitude));
SQL: SELECT T3.Latitude FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID INNER JOIN geolocation AS T3 ON T1.LocationID = T3.LocationID WHERE T2.BrandName = 'Thomas Kemper' GROUP BY T3.Latitude ORDER BY COUNT(T1.BrandID) DESC LIMIT 1
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What star rating is the most common for beers containing corn syrup?
Evidence: most common refers to MAX(COUNT(StarRating)); containing corn syrup refers to CornSyrup = 'TRUE';
SQL: SELECT T2.StarRating FROM rootbeerbrand AS T1 INNER JOIN rootbeerreview AS T2 ON T1.BrandID = T2.BrandID WHERE T1.CornSyrup = 'TRUE' GROUP BY T2.StarRating ORDER BY COUNT(T2.StarRating) DESC LIMIT 1
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What is the precise location of zip code 95819?
Evidence: precise location = Latitude, Longitude;
SQL: SELECT T2.Latitude, T2.Longitude FROM location AS T1 INNER JOIN geolocation AS T2 ON T1.LocationID = T2.LocationID WHERE T1.ZipCode = 95819
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What brands of beers are manufactured at coordinates 38,566,129, -121,426,432?
Evidence: coordinates 38,566,129, -121,426,432 refers to Latitude = 38.566129 AND Longitude = -121.426432;
SQL: SELECT DISTINCT T2.BrandName FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID INNER JOIN geolocation AS T3 ON T1.LocationID = T3.LocationID WHERE T3.Latitude = '38.566129' AND T3.Longitude = '-121.426432'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What is the average unit profit for wholesalers of canned beers?
Evidence: average unit profit = DIVIDE(SUM(SUBTRACT(CurrentRetailPrice, WholesaleCost)), COUNT(ContainerType = 'Can')); canned beers refers to ContainerType = 'Can';
SQL: SELECT AVG(T2.CurrentRetailPrice - T2.WholesaleCost) FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID WHERE T1.ContainerType = 'Can'
Database: beer_factory
Tables: customers, geolocation, location, rootbeerbrand, rootbeer, rootbeerreview, transaction
Columns (table index, column name): -1, *, 0, CustomerID, 0, First, 0, Last, 0, StreetAddress, 0, City, 0, State, 0, ZipCode, 0, Email, 0, PhoneNumber, 0, FirstPurchaseDate, 0, SubscribedToEmailList, 0, Gender, 1, LocationID, 1, Latitude, 1, Longitude, 2, LocationID, 2, LocationName, 2, StreetAddress, 2, City, 2, State, 2, ZipCode, 3, BrandID, 3, BrandName, 3, FirstBrewedYear, 3, BreweryName, 3, City, 3, State, 3, Country, 3, Description, 3, CaneSugar, 3, CornSyrup, 3, Honey, 3, ArtificialSweetener, 3, Caffeinated, 3, Alcoholic, 3, AvailableInCans, 3, AvailableInBottles, 3, AvailableInKegs, 3, Website, 3, FacebookPage, 3, Twitter, 3, WholesaleCost, 3, CurrentRetailPrice, 4, RootBeerID, 4, BrandID, 4, ContainerType, 4, LocationID, 4, PurchaseDate, 5, CustomerID, 5, BrandID, 5, StarRating, 5, ReviewDate, 5, Review, 6, TransactionID, 6, CreditCardNumber, 6, CustomerID, 6, TransactionDate, 6, CreditCardType, 6, LocationID, 6, RootBeerID, 6, PurchasePrice
Question: What percentage of customers who paid with a Discover Credit Card gave a 3-star rating?
Evidence: percentage = MULTIPLY(DIVIDE(COUNT(CustomerID WHERE StarRating = 3), COUNT(CustomerID) WHERE CreditCardType = 'Discover'), 100); Discover Credit Card refers to CreditCardType = 'Discover'; 3-star rating refers to StarRating = 3;
SQL: SELECT CAST(COUNT(CASE WHEN T1.StarRating = 3 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.CustomerID) FROM rootbeerreview AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.CreditCardType = 'Discover'