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-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- If a pair of genes is positively correlated, what is the possibility of it being composed of two genes both with over 10 chromosomes?
| SELECT CAST(SUM(IIF(T1.Chromosome > 10 AND T3.Chromosome > 10, 1, 0)) AS REAL) * 100 / COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 INNER JOIN Genes AS T3 ON T3.GeneID = T2.GeneID2 WHERE T2.Expression_Corr > 0; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- For the pairs of genes both from the class ATPases, what is the average expression correlation score?
| SELECT AVG(T2.Expression_Corr) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Class = 'ATPases'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- Lists all genes by identifier number located in the cytoplasm and whose function is metabolism.
| SELECT DISTINCT GeneID FROM Genes WHERE Localization = 'cytoplasm' AND Function = 'METABOLISM'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- How many different genes do we have if we add those located in the plasma and in the nucleus?
| SELECT COUNT(GeneID) FROM Classification WHERE Localization IN ('plasma', 'nucleus'); |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- What kind of expression correlation occurs in physical type interacting gene pairs and what percentage of these are negatively correlated?
| SELECT Expression_Corr FROM Interactions WHERE Type = 'Physical' UNION ALL SELECT CAST(SUM(Expression_Corr < 0) AS REAL) * 100 / COUNT(*) FROM Interactions WHERE Type = 'Physical'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- What percentage of genes located in the cytoskeleton are of unknown class? And of these, how many are not conditional phenotypes?
| SELECT SUM(Localization = 'cytoskeleton' AND Phenotype = 'Conditional phenotypes') , CAST(SUM(Localization = 'cytoskeleton') AS REAL) * 100 / COUNT(GeneID) FROM Genes; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- What type of interactions occurs in genes whose function is cellular transport and transport medicine and are classified as non-essential?
| SELECT T2.Type FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Function = 'TRANSCRIPTION' AND T1.Essential = 'Non-Essential'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- List all genes whose interaction is with genes located in the nucleus in which it is positively correlated.
| SELECT T1.GeneID FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Expression_Corr > 0 AND T1.Localization = 'nucleus'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- Taking all the essential genes of the transcription factors class located in the nucleus as a reference, how many of them carry out a genetic-type interaction with another gene? List them.
| SELECT T2.GeneID1 FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Localization = 'nucleus' AND T1.Class = 'Transcription factors' AND T1.Essential = 'Essential' AND T2.Expression_Corr != 0; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- Of all the nonessential genes that are not of the motorprotein class and whose phenotype is cell cycle defects, how many do not have a physical type of interaction?
| SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Type != 'Physical' AND T1.Phenotype = 'Cell cycle defects' AND T1.Class != 'Motorproteins' AND T1.Essential = 'Non-Essential'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- Of the genes whose phenotype and motif are nucleic acid metabolism defects, PS00107, what percentage perform positive interaction with another gene?
| SELECT CAST(SUM(IIF(T2.Expression_Corr > 0, 1, 0)) AS REAL) * 100 / COUNT(T2.GeneID1) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Phenotype = 'Nucleic acid metabolism defects' AND T1.Motif = 'PS00107'; |
-- Database schema
| Classification : GeneID [ TEXT ] primary_key , Localization [ TEXT ] | Genes : GeneID [ TEXT ] Genes.GeneID = Classification.GeneID , Essential [ TEXT ] , Class [ TEXT ] , Complex [ TEXT ] , Phenotype [ TEXT ] , Motif [ TEXT ] , Chromosome [ INTEGER ] , Function [ TEXT ] , Localization [ TEXT ] | Interactions : GeneID1 [ TEXT ] Interactions.GeneID1 = Classification.GeneID , GeneID2 [ TEXT ] Interactions.GeneID2 = Classification.GeneID , Type [ TEXT ] , Expression_Corr [ REAL ] |
-- -- Which negatively correlated, genetically interacting genes are non-essential? What percentage do they represent with respect to those that are essential?
| SELECT CAST(COUNT(T1.GeneID) AS REAL) * 100 / ( SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Expression_Corr < 0 ) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Expression_Corr < 0 AND T1.Essential = 'Non-Essential'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many apps were last updated in January of 2018? Please write one translated review with positive sentiment for each app, if there's any.
| SELECT DISTINCT Translated_Review FROM user_reviews WHERE App IN ( SELECT App FROM playstore WHERE `Last Updated` BETWEEN 'January 1, 2018' AND 'January 31, 2018' ) AND Sentiment = 'Positive'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many users mildly likes the 7 Minute Workout app and when was it last updated?
| SELECT COUNT(T2.Sentiment_Polarity), T1."Last Updated" FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = '7 Minute Workout' AND T2.Sentiment_Polarity BETWEEN 0 AND 0.5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many users holds neutral attitude towards the HTC Weather app? Indicate the app's rating on the Google Play Store.
| SELECT COUNT(T1.Rating), T1.Rating FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'HTC Weather' AND T2.Sentiment = 'Neutral'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the name and category of the app with the highest amount of -1 sentiment polarity score?
| SELECT DISTINCT T1.App, T1.Category FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment_Polarity = '-1.0'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average sentiment polarity score of the Cooking Fever app? Indicate the age group that the app is targeted at.
| SELECT AVG(T2.Sentiment_Polarity), T1."Content Rating" FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Cooking Fever'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the lowest sentiment polarity score of the Basketball Stars app for people who dislikes the app pretty much and how many downloads does it have?
| SELECT MIN(T2.Sentiment_Polarity), T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Basketball Stars'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- For the Akinator app, how many reviews have sentiment subjectivity of no more than 0.5 and what is its current version?
| SELECT COUNT(T2.Sentiment_Subjectivity), T1."Current Ver" FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Akinator' AND T2.Sentiment_Subjectivity < 0.5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many apps have rating of 5?
| SELECT COUNT(App) FROM playstore WHERE Rating = 5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What are the top 5 installed free apps?
| SELECT App FROM playstore WHERE Price = 0 ORDER BY CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER) DESC LIMIT 5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Name the top 10 most reviewed apps.
| SELECT DISTINCT App FROM playstore ORDER BY Reviews DESC LIMIT 10; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many of the users hold neutral attitude on "10 Best Foods for You" app and what category is this app?
| SELECT COUNT(T2.App), T1.Category FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = '10 Best Foods for You' AND T2.Sentiment = 'Neutral'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What are the apps that users pretty like this app and how many installs amount of these apps?
| SELECT DISTINCT T1.App, T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment_Polarity > 0; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List apps whose rating is 3.9 and state the translated review of each app.
| SELECT T1.App, T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Rating = 3.9; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many apps that are only compatible with Android ver 8.0 and above? List down the users' sentiment of these apps.
| SELECT DISTINCT Sentiment FROM user_reviews WHERE App IN ( SELECT App FROM playstore WHERE `Android Ver` = '8.0 and up' ); |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which apps have multiple genres and what is the total sentiment subjectivity of these apps?
| SELECT SUM(T2.Sentiment_Subjectivity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres > 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which apps have not been updated since year 2015 and what kind of sentiment users hold on it?
| SELECT DISTINCT App, Sentiment FROM user_reviews WHERE App IN ( SELECT App FROM playstore WHERE CAST(SUBSTR('Last Updated', -4, 4) AS INTEGER) < 2015 ); |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the total installs of apps with content rating of adults only 18+ and what are the translated reviews of it?
| SELECT SUM(T1.Installs), T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1."Content Rating" = 'Adults only 18+'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which of the app is the best selling app and what is the sentiments polarity of it?
| SELECT T1.App, T2.Sentiment_Polarity FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App ORDER BY T1.Price * CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER) DESC LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average rating of comic category apps? How many users hold positive attitude towards this app?
| SELECT AVG(T1.Rating) , COUNT(CASE WHEN T2.Sentiment = 'Positive' THEN 1 ELSE NULL END) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Category = 'COMICS'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the rating for "Draw A Stickman"?
| SELECT Rating FROM playstore WHERE APP = 'Draw A Stickman'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many of the reviews for the app "Brit + Co" have a comment?
| SELECT COUNT(App) FROM user_reviews WHERE App = 'Brit + Co' AND Translated_Review IS NOT NULL; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List the top 5 shopping apps with the most reviews.
| SELECT DISTINCT App FROM playstore WHERE Genres = 'Shopping' GROUP BY App ORDER BY COUNT(App) DESC LIMIT 5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many neutral reviews does the app "Dino War: Rise of Beasts" have?
| SELECT COUNT(App) FROM user_reviews WHERE App = 'Dino War: Rise of Beasts' AND Sentiment = 'Neutral'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What are the apps with only 5,000+ installs?
| SELECT DISTINCT App FROM playstore WHERE Installs = '5,000+'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List all the negative comments on the "Dog Run - Pet Dog Simulator" app.
| SELECT Translated_Review FROM user_reviews WHERE App = 'Dog Run - Pet Dog Simulator' AND Sentiment = 'Negative'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which free app has the most Negative comments?
| SELECT T1.App FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Type = 'Free' AND T2.Sentiment = 'Negative' GROUP BY T1.App ORDER BY COUNT(T2.Sentiment) DESC LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How many negative comments are there in all the apps with 100,000,000+ installs?
| 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 schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What are the content ratings for the apps that have "gr8" in their comments?
| SELECT DISTINCT T1.`Content Rating` FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Translated_Review LIKE '%gr8%'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the total Sentiment polarity score of the most expensive app?
| SELECT SUM(T2.Sentiment_Polarity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Price = ( SELECT MAX(Price) FROM playstore ); |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the rating for "Garden Coloring Book"? List all of its reviews.
| SELECT T1.Rating, T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Garden Coloring Book'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which Photography app has the highest total Sentiment subjectivity score?
| SELECT T1.App FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres = 'Photography' GROUP BY T1.App ORDER BY SUM(T2.Sentiment_Subjectivity) DESC LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List all the comments on the lowest rated Mature 17+ app.
| SELECT T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1."Content Rating" = 'Mature 17+' ORDER BY T1.Rating LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the number of installments of the app with the highest total Sentiment polarity score?
| SELECT T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App GROUP BY T1.App ORDER BY SUM(T2.Sentiment_Polarity) DESC LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the number of neutral comments from all the weather apps?
| SELECT COUNT(T2.Sentiment) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres = 'Weather' AND T2.Sentiment = 'Neutral'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which 1,000,000,000+ intalls apps has the most no comment reviews?
| SELECT T1.App FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Installs = '1,000,000+' AND T2.Translated_Review = 'nan' GROUP BY T1.App ORDER BY COUNT(T2.Translated_Review) DESC LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the rating and the total Sentiment subjectivity score of "Onefootball - Soccer Scores"?
| SELECT T1.Rating, SUM(T2.Sentiment_Subjectivity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Onefootball - Soccer Scores'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What percentage of no comment reviews are from "Teen" content rating apps?
| SELECT CAST(COUNT(CASE WHEN T1.`Content Rating` = 'Teen' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.App) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Translated_Review = 'nan'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which apps have 5 rating? List out then application name.
| SELECT DISTINCT App FROM playstore WHERE Rating = 5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which apps have been reviewed more than 75 000 000 times and the content is suitable for teenagers?
| SELECT DISTINCT App FROM playstore WHERE Reviews > 75000000 AND `Content Rating` = 'Teen'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List out genre that have downloads more than 1000000000.
| SELECT Genres FROM playstore WHERE Installs = '1,000,000,000+' GROUP BY Genres; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average price for a dating application?
| SELECT AVG(Price) FROM playstore WHERE Genres = 'Dating'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average download for entertainment apps with size no more than 1.0 M?
| SELECT AVG(CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER)) FROM playstore WHERE Category = 'ENTERTAINMENT' AND Size < '1.0M'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average review number for application with 5 rating?
| SELECT AVG(Reviews) FROM playstore WHERE Rating = 5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List out the top 3 genre for application with a sentiment review greater than 0.5.
| SELECT Genres FROM playstore WHERE App IN ( SELECT App FROM user_reviews WHERE Sentiment = 'Positive' AND Sentiment_Polarity > 0.5 ORDER BY Sentiment_Polarity DESC LIMIT 3 ); |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the percentage of application with 4.7 rating having more positives sentiment than negative sentiment?
| SELECT CAST(COUNT(CASE WHEN ( SELECT COUNT(CASE WHEN Sentiment = 'Positive' THEN 1 ELSE NULL END) - COUNT(CASE WHEN Sentiment = 'Negative' THEN 1 ELSE NULL END) FROM user_reviews GROUP BY App ) > 0 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T2.Sentiment) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Rating = 4.7; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List down app that does not have negative sentiment and give their average rating?
| SELECT T1.App, AVG(T2.Sentiment_Polarity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment != 'Negative' GROUP BY T1.App; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List down application that have not been updated since 2015. What is the percentage of this application having more negative sentiment than positive sentiment?
| SELECT CAST((( SELECT COUNT(*) Po FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE SUBSTR(T1."Last Updated", -4, 4) > '2015' AND T2.Sentiment = 'Positive' ) - ( SELECT COUNT(*) Ne FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE SUBSTR(T1."Last Updated", -4, 4) > '2015' AND T2.Sentiment = 'Negative' )) AS REAL) * 100 / ( SELECT COUNT(*) NUM FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE SUBSTR(T1."Last Updated", -4, 4) > '2015' ); |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the percentage for free application with a rating 4.5 and above have not been updated since 2018?
| SELECT CAST(SUM(CASE WHEN SUBSTR('Last Updated', -4) > '2018' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(App) PER FROM playstore WHERE Type = 'Free' AND Rating >= 4.5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What genre does Honkai Impact 3rd belong to?
| SELECT DISTINCT Genres FROM playstore WHERE App = 'Honkai Impact 3rd'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List down the rating for the App Learn C++.
| SELECT DISTINCT Rating FROM playstore WHERE App = 'Learn C++'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average price of games belonging in the arcade genre which has a content rating of Everyone 10+?
| SELECT AVG(Price) FROM playstore WHERE 'Content Rating' = 'Everyone 10+' AND Genres = 'Arcade'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How much is the size of Browser 4G and how many users have a pretty positive favorability on it?
| SELECT T1.Size, COUNT(T1.App) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Browser 4G' AND T2.Sentiment_Polarity >= 0.5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Name the Apps with a sentiment objectivity of 0.3 and include their number of installs.
| SELECT DISTINCT T1.App, T1.Installs FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment_Polarity = 0.3; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- How much is the average sentiment polarity score of Golf GPS Rangefinder: Golf Pad and what is it's rating in the Google Play Store?
| SELECT AVG(T2.Sentiment_Polarity), T1.Rating FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Golf GPS Rangefinder: Golf Pad'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List the top 5 lowest rated puzzle games and count the number of negative sentiments the games received.
| SELECT T1.App, COUNT(T1.App) COUNTNUMBER FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment = 'Negative' GROUP BY T1.App ORDER BY T1.Rating LIMIT 5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the percentage ratio between positive sentiments and negative sentiments that are in Fate/Grand Order? Also indicate the current version.
| SELECT CAST(SUM(CASE WHEN T2.Sentiment = 'Positive' THEN 1 ELSE 0 END) AS REAL) * 100 / SUM(CASE WHEN T2.Sentiment = 'Negative' THEN 1 ELSE 0 END), T1.`Current Ver` FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Fate/Grand Order (English)' AND T1.`Current Ver` = '1.18.0'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Indicate the number of installs and include the percentage of positive sentiments of FREEDOME VPN Unlimited anonymous Wifi Security.
| SELECT T1.Installs , CAST(SUM(CASE WHEN T2.Sentiment = 'Positive' THEN 1 ELSE 0 END) * 100 / SUM(CASE WHEN T2.Sentiment IS NOT NULL THEN 1.0 ELSE 0 END) AS REAL) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'FREEDOME VPN Unlimited anonymous Wifi Security'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- For the Honkai Impact 3rd App, what is the highest sentiment polarity score and what genre does it belong to?
| SELECT MAX(T2.Sentiment_Polarity), T1.Genres FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Honkai Impact 3rd' AND T2.Sentiment_Polarity > 0.5 GROUP BY T1.Genres; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the rating of Dragon Ball Legends and how many users dislike this App?
| SELECT T1.Rating, COUNT(T2.Sentiment_Polarity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'Dragon Ball Legends' AND CAST(Sentiment_Polarity AS INTEGER) < -0.5; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Which education App has the worst rating and state the translated review if available.
| SELECT T1.App, T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Category = 'EDUCATION' GROUP BY T1.App, T2.Translated_Review ORDER BY T1.Rating ASC LIMIT 1; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- List all free sports Apps and their translated review.
| SELECT T1.App, T2.Translated_Review FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Type = 'Free' AND T1.Category = 'SPORTS'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- Among the role playing game genre, how many are targeted to teens and what is their average sentiment polarity score?
| SELECT COUNT(T1.App), AVG(T2.Sentiment_Polarity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1."Content Rating" = 'Teen' AND T1.Genres = 'Role Playing'; |
-- Database schema
| playstore : App [ TEXT ] , Category [ TEXT ] , Rating [ REAL ] , Reviews [ INTEGER ] , Size [ TEXT ] , Installs [ TEXT ] , Type [ TEXT ] , Price [ TEXT ] , Content Rating [ TEXT ] , Genres [ TEXT ] | user_reviews : App [ TEXT ] user_reviews.App = playstore.App , Translated_Review [ TEXT ] , Sentiment [ TEXT ] , Sentiment_Polarity [ TEXT ] , Sentiment_Subjectivity [ TEXT ] |
-- -- What is the average rating of Apps falling under the racing genre and what is the percentage ratio of positive sentiment reviews?
| SELECT AVG(T1.Rating), CAST(COUNT(CASE WHEN T2.Sentiment = 'Positive' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T2.Sentiment) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres = 'Racing'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Which region has the most number of sales team?
| SELECT Region FROM `Sales Team` GROUP BY Region ORDER BY COUNT(DISTINCT `Sales Team`) DESC LIMIT 1; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List all the customers with name containing the word 'Group'.
| SELECT T FROM ( SELECT IIF(`Customer Names` LIKE '%Group%', `Customer Names`, NULL) AS T FROM Customers ) WHERE T IS NOT NULL; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- What is the average median income for all City type of stores?
| SELECT AVG(`Median Income`) FROM `Store Locations` WHERE Type = 'City'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Name the sales team and the region of order number 'SO - 000137'.
| SELECT T2.`Sales Team`, T2.Region FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T1.OrderNumber = 'SO - 000137'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List all the order numbers along with its product name for each order under the sales team of 'Douglas Tucker'.
| SELECT DISTINCT T1.ProductID, T1.`Product Name` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Sales Team` AS T3 ON T3.SalesTeamID = T2._SalesTeamID WHERE T3.`Sales Team` = 'Douglas Tucker'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Among orders in 2020, name the customers who had the greatest discount applied for 'Cocktail Glasses'
| SELECT DISTINCT T1.`Customer Names` FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID INNER JOIN Products AS T3 ON T3.ProductID = T2._ProductID WHERE T3.`Product Name` = 'Cocktail Glasses' AND SUBSTR(T2.OrderDate, -2) = '20' AND T2.`Discount Applied` = ( SELECT T2.`Discount Applied` FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID INNER JOIN Products AS T3 ON T3.ProductID = T2._ProductID WHERE T3.`Product Name` = 'Cocktail Glasses' AND T2.OrderDate LIKE '%/%/20' ORDER BY T2.`Discount Applied` DESC LIMIT 1 ); |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List all the order numbers for In-Store sales and find the city where the store is located.
| SELECT DISTINCT T1.OrderNumber, T2.`City Name` FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T1.`Sales Channel` = 'In-Store'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Name the most expensive ordered? Who, when was it ordered?
| SELECT T2.OrderNumber, T1.`Customer Names`, T2.OrderDate FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID INNER JOIN Products AS T3 ON T3.ProductID = T2._ProductID ORDER BY T2.`Unit Cost` DESC LIMIT 1; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List all the numbers ordered by 'Rochester Ltd' in 2018.
| SELECT DISTINCT T FROM ( SELECT CASE WHEN T1.OrderDate LIKE '%/%/18' AND T2.`Customer Names` = 'Rochester Ltd' THEN T1.OrderNumber ELSE NULL END AS T FROM `Sales Orders` T1 INNER JOIN Customers T2 ON T2.CustomerID = T1._CustomerID ) WHERE T IS NOT NULL; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Provide all the orders from WARE-NMK1003. Name the product and sales team for each of these order.
| SELECT DISTINCT T1.`Product Name`, T3.`Sales Team` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Sales Team` AS T3 ON T3.SalesTeamID = T2._SalesTeamID WHERE T2.WarehouseCode = 'WARE-NMK1003'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List the name of all customers who had made orders online.
| SELECT T FROM ( SELECT CASE WHEN T2.`Sales Channel` = 'Online' THEN T1.`Customer Names` ELSE NULL END AS T FROM Customers T1 INNER JOIN `Sales Orders` T2 ON T2._CustomerID = T1.CustomerID ) WHERE T IS NOT NULL; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Calculate the average net profit for bakeware product.
| SELECT AVG(REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '')) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE T2.`Product Name` = 'Bakeware'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Name the sales team name who had orders with the greatest net profit in 2020.
| SELECT T2.`Sales Team` FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T1.OrderDate LIKE '%/%/20' GROUP BY T2.`Sales Team` ORDER BY SUM(REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '')) DESC LIMIT 1; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Sate the order number and calculate the net profit for each order under Joshua Bennett.
| SELECT T1.OrderNumber , REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '') FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.`Sales Team` = 'Joshua Bennett'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Among the sales order shipped in July 2018, calculate the percentage of orders for home fragrances.
| SELECT SUM(CASE WHEN T2.`Product Name` = 'Home Fragrances' THEN 1 ELSE 0 END) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE T1.ShipDate LIKE '7/%/18'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List down the customer IDs and names that start with alphabet "W".
| SELECT DISTINCT CustomerID, `Customer Names` FROM Customers WHERE `Customer Names` LIKE 'W%' ORDER BY `Customer Names` DESC; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List down the product IDs and names that include the word "Outdoor".
| SELECT ProductID, T FROM ( SELECT ProductID , CASE WHEN `Product Name` LIKE '%Outdoor%' THEN `Product Name` ELSE NULL END AS T FROM Products ) WHERE T IS NOT NULL ORDER BY T DESC; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Among the sales with 40% discount via in-store channel, how many products were shipped from warehouse code of WARE-NMK1003?
| SELECT COUNT(DISTINCT T) FROM ( SELECT CASE WHEN `Sales Channel` = 'In-Store' AND WarehouseCode = 'WARE-NMK1003' AND `Discount Applied` = '0.4' THEN OrderNumber ELSE NULL END AS T FROM `Sales Orders` ) WHERE T IS NOT NULL; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Mention the most populated city and median income of the store in Florida state.
| SELECT `City Name`, `Median Income` FROM `Store Locations` WHERE State = 'Florida' ORDER BY Population DESC LIMIT 1; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Describe the ID, city and region of the stores which are in Allen country.
| SELECT DISTINCT T2.StoreID, T2.`City Name`, T1.Region FROM Regions AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StateCode = T1.StateCode WHERE T2.County = 'Allen County'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- List the ID, city, state and region for the store type which is fewer between borough and CDP.
| SELECT DISTINCT T2.StoreID, T2.`City Name`, T1.State, T2.Type FROM Regions AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StateCode = T1.StateCode WHERE T2.Type = 'Borough' OR T2.Type = 'CDP'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Write down the region and name of the sale team ID of 18 and compare their orders between in-store and online.
| SELECT T2.Region, T2.`Sales Team` FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.SalesTeamID = 18 AND T1.`Sales Channel` = 'In-Store' OR T1.`Sales Channel` = 'Online'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Calculate the percentage of order via in-store channel of customer "Medline".
| SELECT CAST(SUM(CASE WHEN T1.`Sales Channel` = 'In-Store' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1._CustomerID) FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID WHERE T2.`Customer Names` = 'Medline '; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Describe the customer names and lasting delivery periods for the product of "Bedroom Furniture" by wholesale channel in 2019.
| SELECT T1.`Customer Names`, T2.DeliveryDate FROM Customers AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._CustomerID = T1.CustomerID INNER JOIN Products AS T3 ON T3.ProductID = T2._ProductID WHERE T2.`Sales Channel` = 'Wholesale' AND T3.`Product Name` = 'Bedroom Furniture' AND T2.OrderDate LIKE '%/%/19'; |
-- Database schema
| Customers : CustomerID [ INTEGER ] primary_key , Customer Names [ TEXT ] | Products : ProductID [ INTEGER ] primary_key , Product Name [ TEXT ] | Regions : StateCode [ TEXT ] primary_key , State [ TEXT ] , Region [ TEXT ] | Sales Team : SalesTeamID [ INTEGER ] primary_key , Sales Team [ TEXT ] , Region [ TEXT ] | Store Locations : StoreID [ INTEGER ] primary_key , City Name [ TEXT ] , County [ TEXT ] , StateCode [ TEXT ] Store Locations.StateCode = Regions.StateCode , State [ TEXT ] , Type [ TEXT ] , Latitude [ REAL ] , Longitude [ REAL ] , AreaCode [ INTEGER ] , Population [ INTEGER ] , Household Income [ INTEGER ] , Median Income [ INTEGER ] , Land Area [ INTEGER ] , Water Area [ INTEGER ] , Time Zone [ TEXT ] | Sales Orders : OrderNumber [ TEXT ] primary_key , Sales Channel [ TEXT ] , WarehouseCode [ TEXT ] , ProcuredDate [ TEXT ] , OrderDate [ TEXT ] , ShipDate [ TEXT ] , DeliveryDate [ TEXT ] , CurrencyCode [ TEXT ] , _SalesTeamID [ INTEGER ] Sales Orders._SalesTeamID = Sales Team.SalesTeamID , _CustomerID [ INTEGER ] Sales Orders._CustomerID = Customers.CustomerID , _StoreID [ INTEGER ] Sales Orders._StoreID = Store Locations.StoreID , _ProductID [ INTEGER ] Sales Orders._ProductID = Products.ProductID , Order Quantity [ INTEGER ] , Discount Applied [ REAL ] , Unit Price [ TEXT ] , Unit Cost [ TEXT ] |
-- -- Describe the customer names and product names which had over 3800 USD in net profit.
| SELECT DISTINCT `Customer Names`, `Product Name` FROM ( SELECT T1.`Customer Names`, T3.`Product Name` , REPLACE(T2.`Unit Price`, ',', '') - REPLACE(T2.`Unit Cost`, ',', '') AS T FROM Customers T1 INNER JOIN `Sales Orders` T2 ON T2._CustomerID = T1.CustomerID INNER JOIN Products T3 ON T3.ProductID = T2._ProductID ) WHERE T > 3800; |
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