1sf/bird-sql-train-with-schema huggingface dataset:
Database: shooting
Tables: incidents, officers, subjects
Columns (table index, column name): -1, *, 0, case_number, 0, date, 0, location, 0, subject_statuses, 0, subject_weapon, 0, subjects, 0, subject_count, 0, officers, 1, case_number, 1, race, 1, gender, 1, last_name, 1, first_name, 1, full_name, 2, case_number, 2, race, 2, gender, 2, last_name, 2, first_name, 2, full_name
Question: Which near-death incident did a policeman by the name of Ruben Fredirick look into? What is the victim in this incident's race and gender?
Evidence: near-death refers to subject_statuses = 'Deceased Injured'; incident refers to case_number; Ruben Fredirick refers to full_name = 'Ruben Fredirick'
SQL: SELECT T1.case_number, T3.race, T3.gender FROM incidents AS T1 INNER JOIN officers AS T2 ON T1.case_number = T2.case_number INNER JOIN subjects AS T3 ON T1.case_number = T3.case_number WHERE T2.first_name = 'Fredirick' AND T2.last_name = 'Ruben'
Database: shooting
Tables: incidents, officers, subjects
Columns (table index, column name): -1, *, 0, case_number, 0, date, 0, location, 0, subject_statuses, 0, subject_weapon, 0, subjects, 0, subject_count, 0, officers, 1, case_number, 1, race, 1, gender, 1, last_name, 1, first_name, 1, full_name, 2, case_number, 2, race, 2, gender, 2, last_name, 2, first_name, 2, full_name
Question: What proportion of male police officers looked into events where people were injured?
Evidence: male refers to gender = 'M'; people were injured refers to subject_statuses = 'Injured'; proportion = divide(count(case_number where gender = 'M'), count(case_number)) where subject_statuses = 'Injured' * 100%
SQL: SELECT CAST(SUM(T2.gender = 'M') AS REAL) * 100 / COUNT(T1.case_number) FROM incidents T1 INNER JOIN officers T2 ON T1.case_number = T2.case_number WHERE T1.subject_statuses = 'Injured'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: For the genes that are located in the plasma membrane, please list their number of chromosomes.
SQL: SELECT T1.Chromosome FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'plasma membrane'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: How many non-essential genes are located in the nucleus?
SQL: SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'nucleus' AND T1.Essential = 'Non-Essential'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Among the genes with nucleic acid metabolism defects, how many of them can be found in the vacuole?
SQL: SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID WHERE T2.Localization = 'vacuole' AND T1.Phenotype = 'Nucleic acid metabolism defects'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Please list the location of the genes that have the most chromosomes.
SQL: SELECT T2.Localization FROM Genes AS T1 INNER JOIN Classification AS T2 ON T1.GeneID = T2.GeneID ORDER BY T1.Chromosome DESC LIMIT 1
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Among the pairs of genes that are both located in the nucleus, what is the highest expression correlation score?
SQL: SELECT T2.Expression_Corr 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 T1.Localization = 'nucleus' AND T3.Localization = 'nucleus' ORDER BY T2.Expression_Corr DESC LIMIT 1
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: What are the functions of the pair of genes that have the lowest expression correlation score?a
SQL: SELECT T1.Function FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 ORDER BY T2.Expression_Corr ASC LIMIT 1
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Among the pairs of genes that are not from the class of motorproteins, how many of them are negatively correlated?
Evidence: If Expression_Corr < 0, it means the negatively correlated
SQL: SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Expression_Corr < 0 AND T1.Class = 'Motorproteins'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: For the pairs of genes with one having 8 chromosomes and the other having 6 chromosomes, what is the highest expression correlation score?
SQL: SELECT T2.Expression_Corr FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Chromosome = 6 OR T1.Chromosome = 8 ORDER BY T2.Expression_Corr DESC LIMIT 1
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Please list the motif of the genes that are located in the cytoplasm and have 7 chromosomes.
SQL: SELECT T2.GeneID1, T2.GeneID2 FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Localization = 'cytoplasm' AND T1.Chromosome = 7
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: For the non-essential genes whose functions are transcription, how many of them are not located in the cytoplasm?
SQL: SELECT COUNT(T1.GeneID) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Localization != 'cytoplasm' AND T1.Function = 'TRANSCRIPTION' AND T1.Essential = 'NON-Essential'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: How many pairs of positively correlated genes are both non-essential?
Evidence: If Expression_Corr > 0, it means the expression correlation is positive
SQL: SELECT COUNT(T2.GeneID2) 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: If a pair of genes is positively correlated, what is the possibility of it being composed of two genes both with over 10 chromosomes?
Evidence: Positively correlated means Expression_Corr > 0; Possibility = count(the pairs of genes with both chromosomes over 20) / count(pairs of genes that are positively correlated)
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: For the pairs of genes both from the class ATPases, what is the average expression correlation score?
SQL: SELECT AVG(T2.Expression_Corr) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T1.Class = 'ATPases'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Lists all genes by identifier number located in the cytoplasm and whose function is metabolism.
SQL: SELECT DISTINCT GeneID FROM Genes WHERE Localization = 'cytoplasm' AND Function = 'METABOLISM'
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: How many different genes do we have if we add those located in the plasma and in the nucleus?
SQL: SELECT COUNT(GeneID) FROM Classification WHERE Localization IN ('plasma', 'nucleus')
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: What kind of expression correlation occurs in physical type interacting gene pairs and what percentage of these are negatively correlated?
Evidence: If the Expression_Corr value is negative then it's negatively correlated. Percentage of Negative Correlation = count(negative Expression_Corr physical type) / count(Expression_Corr physical type) * 100%
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: What percentage of genes located in the cytoskeleton are of unknown class? And of these, how many are not conditional phenotypes?
Evidence: Percentage = count(genes located in the cytoskeleton unknown class) / count(genes located in the cytoskeleton) * 100%
SQL: SELECT SUM(Localization = 'cytoskeleton' AND Phenotype = 'Conditional phenotypes') , CAST(SUM(Localization = 'cytoskeleton') AS REAL) * 100 / COUNT(GeneID) FROM Genes;
Database: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: What type of interactions occurs in genes whose function is cellular transport and transport medicine and are classified as non-essential?
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: List all genes whose interaction is with genes located in the nucleus in which it is positively correlated.
Evidence: If the Expression_Corr value is positive then it's positively correlated
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: 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.
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: 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?
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Of the genes whose phenotype and motif are nucleic acid metabolism defects, PS00107, what percentage perform positive interaction with another gene?
Evidence: Percentage of no interaction = [count(nucleic acid metabolism, PS00107, no interaction) / count(nucleic acid metabolism, PS00107) * 100%
SQL: 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: genes
Tables: Classification, Genes, Interactions
Columns (table index, column name): -1, *, 0, GeneID, 0, Localization, 1, GeneID, 1, Essential, 1, Class, 1, Complex, 1, Phenotype, 1, Motif, 1, Chromosome, 1, Function, 1, Localization, 2, GeneID1, 2, GeneID2, 2, Type, 2, Expression_Corr
Question: Which negatively correlated, genetically interacting genes are non-essential? What percentage do they represent with respect to those that are essential?
Evidence: If the Expression_Corr value is negative then it's negatively correlated; Percentage of Essensity = [count(negatively correlated, genetical interaction, non-essential) / count(negatively correlated, genetical interaction, non-essential+negatively correlated, genetical interaction, essential)] * 100%
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: 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.
Evidence: updated in January of 2018 refers to Last Updated BETWEEN 'January 1, 2018' and 'January 31, 2018';
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: How many users mildly likes the 7 Minute Workout app and when was it last updated?
Evidence: mildly likes the app refers to Sentiment_Polarity> = 0 and Sentiment_Polarity<0.5;
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: How many users holds neutral attitude towards the HTC Weather app? Indicate the app's rating on the Google Play Store.
Evidence: user holds neutral attitude refers to Sentiment = 'Neutral';
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: What is the name and category of the app with the highest amount of -1 sentiment polarity score?
Evidence: highest amount of -1 sentiment polarity score refers to MAX(Count(Sentiment_Polarity = 1.0))
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: What is the average sentiment polarity score of the Cooking Fever app? Indicate the age group that the app is targeted at.
Evidence: average sentiment polarity score = AVG(Sentiment_Polarity); age group the app is target at refers to Content Rating;
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: 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?
Evidence: lowest sentiment polarity score refers to MIN(Sentiment_Polarity); user dislike the app pretty much refers to Sentiment_Polarity<-0.5; number of downloads it has refers to installs;
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: For the Akinator app, how many reviews have sentiment subjectivity of no more than 0.5 and what is its current version?
Evidence: Sentiment_Subjectivity<0.5; current version refers to Current Ver;
SQL: 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: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: How many apps have rating of 5?
Evidence: FALSE;
SQL: SELECT COUNT(App) FROM playstore WHERE Rating = 5
Database: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: What are the top 5 installed free apps?
Evidence: free app refers to price = 0; most installed app refers to MAX(Installs);
SQL: SELECT App FROM playstore WHERE Price = 0 ORDER BY CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER) DESC LIMIT 5
Database: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: Name the top 10 most reviewed apps.
Evidence: most reviewed app refers to MAX(Reviews);
SQL: SELECT DISTINCT App FROM playstore ORDER BY Reviews DESC LIMIT 10
Database: app_store
Tables: playstore, user_reviews
Columns (table index, column name): -1, *, 0, App, 0, Category, 0, Rating, 0, Reviews, 0, Size, 0, Installs, 0, Type, 0, Price, 0, Content Rating, 0, Genres, 1, App, 1, Translated_Review, 1, Sentiment, 1, Sentiment_Polarity, 1, Sentiment_Subjectivity
Question: How many of the users hold neutral attitude on "10 Best Foods for You" app and what category is this app?
Evidence: neutral attitude refers to Sentiment = 'Neutral';
SQL: 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'