id int64 0 9.43k | db_id stringclasses 69
values | schema stringclasses 69
values | question stringlengths 24 325 | output stringlengths 23 804 | evidence stringlengths 0 673 | filtered_schema listlengths 0 16 |
|---|---|---|---|---|---|---|
2,500 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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 | 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) | [
"Genes.Chromosome",
"Genes.GeneID",
"Interactions.Expression_Corr",
"Interactions.GeneID1",
"Interactions.GeneID2"
] |
2,501 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | [
"Genes.Class",
"Genes.GeneID",
"Interactions.Expression_Corr",
"Interactions.GeneID1"
] | |
2,502 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | [
"Genes.Function",
"Genes.GeneID",
"Genes.Localization"
] | |
2,503 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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') | [
"Classification.GeneID",
"Classification.Localization"
] | |
2,504 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | 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% | [
"Interactions.Expression_Corr",
"Interactions.Type"
] |
2,505 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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; | Percentage = count(genes located in the cytoskeleton unknown class) / count(genes located in the cytoskeleton) * 100% | [
"Genes.GeneID",
"Genes.Localization",
"Genes.Phenotype"
] |
2,506 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | [
"Genes.Essential",
"Genes.Function",
"Genes.GeneID",
"Interactions.GeneID1",
"Interactions.Type"
] | |
2,507 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | If the Expression_Corr value is positive then it's positively correlated | [
"Genes.GeneID",
"Genes.Localization",
"Interactions.Expression_Corr",
"Interactions.GeneID1"
] |
2,508 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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 | [
"Genes.Class",
"Genes.Essential",
"Genes.GeneID",
"Genes.Localization",
"Interactions.Expression_Corr",
"Interactions.GeneID1"
] | |
2,509 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | [
"Genes.Class",
"Genes.Essential",
"Genes.GeneID",
"Genes.Phenotype",
"Interactions.GeneID1",
"Interactions.Type"
] | |
2,510 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | Percentage of no interaction = [count(nucleic acid metabolism, PS00107, no interaction) / count(nucleic acid metabolism, PS00107) * 100% | [
"Genes.GeneID",
"Genes.Motif",
"Genes.Phenotype",
"Interactions.Expression_Corr",
"Interactions.GeneID1"
] |
2,511 | genes | CREATE TABLE Classification
(
GeneID TEXT not null
primary key,
Localization TEXT not null
);
CREATE TABLE Genes
(
GeneID TEXT not null,
Essential TEXT not null,
Class TEXT not null,
Complex TEXT null,
Phenotype TEXT not null,
Motif TEXT ... | 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' | 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% | [
"Genes.Essential",
"Genes.GeneID",
"Interactions.Expression_Corr",
"Interactions.GeneID1"
] |
2,512 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | updated in January of 2018 refers to Last Updated BETWEEN 'January 1, 2018' and 'January 31, 2018'; | [
"playstore.App",
"playstore.`Last Updated`"
] |
2,513 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | mildly likes the app refers to Sentiment_Polarity> = 0 and Sentiment_Polarity<0.5; | [
"playstore.App",
"playstore.`Last Updated`",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,514 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | user holds neutral attitude refers to Sentiment = 'Neutral'; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,515 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | highest amount of -1 sentiment polarity score refers to MAX(Count(Sentiment_Polarity = 1.0)) | [
"playstore.App",
"playstore.Category",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,516 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | average sentiment polarity score = AVG(Sentiment_Polarity); age group the app is target at refers to Content Rating; | [
"playstore.App",
"playstore.`Content Rating`",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,517 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | 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; | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,518 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | Sentiment_Subjectivity<0.5; current version refers to Current Ver; | [
"playstore.App",
"playstore.`Current Ver`",
"user_reviews.App",
"user_reviews.Sentiment_Subjectivity"
] |
2,519 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | How many apps have rating of 5? | SELECT COUNT(App) FROM playstore WHERE Rating = 5 | FALSE; | [
"playstore.App",
"playstore.Rating"
] |
2,520 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | free app refers to price = 0; most installed app refers to MAX(Installs); | [
"playstore.App",
"playstore.Installs",
"playstore.Price"
] |
2,521 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | Name the top 10 most reviewed apps. | SELECT DISTINCT App FROM playstore ORDER BY Reviews DESC LIMIT 10 | most reviewed app refers to MAX(Reviews); | [
"playstore.App",
"playstore.Reviews"
] |
2,522 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | neutral attitude refers to Sentiment = 'Neutral'; | [
"playstore.App",
"playstore.Category",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,523 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | users pretty much likes the app refers to Sentiment_Polarity = 'Positive'; | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,524 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | lowest rating refers to Rating = 1; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,525 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' ) | compatible with android refers to Android Ver; Android Ver" = '8.0 and up'; | [
"playstore.App",
"playstore.`Android Ver`"
] |
2,526 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | multiple genres refers to COUNT(Genres>1; total sentiment subjectivity = Sum(Sentiment_Subjectivity); | [
"playstore.App",
"playstore.Genres",
"user_reviews.App",
"user_reviews.Sentiment_Subjectivity"
] |
2,527 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 ) | since year 2015 refers to "Last Updated"<'January 1, 2015'; | [
"playstore.App"
] |
2,528 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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+' | total installs = SUM(Installs); | [
"playstore.App",
"playstore.Installs",
"playstore.`Content Rating`",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,529 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | best selling app = MAX(MULTIPLY(Price, Installs)); | [
"playstore.App",
"playstore.Price",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,530 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | average rating = AVG(Rating where Category = 'COMICS'); number of users who hold a positive attitude towards the app refers to SUM(Sentiment = 'Positive'); | [
"playstore.App",
"playstore.Category",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,531 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | What is the rating for "Draw A Stickman"? | SELECT Rating FROM playstore WHERE APP = 'Draw A Stickman' | Draw A Stickman refers to App = 'Draw A Stickman'; | [
"playstore.APP",
"playstore.Rating"
] |
2,532 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | Brit + Co refers to App = 'Brit + Co'; comment refers to Translated Review NOT null; | [
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,533 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | shopping apps refers to Genre = 'Shopping'; most reviews refers to MAX(Reviews); | [
"playstore.App",
"playstore.Genres"
] |
2,534 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | neutral reviews refers to Sentiment = 'Neutral'; | [
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,535 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | What are the apps with only 5,000+ installs? | SELECT DISTINCT App FROM playstore WHERE Installs = '5,000+' | Installs = '5,000+'; | [
"playstore.App",
"playstore.Installs"
] |
2,536 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | negative comment refers to Sentiment = 'Negative'; | [
"user_reviews.App",
"user_reviews.Sentiment",
"user_reviews.Translated_Review"
] |
2,537 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | paid app refers to Type = 'Paid'; negative comment refers to Sentiment = 'Negative'; paid app with most negative comments refers to MAX(COUNT(Sentiment = 'Negative')) where Type = 'Paid'; | [
"playstore.App",
"playstore.Type",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,538 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | negative comment refers to Sentiment = 'Negative'; Installs = '100,000,000+'; | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,539 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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%' | app with gr8 in their comments refers to Translated_Review LIKE '%gr8%'; | [
"playstore.App",
"playstore.`Content Rating`",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,540 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 ) | total sentiment polarity score = sum(Sentiment_Polarity); most expensive app refers to MAX(Price); | [
"playstore.App",
"playstore.Price",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,541 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | Golfshot Plus: Golf GPS refers to App = 'Golfshot Plus: Golf GPS'; review refers to Translated_Review; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,542 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | Photography app refers to Genre = 'Photography'; highest total sentiment subjectivity score = MAX(sum(Sentiment_Subjectivity)); | [
"playstore.App",
"playstore.Genres",
"user_reviews.App",
"user_reviews.Sentiment_Subjectivity"
] |
2,543 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | comments refers to Translated_Review; lowest rated refers to Rating = 1; Mature 17+ refers to Content Rating = 'Mature 17+ '; | [
"playstore.App",
"playstore.Rating",
"playstore.`Content Rating`",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,544 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | installments refers to Installs; highest total sentiment polarity score = MAX(SUM(Sentiment_Polarity)); | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,545 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | neutral comments refers to Sentiment = 'Neutral'; weather app refers to Genre = 'Weather'; | [
"playstore.App",
"playstore.Genres",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,546 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | no comment refers to Translated_Review = 'nan'; most no comment reviews = (MAX(COUNT(Translated_Review = 'nan'))); | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,547 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | Onefootball - Soccer Scores refers to App = 'Onefootball - Soccer Scores'; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment_Subjectivity"
] |
2,548 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | no comment refers to Translated_Review = 'nan'; percentage = DIVIDE((SUM(Content Rating = 'Teen')), COUNT(*)); | [
"playstore.App",
"playstore.`Content Rating`",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,549 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | Which apps have 5 rating? List out then application name. | SELECT DISTINCT App FROM playstore WHERE Rating = 5 | application name refers to App; | [
"playstore.App",
"playstore.Rating"
] |
2,550 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | Reviews>75000000; suitable for teenagers refers to Content Rating = 'Teen'; | [
"playstore.App",
"playstore.Reviews",
"playstore.`Content Rating`"
] |
2,551 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | List out genre that have downloads more than 1000000000. | SELECT Genres FROM playstore WHERE Installs = '1,000,000,000+' GROUP BY Genres | downloads and installs are synonyms; Installs = '1,000,000,000+'; | [
"playstore.Genres",
"playstore.Installs"
] |
2,552 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | What is the average price for a dating application? | SELECT AVG(Price) FROM playstore WHERE Genres = 'Dating' | average price = AVG(Price where Genre = 'Dating'); dating application refers to Genre = 'Dating'; | [
"playstore.Genres",
"playstore.Price"
] |
2,553 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | downloads and installs are synonyms; entertainment apps refers to Category = 'ENTERTAINMENT'; | [
"playstore.Category",
"playstore.Installs",
"playstore.Size"
] |
2,554 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | What is the average review number for application with 5 rating? | SELECT AVG(Reviews) FROM playstore WHERE Rating = 5 | average review = AVG(Review); application refers to app; Rating = 5; | [
"playstore.Rating",
"playstore.Reviews"
] |
2,555 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 ) | sentiment review refers to Sentiment_Polarity; Sentiment_Polarity>0.5; | [
"user_reviews.App",
"user_reviews.Sentiment",
"user_reviews.Sentiment_Polarity"
] |
2,556 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 = ... | percentage = DIVIDE(SUBTRACT(SUM(Sentiment = 'Positive')), (SUM(Sentiment = 'Negative')), SUM(Sentiment = 'Negative')) as percentage; having more positive sentiment than negative sentiment refers to Sentiment = 'Positive'>Sentiment = 'Negative'; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,557 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | doest not have negative sentiment refers to Sentiment! = 'Negative'; average = AVG(Sentiment_Polarity); | [
"playstore.App",
"user_reviews.App",
"user_reviews.Sentiment",
"user_reviews.Sentiment_Polarity"
] |
2,558 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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) > '2... | percentage = DIVIDE(SUBTRACT(SUM(Sentiment = 'Positive')), (SUM(Sentiment = 'Negative'))), (SUM(Sentiment = 'Negative')) as percent; Last Updated>'2015'; | [
"playstore.App",
"playstore.`Last Updated`",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,559 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | paid refers to Type = 'Paid'; application refers to App; Rating>4.5; Last Updated>'2018; percentage = DIVIDE(SUM(Genres = 'Mature 17+' and Rating>4.5 and substr("Last Updated",-4,4)>'2018' )), (COUNT(App)) as percent; | [
"playstore.App",
"playstore.Rating",
"playstore.Type"
] |
2,560 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | What genre does Honkai Impact 3rd belong to? | SELECT DISTINCT Genres FROM playstore WHERE App = 'Honkai Impact 3rd' | Honkai Impact 3rd is the App; | [
"playstore.App",
"playstore.Genres"
] |
2,561 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | List down the rating for the App Learn C++. | SELECT DISTINCT Rating FROM playstore WHERE App = 'Learn C++' | FALSE; | [
"playstore.App",
"playstore.Rating"
] |
2,562 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | average price = AVG(Price); | [
"playstore.Genres",
"playstore.Price"
] |
2,563 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | Browser 4G is the App; pretty positive favorability refers to Sentiment_Polarity score = 0.5 | [
"playstore.App",
"playstore.Size",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,564 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | FALSE; | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,565 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | average sentiment polarity score = AVG(Sentiment_Polarity); Golf GPS Rangefinder: Golf Pad is the App; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,566 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | lowest rating refers to MIN(Rating); puzzle is the genre; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,567 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | Fate/Grand Order is the App; percentage ratio = MULTIPLY(DIVIDE((SUM(Sentiment = 'Positive')), (SUM(Sentiment = 'Negative'))), 100); | [
"playstore.App",
"playstore.`Current Ver`",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,568 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | FREEDOME VPN Unlimited anonymous Wifi Security is the App; percentage = MULTIPLY(DIVIDE((SUM(Sentiment = 'Positive')), (COUNT(*))), 100) | [
"playstore.App",
"playstore.Installs",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,569 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | highest sentiment polarity score refers to MAX(Sentiment_Polarity); | [
"playstore.App",
"playstore.Genres",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,570 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | Dragon Ball Legends is the app; users who dislikes the app refers to Sentiment_Polarity<-0.5; | [
"playstore.App",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,571 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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 | education App refers to Category = 'EDUCATION'; worst rated app refers to Rating = 1; | [
"playstore.App",
"playstore.Category",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,572 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | paid sports Apps refers to type = 'Paid' and Category = 'SPORTS'; | [
"playstore.App",
"playstore.Category",
"playstore.Type",
"user_reviews.App",
"user_reviews.Translated_Review"
] |
2,573 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | targeted to teen refers to Content Rating = 'Teen'; average = AVG(Sentiment_Polarity); | [
"playstore.App",
"playstore.Genres",
"playstore.`Content Rating`",
"user_reviews.App",
"user_reviews.Sentiment_Polarity"
] |
2,574 | app_store | CREATE TABLE "playstore"
(
App TEXT,
Category TEXT,
Rating REAL,
Reviews INTEGER,
Size TEXT,
Installs TEXT,
Type TEXT,
Price TEXT,
"Content Rating" TEXT,
Genres TEXT
);
CREATE TABLE "use... | 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' | average rating = AVG(Rating); percentage = MULTIPLY(DIVIDE((SUM(Sentiment = 'Positive')), (COUNT(*)), 100)); | [
"playstore.App",
"playstore.Genres",
"playstore.Rating",
"user_reviews.App",
"user_reviews.Sentiment"
] |
2,575 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | the most number of sales team refers to MAX(COUNT(Sales Team)); | [
"Sales Team.Region",
"Sales Team.`Sales Team`"
] |
2,576 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | name containing the word 'Group' refers to Customer Names LIKE '%Group%'; | [
"Customers.T",
"Customers.`Customer Names`"
] |
2,577 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode TEXT
... | What is the average median income for all City type of stores? | SELECT AVG(`Median Income`) FROM `Store Locations` WHERE Type = 'City' | AVG(Median Income) where Type = 'City'; | [
"Store Locations.Type",
"Store Locations.`Median Income`"
] |
2,578 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | [
"Sales Orders.OrderNumber",
"Sales Orders._SalesTeamID",
"Sales Team.Region",
"Sales Team.SalesTeamID",
"Sales Team.`Sales Team`"
] | |
2,579 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | [
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders._ProductID",
"Sales Orders._SalesTeamID",
"Sales Team.SalesTeamID",
"Sales Team.`Sales Team`"
] | |
2,580 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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`... | MAX(Discount Applied) where Product Name = 'Cocktail Glasses'; orders in 2020 refer to the OrderDate between 01-01-2020 and 31-12-2020; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders.OrderDate",
"Sales Orders._CustomerID",
"Sales Orders._ProductID",
"Sales Orders.`Discount Applied`"
] |
2,581 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | In-Store sales refer to Sales Channel = 'In-Store'; city refers to City Name; | [
"Sales Orders.OrderNumber",
"Sales Orders._StoreID",
"Sales Orders.`Sales Channel`",
"Store Locations.StoreID",
"Store Locations.`City Name`"
] |
2,582 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | the most expensive refers to MAX(Unit Cost); who refers to Customer Names; when refers to OrderDate; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Products.ProductID",
"Sales Orders.OrderDate",
"Sales Orders.OrderNumber",
"Sales Orders._CustomerID",
"Sales Orders._ProductID",
"Sales Orders.`Unit Cost`"
] |
2,583 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | Rochester Ltd is the name of the customer; all the numbers ordered refer to OrderNumber; 2018 refers to SUBSTR(OrderDate, -2) = '18'; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Sales Orders.OrderDate",
"Sales Orders.OrderNumber",
"Sales Orders._CustomerID"
] |
2,584 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | all the orders from WARE-NMK1003 refer to OrderNumber where WarehouseCode = 'WARE-NMK1003'; product refers to Product Name; | [
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders.WarehouseCode",
"Sales Orders._ProductID",
"Sales Orders._SalesTeamID",
"Sales Team.SalesTeamID",
"Sales Team.`Sales Team`"
] |
2,585 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | orders online refer to Sales Channel = 'Online'; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Sales Orders._CustomerID",
"Sales Orders.`Sales Channel`"
] |
2,586 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | net profit can be computed as SUBTRACT(Unit Price, Unit Cost); AVG(net profit) where Product Name = 'Bakeware'; | [
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders._ProductID",
"Sales Orders.`Unit Cost`",
"Sales Orders.`Unit Price`"
] |
2,587 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | net profit can be computed as SUBTRACT(Unit Price, Unit Cost); the greatest net profit in 2020 refers to MAX(net profit) where OrderDate LIKE '%/20'; | [
"Sales Orders.OrderDate",
"Sales Orders._SalesTeamID",
"Sales Orders.`Unit Cost`",
"Sales Orders.`Unit Price`",
"Sales Team.SalesTeamID",
"Sales Team.`Sales Team`"
] |
2,588 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | net profit can be computed as SUBTRACT(Unit Price, Unit Cost); Joshua Bennett is the name of Sales Team; | [
"Sales Orders.OrderNumber",
"Sales Orders._SalesTeamID",
"Sales Orders.`Unit Cost`",
"Sales Orders.`Unit Price`",
"Sales Team.SalesTeamID",
"Sales Team.`Sales Team`"
] |
2,589 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | shipped in July 2018 refers to ShipDate between 01-07-2018 and 31-07-2018; DIVIDE(COUNT(OrderNumber where Product Name = 'Home Fragrances' and SUBSTR(OrderDate, 1, 1) = '7'), COUNT(OrderNumber where SUBSTR(ShipDate, -2) = '18')) as percentage; | [
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders.OrderNumber",
"Sales Orders.ShipDate",
"Sales Orders._ProductID"
] |
2,590 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | names that start with alphabet "W" refer to Customer Names LIKE 'W%'; | [
"Customers.CustomerID",
"Customers.`Customer Names`"
] |
2,591 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | names that include the word "Outdoor" refer to Product Name LIKE '%Outdoor%'; | [
"Products.ProductID",
"Products.T",
"Products.`Product Name`"
] |
2,592 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | 40% discount refers to Discount Applied = 0.4; in-store channel refers to Sales Channel = 'In-Store'; orders refer to OrderNumber; | [
"Sales Orders.OrderNumber",
"Sales Orders.T",
"Sales Orders.WarehouseCode",
"Sales Orders.`Discount Applied`",
"Sales Orders.`Sales Channel`"
] |
2,593 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 | most populated refers to Max(Population); | [
"Store Locations.Population",
"Store Locations.State",
"Store Locations.`City Name`",
"Store Locations.`Median Income`"
] |
2,594 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | ID refers to StoreID; | [
"Regions.Region",
"Regions.StateCode",
"Store Locations.County",
"Store Locations.StateCode",
"Store Locations.StoreID",
"Store Locations.`City Name`"
] |
2,595 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | COUNT(StoreID) < COUNT(StoreID where Type = 'Borough') < COUNT(StoreID where Type = 'CDP'); | [
"Regions.State",
"Regions.StateCode",
"Store Locations.StateCode",
"Store Locations.StoreID",
"Store Locations.Type",
"Store Locations.`City Name`"
] |
2,596 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | sale team ID of 18 refers to _SalesTeamID = 18; COUNT(OrderNumber where Sales Channel = 'In-Store') > COUNT(OrderNumber where Sales Channel = 'Online'); | [
"Sales Orders._SalesTeamID",
"Sales Orders.`Sales Channel`",
"Sales Team.Region",
"Sales Team.SalesTeamID",
"Sales Team.`Sales Team`"
] |
2,597 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 ' | Medline is the name of the customer; DIVIDE(COUNT(OrderNumber where Sales Channel = 'In-Store' and Customer Names = 'Medline'), COUNT(OrderNumber where Customer Names = 'Medline')) as percentage; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Sales Orders._CustomerID",
"Sales Orders.`Sales Channel`"
] |
2,598 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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' | delivery period in 2019 means time between placing of an order and the receipt of product and refers to SUBTRACT(DeliveryDate, OrderDate) where SUBSTR(OrderDate, -2 ) = '19'; Sales Channel = 'Wholesale'; Product Name = 'Bedroom Furniture'; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders.DeliveryDate",
"Sales Orders.OrderDate",
"Sales Orders._CustomerID",
"Sales Orders._ProductID",
"Sales Orders.`Sales Channel`"
] |
2,599 | regional_sales | CREATE TABLE Customers
(
CustomerID INTEGER
constraint Customers_pk
primary key,
"Customer Names" TEXT
);
CREATE TABLE Products
(
ProductID INTEGER
constraint Products_pk
primary key,
"Product Name" TEXT
);
CREATE TABLE Regions
(
StateCode 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 ) WHER... | over 3800 USD in net profit refers to SUBTRACT(Unit Price, Unit Cost) where Net Profit > 3800; | [
"Customers.CustomerID",
"Customers.`Customer Names`",
"Products.ProductID",
"Products.`Product Name`",
"Sales Orders._CustomerID",
"Sales Orders._ProductID",
"Sales Orders.`Unit Cost`",
"Sales Orders.`Unit Price`"
] |
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