QIAN-ME/bird_schema_data huggingface dataset:
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【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. updated in January of 2018 refers to Last Updated BETWEEN 'January 1, 2018' and 'January 31, 2018';

    【Evidence】
    updated in January of 2018 refers to Last Updated BETWEEN 'January 1, 2018' and 'January 31, 2018';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    How many users mildly likes the 7 Minute Workout app and when was it last updated? mildly likes the app refers to Sentiment_Polarity> = 0 and Sentiment_Polarity<0.5;

    【Evidence】
    mildly likes the app refers to Sentiment_Polarity> = 0 and Sentiment_Polarity<0.5;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    How many users holds neutral attitude towards the HTC Weather app? Indicate the app's rating on the Google Play Store. user holds neutral attitude refers to Sentiment = 'Neutral';

    【Evidence】
    user holds neutral attitude refers to Sentiment = 'Neutral';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    What is the name and category of the app with the highest amount of -1 sentiment polarity score? highest amount of -1 sentiment polarity score refers to MAX(Count(Sentiment_Polarity = 1.0))

    【Evidence】
    highest amount of -1 sentiment polarity score refers to MAX(Count(Sentiment_Polarity = 1.0))

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    What is the average sentiment polarity score of the Cooking Fever app? Indicate the age group that the app is targeted at. average sentiment polarity score = AVG(Sentiment_Polarity); age group the app is target at refers to Content Rating;

    【Evidence】
    average sentiment polarity score = AVG(Sentiment_Polarity); age group the app is target at refers to Content Rating;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【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? 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;

    【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;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    For the Akinator app, how many reviews have sentiment subjectivity of no more than 0.5 and what is its current version? Sentiment_Subjectivity<0.5; current version refers to Current Ver;

    【Evidence】
    Sentiment_Subjectivity<0.5; current version refers to Current Ver;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    How many apps have rating of 5? FALSE;

    【Evidence】
    FALSE;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(App) FROM playstore WHERE Rating = 5
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    What are the top 5 installed free apps? free app refers to price = 0; most installed app refers to MAX(Installs);

    【Evidence】
    free app refers to price = 0; most installed app refers to MAX(Installs);

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT App FROM playstore WHERE Price = 0 ORDER BY CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER) DESC LIMIT 5
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    Name the top 10 most reviewed apps. most reviewed app refers to MAX(Reviews);

    【Evidence】
    most reviewed app refers to MAX(Reviews);

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT DISTINCT App FROM playstore ORDER BY Reviews DESC LIMIT 10
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    How many of the users hold neutral attitude on "10 Best Foods for You" app and what category is this app? neutral attitude refers to Sentiment = 'Neutral';

    【Evidence】
    neutral attitude refers to Sentiment = 'Neutral';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

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'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    What are the apps that users pretty like this app and how many installs amount of these apps? users pretty much likes the app refers to Sentiment_Polarity = 'Positive';

    【Evidence】
    users pretty much likes the app refers to Sentiment_Polarity = 'Positive';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: 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
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    List apps whose rating is 3.9 and state the translated review of each app. lowest rating refers to Rating = 1;

    【Evidence】
    lowest rating refers to Rating = 1;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: 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
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    How many apps that are only compatible with Android ver 8.0 and above? List down the users' sentiment of these apps. compatible with android refers to Android Ver; Android Ver" = '8.0 and up';

    【Evidence】
    compatible with android refers to Android Ver; Android Ver" = '8.0 and up';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT DISTINCT Sentiment FROM user_reviews WHERE App IN ( SELECT App FROM playstore WHERE `Android Ver` = '8.0 and up' )
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 app_store
【Schema】
# Table: user_reviews
[
(App:TEXT, Examples: [10 Best Foods for You]),
(Translated_Review:TEXT),
(Sentiment:TEXT, Examples: [Positive, nan, Neutral]),
(Sentiment_Polarity:TEXT, Examples: [1.0, 0.25, nan]),
(Sentiment_Subjectivity:TEXT, Examples: [0.5333333333333333, 0.28846153846153844, nan])
]
# Table: playstore
[
(App:TEXT, Examples: [Photo Editor & Candy Camera & Grid & ScrapBook]),
(Category:TEXT, Examples: [ART_AND_DESIGN, AUTO_AND_VEHICLES, BEAUTY]),
(Rating:REAL, Examples: [4.1, 3.9, 4.7]),
(Reviews:INTEGER, Examples: [159, 967, 87510]),
(Size:TEXT, Examples: [19M, 14M, 8.7M]),
(Installs:TEXT, Examples: [10,000+, 500,000+, 5,000,000+]),
(Type:TEXT, Examples: [Free, Paid, NaN]),
(Price:TEXT, Examples: [0, $4.99, $3.99]),
(Content Rating:TEXT, Examples: [Everyone, Teen, Everyone 10+]),
(Genres:TEXT, Examples: [Art & Design])
]
【Foreign keys】
user_reviews.App=playstore.App

    【Question】
    Which apps have multiple genres and what is the total sentiment subjectivity of these apps? multiple genres refers to COUNT(Genres>1; total sentiment subjectivity = Sum(Sentiment_Subjectivity);

    【Evidence】
    multiple genres refers to COUNT(Genres>1; total sentiment subjectivity = Sum(Sentiment_Subjectivity);

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT SUM(T2.Sentiment_Subjectivity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres > 1