1sf/bird-sql-train-with-schema huggingface dataset:
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: State the category of the label that represented the behavior category of app id 4955831798976240000.
Evidence: label that represented the behavior category refers to label_id;
SQL: SELECT T1.category FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T2.app_id = 4955831798976240000
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: How many female users use device model of MI 3?
Evidence: female refers to gender = 'F';
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'F' AND T2.device_model = 'MI 3'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Among the male users, how many users use device model of Desire 820?
Evidence: male refers to gender = 'M';
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.device_model = 'Desire 820' AND T1.gender = 'M'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Among the users who are above 20, how many users use device model of ELIFE E7 Mini?
Evidence: above 20 refers to age > 20;
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.device_model = 'ELIFE E7 Mini' AND T1.age > 20
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: State the number of users who are under 50 and above 20 use device model of Galaxy Premier.
Evidence: under 50 and above 20 refers to age BTWEEEN 20 AND 50;
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.age BETWEEN 20 AND 50 AND T2.device_model = 'Galaxy Premier'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Give the number of male users who use phone branded HTC.
Evidence: male refers to gender = 'M';
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'M' AND T2.phone_brand = 'HTC'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: How many users who are between 20 and 60 use phone brand of TCL?
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.age BETWEEN 20 AND 60 AND T2.phone_brand = 'TCL'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Among the users who use SUGAR, calculate the percentage of those who are above 20 years old.
Evidence: SUGAR refers to phone_brand = 'SUGAR'; percentage = MULTIPLY(DIVIDE(SUM(age > 20), COUNT(device_id)) 1.0); above 20 years old refers to age > 20;
SQL: SELECT SUM(IIF(T1.age > 20, 1, 0)) / COUNT(T1.device_id) AS per FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.phone_brand = 'SUGAR'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Indicate the location of all the events that occurred on April 30, 2016.
Evidence: location = longitude, latitude; on April 30, 2016 refers timestamp BETWEEN '2016-04-30 00:00:00' AND '2016-04-30 23:59:59';
SQL: SELECT longitude, latitude FROM events WHERE date(timestamp) = '2016-04-30'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: How many different models does the HTC brand have?
Evidence: models refers to device_model; HTC brand refers to phone_brand = 'HTC';
SQL: SELECT COUNT(device_model) FROM phone_brand_device_model2 WHERE phone_brand = 'HTC'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Identify all installed and activated apps by their id.
Evidence: installed refers to is_installed = 1; activated refers to is_active = 1; id refers to app_id;
SQL: SELECT app_id FROM app_events WHERE is_active = 1 AND is_installed = 1
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: How many apps are labeled 7?
Evidence: labeled 7 refers to label_id = 7;
SQL: SELECT COUNT(app_id) FROM app_labels WHERE label_id = 7
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Identify by their id all the devices that are used by women who are in the age range of 29 to 31 years.
Evidence: id refers to device_id; women refers to gender = 'F'; age range of 29 to 31 years refers to age between 29 and 31;
SQL: SELECT device_id FROM gender_age_train WHERE age BETWEEN 29 AND 31 AND gender = 'F'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Identify by their id all the apps that belong to the game-stress reliever category.
Evidence: id refers to device_id;
SQL: SELECT T2.app_id FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T1.category = 'game-stress reliever'
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: On what date were the most events logged on devices for 40-year-old male users?
Evidence: date refers to timestamp; most events refers to MAX(COUNT(event_id)); 40-year-old  refers to age = 40; male refers to gender = 'M';
SQL: SELECT T.timestamp FROM ( SELECT T2.timestamp, COUNT(T2.event_id) AS num FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'M' AND T1.age = 40 GROUP BY T2.timestamp ) AS T ORDER BY T.num DESC LIMIT 1
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: On which brand of phone are the most applications installed?
Evidence: brand of phone refers to phone_brand; most applications are installed refers to MAX(COUNT(is_installed = 1));
SQL: SELECT T.phone_brand FROM ( SELECT T1.phone_brand, COUNT(T4.is_active) AS num FROM phone_brand_device_model2 AS T1 INNER JOIN gender_age AS T2 ON T1.device_id = T2.device_id INNER JOIN events_relevant AS T3 ON T2.device_id = T3.device_id INNER JOIN app_events_relevant AS T4 ON T3.event_id = T4.event_id WHERE T4.is_active = 1 GROUP BY T1.phone_brand ) AS T ORDER BY T.num DESC LIMIT 1
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: How many men under the age of 23 have apps installed but are not active on their devices?
Evidence: men refers to gender = 'M'; under the age of 23 refers to age < 23; installed refers to is_installed = 1; not active refers to is_active = 0;
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id INNER JOIN app_events_relevant AS T3 ON T2.event_id = T3.event_id WHERE T1.gender = 'M' AND T3.is_active = 0 AND T1.age < 23
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: How many women have apps from the game-Finding fault category installed on their device?
Evidence: women refers to gender = 'F'; installed refers to is_installed = 1;
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id INNER JOIN app_events_relevant AS T3 ON T2.event_id = T3.event_id WHERE T1.age < 23 AND T1.gender = 'F' AND T3.is_active = 0 AND T3.is_installed = 1
Database: talkingdata
Tables: app_all, app_events, app_events_relevant, app_labels, events, events_relevant, gender_age, gender_age_test, gender_age_train, label_categories, phone_brand_device_model2, sample_submission
Columns (table index, column name): -1, *, 0, app_id, 1, event_id, 1, app_id, 1, is_installed, 1, is_active, 2, event_id, 2, app_id, 2, is_installed, 2, is_active, 3, app_id, 3, label_id, 4, event_id, 4, device_id, 4, timestamp, 4, longitude, 4, latitude, 5, event_id, 5, device_id, 5, timestamp, 5, longitude, 5, latitude, 6, device_id, 6, gender, 6, age, 6, group, 7, device_id, 8, device_id, 8, gender, 8, age, 8, group, 9, label_id, 9, category, 10, device_id, 10, phone_brand, 10, device_model, 11, device_id, 11, F23-, 11, F24-26, 11, F27-28, 11, F29-32, 11, F33-42, 11, F43+, 11, M22-, 11, M23-26, 11, M27-28, 11, M29-31, 11, M32-38, 11, M39+
Question: Which gender logged in the most to an event in the first 10 days of May 2016?
Evidence: gender that logged in the most refers to MAX(COUNT(gender)); first 10 days of May 2016 refers to timestamp BETWEEN '2016-05-01 00:00:00' AND '2016-05-10 23:59:59';
SQL: SELECT T.gender FROM ( SELECT T1.gender, COUNT(T1.device_id) AS num FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id WHERE date(T2.timestamp) BETWEEN '2016-05-01' AND '2016-05-10' GROUP BY T1.gender ) AS T ORDER BY T.num DESC LIMIT 1