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: What age group is the most using SM-T2558 model phones?
Evidence: age group using SM-T2558 model phones the most refers to MAX(COUNT(group WHERE device_model = 'SM-T2558')); SM-T2558 model phones refers to device_model = 'SM-T2558';
SQL: SELECT T.`group` FROM ( SELECT T1.`group`, COUNT(T1.device_id) AS num FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.device_model = 'SM-T2558' GROUP BY T1.`group` ) 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 people over the age of 50 do not have HTC One M8 Eye phones?
Evidence: over the age of 50 refers to age > 50; do not have HTC One M8 Eye phones refers to phone_brand ! = 'HTC' AND device_model ! = 'One M8 Eye';
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 > 50 AND T2.device_model != 'One M8 Eye' 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: Locate all events on devices of women under 30 years old.
Evidence: locate = longitude, latitude; women refers to gender = 'F'; under 30 years old refers to age < 30;
SQL: SELECT T1.device_id FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id WHERE T1.gender = 'F' AND T1.age < 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: What percentage of women do not have applications installed on their mobile with respect to men?
Evidence: percentage = MULTIPLY(DIVIDE(SUM(gender = 'F'), SUM(gender = 'M')), 1.0); women refers to gender = 'F'; not installed refers to is_installed = 0; men refers to gender = 'M';
SQL: SELECT SUM(IIF(T1.gender = 'F', 1, 0)) / SUM(IIF(T1.gender = 'M', 1, 0)) AS per 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 T3.is_installed = 0
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: Calculate the average age of people who have apps installed but are not active on their devices.
Evidence: average age = AVG(age); installed refers to is_installed = 1; not active refers to is_active = 0;
SQL: SELECT AVG(T1.age) 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 T3.is_installed = 1 AND T3.is_active = 0
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: Please list any three events that happened on the 1st of May 2016 that have the same latitude of 31.
Evidence: on the 1st of May 2016 refers to timestamp like '2016-05-01%';
SQL: SELECT event_id FROM events WHERE timestamp LIKE '2016-05-01%' AND latitude = 31 LIMIT 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: Please list any three events that have the longitude and latitude of 0.
SQL: SELECT event_id FROM events WHERE longitude = 0 AND latitude = 0 LIMIT 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: What is the difference between the events of device number -9222956879900150000 that can be located and those that are unable to be located?
Evidence: difference = SUBTRACT(SUM(latitude! = 0 and longitude! = 0), SUM(latitude = 0 and longitude = 0)); device number refers to device_id; device_id = -922956879900150000; can be location refers to latitude ! = 0 and longitude ! = 0; unable to be location refers to latitude = 0 and longitude = 0;
SQL: SELECT SUM(IIF(latitude != 0 AND longitude != 0, 1, 0)) - SUM(IIF(latitude = 0 AND longitude = 0, 1, 0)) AS diff FROM events WHERE device_id = '-922956879900150000'
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: Please list any three devices that are owned by female users.
Evidence: female refers to gender = 'F';
SQL: SELECT device_id FROM gender_age WHERE gender = 'F' LIMIT 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: Please list any five app categories that are related to games, along with their label ID.
Evidence: app categories refers to category; related to games refers to category like '%game%';
SQL: SELECT category, label_id FROM label_categories WHERE category LIKE '%game%' LIMIT 5
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: Please list any three OPPO device models.
Evidence: OPPO refers to phone_brand = 'OPPO';
SQL: SELECT device_model FROM phone_brand_device_model2 WHERE phone_brand = 'OPPO' LIMIT 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: What is the percentage of users who experienced event number 6 who have the app installed but do not use the app?
Evidence: percentage = MULTIPLY(DIVIDE(SUM(is_installed = 1 and is_active = 0), COUNT(app_id)), 1.0); event number refers to event_id = 6; installed refers to is_installed = 1; do not use refers to is_active = 0;
SQL: SELECT SUM(IIF(is_installed = 1 AND is_active = 0, 1, 0)) / COUNT(app_id) AS perrcent FROM app_events WHERE event_id = 6
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 owned more of the Galaxy Note 2 device model?
Evidence: gender that owned more = SUBTRACT(IF(SUM(gender = 'M'), SUM(gender = 'F'),'M','F'));
SQL: SELECT IIF(SUM(IIF(T1.gender = 'M', 1, 0)) - SUM(IIF(T1.gender = 'F', 1, 0)) > 0, 'M', 'F') AS gender FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.device_model = 'Galaxy Note 2'
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: When did event number 2 happen and how many users were active?
Evidence: event number refers to event_id; event_id = 2; active refers to is_active = 1;
SQL: SELECT COUNT(T1.app_id) AS num FROM app_events AS T1 INNER JOIN events AS T2 ON T1.event_id = T2.event_id WHERE T1.event_id = 2 AND T1.is_active = 1 GROUP BY T2.timestamp
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 behavior category does user number 5902120154267990000 belong to?
Evidence: behavior category refers to category; number refers to app_id; app_id = 5902120154267990000;
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 = 5902120154267990000
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 belong to the same behavior category as comics?
Evidence: behavior category refers to category; category = 'comics';
SQL: SELECT COUNT(T2.app_id) FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T1.category = 'comics'
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: What is the age and gender of the person who uses the device number 29182687948017100 on event number 1?
Evidence: device number refers to device_id; device_id = 29182687948017100; event number refers to event_id; and event_id = 1;
SQL: SELECT T1.age, T1.gender FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id WHERE T1.device_id = 29182687948017100 AND T2.event_id = 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 male users have the log of events at the same longitude of 114?
Evidence: male refers to gender = 'M';
SQL: SELECT COUNT(T1.device_id) FROM gender_age AS T1 INNER JOIN events_relevant AS T2 ON T1.device_id = T2.device_id WHERE T2.longitude = 114 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: When did event number 7 happen for user number -8022267440849930000?
Evidence: event number refers to event_id; event_id = 7; user number refers to app_id; app_id = -8022267440849930000;
SQL: SELECT T1.timestamp FROM events_relevant AS T1 INNER JOIN app_events AS T2 ON T1.event_id = T2.event_id WHERE T2.app_id = -8022267440849930000 AND T1.event_id = 7