Leetcode MEDIUM 2854 - Rolling Average Steps - Using ROWS BETWEEN in SQL | Everyday Data Science скачать в хорошем качестве

Leetcode MEDIUM 2854 - Rolling Average Steps - Using ROWS BETWEEN in SQL | Everyday Data Science

Question: https://leetcode.com/problems/rolling... SQL Schema: Create table if not exists Steps(user_id int, steps_count int, steps_date date) Truncate table Steps insert into Steps (user_id, steps_count, steps_date) values ('1', '687', '2021-09-02') insert into Steps (user_id, steps_count, steps_date) values ('1', '395', '2021-09-04') insert into Steps (user_id, steps_count, steps_date) values ('1', '499', '2021-09-05') insert into Steps (user_id, steps_count, steps_date) values ('1', '712', '2021-09-06') insert into Steps (user_id, steps_count, steps_date) values ('1', '576', '2021-09-07') insert into Steps (user_id, steps_count, steps_date) values ('2', '153', '2021-09-06') insert into Steps (user_id, steps_count, steps_date) values ('2', '171', '2021-09-07') insert into Steps (user_id, steps_count, steps_date) values ('2', '530', '2021-09-08') insert into Steps (user_id, steps_count, steps_date) values ('3', '945', '2021-09-04') insert into Steps (user_id, steps_count, steps_date) values ('3', '120', '2021-09-07') insert into Steps (user_id, steps_count, steps_date) values ('3', '557', '2021-09-08') insert into Steps (user_id, steps_count, steps_date) values ('3', '840', '2021-09-09') insert into Steps (user_id, steps_count, steps_date) values ('3', '627', '2021-09-10') insert into Steps (user_id, steps_count, steps_date) values ('5', '382', '2021-09-05') insert into Steps (user_id, steps_count, steps_date) values ('6', '480', '2021-09-01') insert into Steps (user_id, steps_count, steps_date) values ('6', '191', '2021-09-02') insert into Steps (user_id, steps_count, steps_date) values ('6', '303', '2021-09-05') Pandas Schema: data = [[1, 687, '2021-09-02'], [1, 395, '2021-09-04'], [1, 499, '2021-09-05'], [1, 712, '2021-09-06'], [1, 576, '2021-09-07'], [2, 153, '2021-09-06'], [2, 171, '2021-09-07'], [2, 530, '2021-09-08'], [3, 945, '2021-09-04'], [3, 120, '2021-09-07'], [3, 557, '2021-09-08'], [3, 840, '2021-09-09'], [3, 627, '2021-09-10'], [5, 382, '2021-09-05'], [6, 480, '2021-09-01'], [6, 191, '2021-09-02'], [6, 303, '2021-09-05']] steps = pd.DataFrame(data, columns=['user_id', 'steps_count', 'steps_date']).astype({'user_id':'Int64', 'steps_count':'Int64', 'steps_date':'datetime64[ns]'}) #leetcode #datascience #tutorial