Скачать или смотреть Leetcode HARD 1892 - Page Recommendations 2 : Using JOINs to FILTER TABLES - Explained by EDS

Question: https://leetcode.com/problems/page-re...

SQL Schema:
Create table If Not Exists Friendship (user1_id int, user2_id int)
Create table If Not Exists Likes (user_id int, page_id int)
Truncate table Friendship
insert into Friendship (user1_id, user2_id) values ('1', '2')
insert into Friendship (user1_id, user2_id) values ('1', '3')
insert into Friendship (user1_id, user2_id) values ('1', '4')
insert into Friendship (user1_id, user2_id) values ('2', '3')
insert into Friendship (user1_id, user2_id) values ('2', '4')
insert into Friendship (user1_id, user2_id) values ('2', '5')
insert into Friendship (user1_id, user2_id) values ('6', '1')
Truncate table Likes
insert into Likes (user_id, page_id) values ('1', '88')
insert into Likes (user_id, page_id) values ('2', '23')
insert into Likes (user_id, page_id) values ('3', '24')
insert into Likes (user_id, page_id) values ('4', '56')
insert into Likes (user_id, page_id) values ('5', '11')
insert into Likes (user_id, page_id) values ('6', '33')
insert into Likes (user_id, page_id) values ('2', '77')
insert into Likes (user_id, page_id) values ('3', '77')
insert into Likes (user_id, page_id) values ('6', '88')

Pandas Schema:
data = [[1, 2], [1, 3], [1, 4], [2, 3], [2, 4], [2, 5], [6, 1]]
friendship = pd.DataFrame(data, columns=['user1_id', 'user2_id']).astype({'user1_id':'Int64', 'user2_id':'Int64'})
data = [[1, 88], [2, 23], [3, 24], [4, 56], [5, 11], [6, 33], [2, 77], [3, 77], [6, 88]]
likes = pd.DataFrame(data, columns=['user_id', 'page_id']).astype({'user_id':'Int64', 'page_id':'Int64'})

#leetcodesolutions #datascience #sql