Here, We see Friend Requests II: Who Has the Most Friends LeetCode Solution. This Leetcode problem is done in many programming languages like C++, Java, JavaScript, Python, etc. with different approaches.
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Friend Requests II: Who Has the Most Friends LeetCode Solution
Table of Contents
Problem Statement
Column Name | Type |
requester_id | int |
accepter_id | int |
accept_date | date |
(requester_id, accepter_id) is the primary key (combination of columns with unique values) for this table. This table contains the ID of the user who sent the request, the ID of the user who received the request, and the date when the request was accepted.
Write a solution to find the people who have the most friends and the most friends number.
The test cases are generated so that only one person has the most friends.
The result format is in the following example.
Example 1:
Input:
requester_id | accepter_id | accept_date |
1 | 2 | 2016/06/03 |
1 | 3 | 2016/06/08 |
2 | 3 | 2016/06/08 |
3 | 4 | 2016/06/09 |
Output:
id | num |
3 | 3 |
Explanation: The person with id 3 is a friend of people 1, 2, and 4, so he has three friends in total, which is the most number than any others.
Friend Requests II: Who Has the Most Friends LeetCode Solution MySQL
with base as(
select
requester_id id
from
RequestAccepted
union all
select
accepter_id id
from
RequestAccepted
)
select
id,
count(*) num
from
base
group by
1
order by
2 desc
limit
1
Code language: JavaScript (javascript)
Friend Requests II: Who Has the Most Friends LeetCode Solution Pandas
import pandas as pd
def most_friends(request_accepted: pd.DataFrame) -> pd.DataFrame:
req = request_accepted.requester_id.value_counts().reset_index().rename(columns ={'requester_id':'id'})
acc = request_accepted.accepter_id.value_counts().reset_index().rename(columns ={'accepter_id':'id'})
df = req.merge(acc, on ='id', how ='outer', suffixes=('_req','_acc')).fillna(0)
return df.assign(num = df.count_req + df.count_acc)[['id','num']].query('num == num.max()')
Code language: JavaScript (javascript)