Last updated on October 9th, 2024 at 09:59 pm
This Leetcode problem Trips and Users LeetCode Solution is done in SQL.
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Level of Question
Hard
Trips and Users LeetCode Solution
Table of Contents
Problem Statement
Column Name | Type |
id | int |
client_id | int |
driver_id | int |
city_id | int |
status | enum |
request_at | date |
id is the primary key (column with unique values) for this table. The table holds all taxi trips. Each trip has a unique id, while client_id and driver_id are foreign keys to the users_id at the Users table. Status is an ENUM (category) type of (‘completed’, ‘cancelled_by_driver’, ‘cancelled_by_client’).
Column Name | Type |
users_id | int |
banned | enum |
role | enum |
Users
users_id is the primary key (column with unique values) for this table. The table holds all users. Each user has a unique users_id, and role is an ENUM type of (‘client’, ‘driver’, ‘partner’). banned is an ENUM (category) type of (‘Yes’, ‘No’).
The cancellation rate is computed by dividing the number of canceled (by client or driver) requests with unbanned users by the total number of requests with unbanned users on that day.
Write a solution to find the cancellation rate of requests with unbanned users (both client and driver must not be banned) each day between "2013-10-01"
and "2013-10-03"
. Round Cancellation Rate
to two decimal points.
Return the result table in any order.
The result format is in the following example.
Example 1:
Input:
users_id | banned | role |
1 | No | client |
2 | Yes | client |
3 | No | client |
4 | No | client |
10 | No | driver |
11 | No | driver |
12 | No | driver |
13 | No | driver |
id | client_id | driver_id | city_id | status | request_at |
1 | 1 | 10 | 1 | completed | 2013-10-01 |
2 | 2 | 11 | 1 | cancelled_by_driver | 2013-10-01 |
3 | 3 | 12 | 6 | completed | 2013-10-01 |
4 | 4 | 13 | 6 | cancelled_by_driver | 2013-10-01 |
5 | 1 | 10 | 1 | completed | 2013-10-02 |
6 | 2 | 11 | 6 | completed | 2013-10-02 |
7 | 3 | 12 | 6 | completed | 2013-10-02 |
8 | 2 | 12 | 12 | completed | 2013-10-03 |
9 | 3 | 10 | 12 | completed | 2013-10-03 |
10 | 4 | 13 | 13 | cancelled_by_driver | 2013-10-03 |
Output:
Day | Cancellation Rate |
2013-10-01 | 0.33 |
2013-10-02 | 0.00 |
2013-10-03 | 0.50 |
Explanation:
On 2013-10-01:
– There were 4 requests in total, 2 of which were canceled.
– However, the request with Id=2 was made by a banned client (User_Id=2), so it is ignored in the calculation.
– Hence there are 3 unbanned requests in total, 1 of which was canceled.
– The Cancellation Rate is (1 / 3) = 0.33
On 2013-10-02:
– There were 3 requests in total, 0 of which were canceled.
– The request with Id=6 was made by a banned client, so it is ignored.
– Hence there are 2 unbanned requests in total, 0 of which were canceled.
– The Cancellation Rate is (0 / 2) = 0.00
On 2013-10-03:
– There were 3 requests in total, 1 of which was canceled.
– The request with Id=8 was made by a banned client, so it is ignored.
– Hence there are 2 unbanned request in total, 1 of which were canceled.
– The Cancellation Rate is (1 / 2) = 0.50
1. Trips and Users LeetCode Solution MySQL
with stats as ( select Request_at, T.Status <> 'completed' as IsCancelled from Trips T join Users C on (Client_Id = C.Users_Id and C.Banned = 'No') join Users D on (Driver_Id = D.Users_Id and D.Banned = 'No') where Request_at between '2013-10-01' and '2013-10-03' ) select Request_at as Day, Round( cast(sum(IsCancelled) as real) / cast(count(*) as real), 2 ) as 'Cancellation Rate' from stats group by Request_at ;
2. Trips and Users LeetCode Solution Pandas
import pandas as pd def trips_and_users(trips: pd.DataFrame, users: pd.DataFrame) -> pd.DataFrame: users = users[users.banned == 'No'] trips = trips[trips.request_at .between('2013-10-01','2013-10-03') ].rename(columns = {'request_at': 'Day'}) trips['can'] = trips.status.str.startswith('can') trips = trips[(trips.client_id.isin(users.users_id)) & (trips.driver_id.isin(users.users_id)) ].groupby('Day')['can'].agg(['sum','size']).reset_index() trips['Cancellation Rate'] = (trips['sum']/trips['size']).round(2) return trips[['Day','Cancellation Rate']]