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# Trips and Users LeetCode Solution

## Problem – Trips and Users LeetCode Solution

SQL Schema

Table: Trips

+-------------+----------+
| Column Name | Type     |
+-------------+----------+
| id          | int      |
| client_id   | int      |
| driver_id   | int      |
| city_id     | int      |
| status      | enum     |
| request_at  | date     |
+-------------+----------+
id is the primary key 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 type of ('completed', 'cancelled_by_driver', 'cancelled_by_client').

Table: Users

+-------------+----------+
| Column Name | Type     |
+-------------+----------+
| users_id    | int      |
| banned      | enum     |
| role        | enum     |
+-------------+----------+
users_id is the primary key 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 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 SQL query 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 query result format is in the following example.

Example 1:

Input:
Trips table:
+----+-----------+-----------+---------+---------------------+------------+
| 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_client | 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        | 12      | cancelled_by_driver | 2013-10-03 |
+----+-----------+-----------+---------+---------------------+------------+
Users table:
+----------+--------+--------+
| 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 |
+----------+--------+--------+
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

## Trips and Users LeetCode Solution in MySQL

SELECT      request_at AS "Day",
ROUND(((SUM(CASE WHEN LOWER(Status) LIKE "cancelled%" THEN 1.000 ELSE 0 END)) / COUNT(id)), 2) AS "Cancellation Rate"
FROM        trips AS t
JOIN        users AS u
ON          t.client_id = u.users_id
AND         u.banned ='No'
WHERE       request_at BETWEEN '2013-10-01' AND '2013-10-03'
GROUP BY    request_at;

## Trips and Users LeetCode Solution in MS SQL Server

select
Request_at AS Day
,cast(round(SUM(case when Status like 'cancelled%' then 1 else 0 end) * 1.0 / count(*), 2) as float) AS 'Cancellation Rate'
from Trips
where
Request_at <= '2013-10-03'
and Client_Id not in (select Users_Id from Users where Banned = 'Yes')
and Driver_Id not in (select Users_Id from Users where Banned = 'Yes')
group by
Request_at

## Trips and Users LeetCode Solution in Oracle

with tr As (
select t.id,t.request_at,t.status
from Trips t Inner Join Users cl On t.client_id=cl.users_id and cl.banned='No' and cl.role='client'
dr.role='driver'
where
to_date(t.request_at,'YYYY-MM-DD') between to_date('20131001','YYYYMMDD') and to_date('20131003','YYYYMMDD')
)
,tr_all As (
select request_at,count(id) As cnt
from tr
group by request_at
)
,tr_cancel As (
select request_at,count(id) As cnt
from tr
where status in ('cancelled_by_driver','cancelled_by_client')
group by request_at
)
select a.request_at As "Day",Round(coalesce(c.cnt,0)/a.cnt,2) As "Cancellation Rate"
from tr_all a Left Join tr_cancel c On a.request_at=c.request_at
order by a.request_at
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