## Algorithm

Problem Name: 262. Trips and Users

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

## Code Examples

### #1 Code Example with SQL

Code - SQL

# Write your MySQL query statement below
SELECT Request_at as Day,
ROUND(SUM(CASE WHEN Status LIKE 'cancelled%' THEN 1 ELSE 0 END) / COUNT(*), 2) as "Cancellation Rate"
FROM(
SELECT * FROM Trips t
WHERE
t.Client_Id not in (select Users_Id from Users where Banned = 'Yes') AND
t.Driver_Id not in (select Users_Id from Users where Banned = 'Yes') AND
t.Request_at between '2013-10-01' and '2013-10-03'
) AS newT
GROUP BY Request_at
Copy The Code &

Input

cmd
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

cmd
+------------+-------------------+ | Day | Cancellation Rate | +------------+-------------------+ | 2013-10-01 | 0.33 | | 2013-10-02 | 0.00 | | 2013-10-03 | 0.50 | +------------+-------------------+
Advertisements