LeetCode MySQL-262. Trips and Users

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.

將當天(客戶或司機)取消用戶數除以總取消用戶數，為取消率。
寫一個 SQL Query來尋找「排除被禁止的用戶」中，在"2013-10-01 ~ 2013-10-03"期間的取消率，
且四捨五入取到小數點第二位。
可任意排序結果。

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').

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

Solution:
1. 選擇標題 tb1.request_at 為 DAY。
2. 選擇標題 Cancellation Rate 為「符合’cancelled%’」的平均數，且取小數點到第二位，同時 banned 不能為 Yes。
3. 分別使用兩個 INNER JOIN 來將存在 Users 名單中的客戶或司機進行連結。
4. 確認日期在 “2013-10-01 ~ 2013-10-03” 之間。
5. 以 DAY 為群組及排序。

ex. 使用雙 INNER JOIN 的目的：

Trips table:
+------+-----------+-----------+---------+---------------------+------------+
| id   | client_id | driver_id | city_id | status              | request_at |
+------+-----------+-----------+---------+---------------------+------------+
| 1111 | 1         | 10        | 1       | completed           | 2013-10-01 |
+------+-----------+-----------+---------+---------------------+------------+

Users table:
+----------+--------+--------+
| users_id | banned | role   |
+----------+--------+--------+
| 1        | No     | client |
| 10       | Yes    | driver |
+----------+--------+--------+

ex. 以上例子中，client_id 與 driver_id 分別符合 1 和 10，但是因其中 driver 判定為禁止，故該筆資料應完全排除。

Code.1:

SELECT tb1.request_at AS DAY,
    ROUND(AVG(IF(tb1.status LIKE 'cancelled%', 1, 0)), 2) AS 'Cancellation Rate'
	FROM Trips AS tb1
    INNER JOIN Users AS tb2
        ON tb1.client_id = tb2.users_id AND tb2.banned = 'No'
    INNER JOIN Users AS tb3
        ON tb1.driver_id = tb3.users_id AND tb3.banned = 'No'
WHERE tb1.request_at BETWEEN "2013-10-01" AND "2013-10-03"
GROUP BY Day
ORDER BY Day;