1321. Restaurant Growth

Table: Customer

+----------------+---------+
| Column Name    | Type    |
+----------------+---------+
| customer_id    | int     |
| name           | varchar |
| visited_on     | date    |
| amount         | int     |
+----------------+---------+
(customer_id, visited_on) is the primary key for this table.
This table contains data about customer transactions in a restaurant.
visited_on is the date on which the customer with ID (customer_id) has visited the restaurant.
amount is the total paid by a customer.

You are the restaurant owner and you want to analyse a possible expansion (there will be at least one customer every day).

Write an SQL query to compute the moving average of how much the customer paid in a seven days window (i.e., current day + 6 days before). average_amount should be rounded to two decimal places.

Return result table ordered by visited_on in ascending order.

The query result format is in the following example.

Example 1:

Customer table:
+-------------+-----------+------------+---------+
| customer_id | name      | visited_on | amount  |
+-------------+-----------+------------+---------+
| 1           | Jhon      | 2019-01-01 | 100     |
| 2           | Daniel    | 2019-01-02 | 110     |
| 3           | Jade      | 2019-01-03 | 120     |
| 4           | Khaled    | 2019-01-04 | 130     |
| 5           | Winston   | 2019-01-05 | 110     |
| 6           | Elvis     | 2019-01-06 | 140     |
| 7           | Anna      | 2019-01-07 | 150     |
| 8           | Maria     | 2019-01-08 | 80      |
| 9           | Jaze      | 2019-01-09 | 110     |
| 1           | Jhon      | 2019-01-10 | 130     |
| 3           | Jade      | 2019-01-10 | 150     |
+-------------+-----------+------------+---------+

Output:
+-------------+----------+----------------+
| visited_on  | amount   | average_amount |
+-------------+----------+----------------+
| 2019-01-07  | 860      | 122.86         |
| 2019-01-08  | 840      | 120            |
| 2019-01-09  | 840      | 120            |
| 2019-01-10  | 1000     | 142.86         |
+-------------+----------+----------------+

Explanation:
1st moving average from 2019-01-01 to 2019-01-07 has an average_amount of (100 + 110 +
120 + 130 + 110 + 140 + 150)/7 = 122.86
2nd moving average from 2019-01-02 to 2019-01-08 has an average_amount of (110 + 120 +
130 + 110 + 140 + 150 + 80)/7 = 120
3rd moving average from 2019-01-03 to 2019-01-09 has an average_amount of (120 + 130 +
110 + 140 + 150 + 80 + 110)/7 = 120
4th moving average from 2019-01-04 to 2019-01-10 has an average_amount of (130 + 110 +
140 + 150 + 80 + 110 + 130 + 150)/7 = 142.86

Refer to 1321-Restaurant-Growth.sql for my solution.