+---------------+---------+
| 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) have visited the restaurant.
amount is the total paid by a customer.
You are the restaurant owner and you want to analyze a possible expansion (there will be at least one customer every day).
Write an SQL query to compute moving average of how much customer paid in a 7 days window (current day + 6 days before) .
The query result format is in the following example:
Return result table ordered by visited_on.
average_amountshould be rounded to 2 decimal places, all dates are in the format ('YYYY-MM-DD').
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 |
+-------------+--------------+--------------+-------------+
Result table:
+--------------+--------------+----------------+
| 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 |
+--------------+--------------+----------------+
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