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64 lines
3.0 KiB
HTML
64 lines
3.0 KiB
HTML
<p>Table: <code>Customer</code></p>
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<pre>
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+---------------+---------+
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| Column Name | Type |
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+---------------+---------+
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| customer_id | int |
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| name | varchar |
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| visited_on | date |
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| amount | int |
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+---------------+---------+
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In SQL,(customer_id, visited_on) is the primary key for this table.
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This table contains data about customer transactions in a restaurant.
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visited_on is the date on which the customer with ID (customer_id) has visited the restaurant.
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amount is the total paid by a customer.
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</pre>
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<p> </p>
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<p>You are the restaurant owner and you want to analyze a possible expansion (there will be at least one customer every day).</p>
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<p>Compute the moving average of how much the customer paid in a seven days window (i.e., current day + 6 days before). <code>average_amount</code> should be <strong>rounded to two decimal places</strong>.</p>
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<p>Return the result table ordered by <code>visited_on</code> <strong>in ascending order</strong>.</p>
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<p>The result format is in the following example.</p>
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<p> </p>
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<p><strong class="example">Example 1:</strong></p>
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<pre>
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<strong>Input:</strong>
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Customer table:
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+-------------+--------------+--------------+-------------+
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| customer_id | name | visited_on | amount |
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+-------------+--------------+--------------+-------------+
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| 1 | Jhon | 2019-01-01 | 100 |
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| 2 | Daniel | 2019-01-02 | 110 |
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| 3 | Jade | 2019-01-03 | 120 |
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| 4 | Khaled | 2019-01-04 | 130 |
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| 5 | Winston | 2019-01-05 | 110 |
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| 6 | Elvis | 2019-01-06 | 140 |
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| 7 | Anna | 2019-01-07 | 150 |
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| 8 | Maria | 2019-01-08 | 80 |
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| 9 | Jaze | 2019-01-09 | 110 |
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| 1 | Jhon | 2019-01-10 | 130 |
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| 3 | Jade | 2019-01-10 | 150 |
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+-------------+--------------+--------------+-------------+
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<strong>Output:</strong>
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+--------------+--------------+----------------+
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| visited_on | amount | average_amount |
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+--------------+--------------+----------------+
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| 2019-01-07 | 860 | 122.86 |
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| 2019-01-08 | 840 | 120 |
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| 2019-01-09 | 840 | 120 |
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| 2019-01-10 | 1000 | 142.86 |
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+--------------+--------------+----------------+
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<strong>Explanation:</strong>
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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
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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
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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
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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
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</pre>
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