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Merge pull request #47 from iamAntimPal/Branch-1
1484. Group Sold Products By The Date
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1484. Group Sold Products By The Date
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Solved
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Easy
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Topics
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Companies
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SQL Schema
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Pandas Schema
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Table Activities:
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+-------------+---------+
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| Column Name | Type |
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+-------------+---------+
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| sell_date | date |
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| product | varchar |
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+-------------+---------+
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There is no primary key (column with unique values) for this table. It may contain duplicates.
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Each row of this table contains the product name and the date it was sold in a market.
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Write a solution to find for each date the number of different products sold and their names.
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The sold products names for each date should be sorted lexicographically.
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Return the result table ordered by sell_date.
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The result format is in the following example.
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Example 1:
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Input:
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Activities table:
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+------------+------------+
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| sell_date | product |
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+------------+------------+
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| 2020-05-30 | Headphone |
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| 2020-06-01 | Pencil |
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| 2020-06-02 | Mask |
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| 2020-05-30 | Basketball |
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| 2020-06-01 | Bible |
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| 2020-06-02 | Mask |
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| 2020-05-30 | T-Shirt |
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+------------+------------+
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Output:
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+------------+----------+------------------------------+
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| sell_date | num_sold | products |
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+------------+----------+------------------------------+
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| 2020-05-30 | 3 | Basketball,Headphone,T-shirt |
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| 2020-06-01 | 2 | Bible,Pencil |
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| 2020-06-02 | 1 | Mask |
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+------------+----------+------------------------------+
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Explanation:
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For 2020-05-30, Sold items were (Headphone, Basketball, T-shirt), we sort them lexicographically and separate them by a comma.
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For 2020-06-01, Sold items were (Pencil, Bible), we sort them lexicographically and separate them by a comma.
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For 2020-06-02, the Sold item is (Mask), we just return it.
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select sell_date, count( DISTINCT product ) as num_sold ,
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GROUP_CONCAT( DISTINCT product order by product ASC separator ',' ) as products
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FROM Activities GROUP BY sell_date order by sell_date ASC;

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