[leetcode][sql]filtering&aggregation. 월별 거래1
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Q3. Monthly Transactions I
Medium
Topics
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Companies
SQL Schema
Pandas Schema
Table: Transactions
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| id | int |
| country | varchar |
| state | enum |
| amount | int |
| trans_date | date |
+---------------+---------+
id is the primary key of this table.
The table has information about incoming transactions.
The state column is an enum of type ["approved", "declined"].
Write an SQL query to find for each month and country, the number of transactions and their total amount, the number of approved transactions and their total amount.
Return the result table in any order.
The query result format is in the following example.
Example 1:
Input:
Transactions table:
+------+---------+----------+--------+------------+
| id | country | state | amount | trans_date |
+------+---------+----------+--------+------------+
| 121 | US | approved | 1000 | 2018-12-18 |
| 122 | US | declined | 2000 | 2018-12-19 |
| 123 | US | approved | 2000 | 2019-01-01 |
| 124 | DE | approved | 2000 | 2019-01-07 |
+------+---------+----------+--------+------------+
Output:
+----------+---------+-------------+----------------+--------------------+-----------------------+
| month | country | trans_count | approved_count | trans_total_amount | approved_total_amount |
+----------+---------+-------------+----------------+--------------------+-----------------------+
| 2018-12 | US | 2 | 1 | 3000 | 1000 |
| 2019-01 | US | 1 | 1 | 2000 | 2000 |
| 2019-01 | DE | 1 | 1 | 2000 | 2000 |
+----------+---------+-------------+----------------+--------------------+-----------------------+
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# Write your MySQL query statement below
# 조건
# GROUP BY(month), GROUP BY(country)
SELECT
DATE_FORMAT(trans_date, '%Y-%m') AS month,
country,
COUNT(*) AS trans_count,
SUM(CASE WHEN state = 'approved' THEN 1 ELSE 0 END) AS approved_count,
SUM(amount) AS trans_total_amount,
SUM(CASE WHEN state = 'approved' THEN amount ELSE 0 END) AS approved_total_amount
FROM Transactions
GROUP BY DATE_FORMAT(trans_date, '%Y-%m'), country;
#leetcode #groupby #월별거래 #DATE_FORMAT
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