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leetcode-SQL-1193. 每月交易 I

中间件小哥 2022-04-25 阅读 134

leetcode-SQL-1193. 每月交易 I

题目

题目链接
Table: Transactions

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| id            | int     |
| country       | varchar |
| state         | enum    |
| amount        | int     |
| trans_date    | date    |
+---------------+---------+
id 是这个表的主键。
该表包含有关传入事务的信息。
state 列类型为 “[”批准“,”拒绝“] 之一。

编写一个 sql 查询来查找每个月和每个国家/地区的事务数及其总金额、已批准的事务数及其总金额。

以 任意顺序 返回结果表。

查询结果格式如下所示。

示例 1:

输入:
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 |
+------+---------+----------+--------+------------+
输出:
+----------+---------+-------------+----------------+--------------------+-----------------------+
| 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                  |
+----------+---------+-------------+----------------+--------------------+-----------------------+

解题

注意按月分组,不是按照日期
date_format(trans_date,'%Y-%m')可以替换成substr(trans_date,1,7)

count(if(state='approved',1,null))一定要是null,而不能是0,还可以使用sum(if(state='approved',1,0))替换

select
    date_format(trans_date,'%Y-%m') as month,
    country,
    count(amount) as trans_count,
    count(if(state='approved',1,null)) as approved_count,
    sum(amount) as trans_total_amount,
    sum(if(state='approved',amount,0)) as approved_total_amount
from Transactions
group by month,country
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