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"].
Table: Chargebacks
+----------------+---------+ | Column Name | Type | +----------------+---------+ | trans_id | int | | trans_date | date | +----------------+---------+ Chargebacks contains basic information regarding incoming chargebacks from some transactions placed in Transactions table. trans_id is a foreign key to the id column of Transactions table. Each chargeback corresponds to a transaction made previously even if they were not approved.
Write an SQL query to find for each month and country: the number of approved transactions and their total amount, the number of chargebacks, and their total amount.
Note: In your query, given the month and country, ignore rows with all zeros.
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 | +-----+---------+----------+--------+------------+ | 101 | US | approved | 1000 | 2019-05-18 | | 102 | US | declined | 2000 | 2019-05-19 | | 103 | US | approved | 3000 | 2019-06-10 | | 104 | US | declined | 4000 | 2019-06-13 | | 105 | US | approved | 5000 | 2019-06-15 | +-----+---------+----------+--------+------------+ Chargebacks table: +----------+------------+ | trans_id | trans_date | +----------+------------+ | 102 | 2019-05-29 | | 101 | 2019-06-30 | | 105 | 2019-09-18 | +----------+------------+ Output: +---------+---------+----------------+-----------------+------------------+-------------------+ | month | country | approved_count | approved_amount | chargeback_count | chargeback_amount | +---------+---------+----------------+-----------------+------------------+-------------------+ | 2019-05 | US | 1 | 1000 | 1 | 2000 | | 2019-06 | US | 2 | 8000 | 1 | 1000 | | 2019-09 | US | 0 | 0 | 1 | 5000 | +---------+---------+----------------+-----------------+------------------+-------------------+