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Monthly Transactions II

Problem

Table: Transactions

+----------------+---------+
| Column Name    | Type    |
+----------------+---------+
| id             | int     |
| country        | varchar |
| state          | enum    |
| amount         | int     |
| trans_date     | date    |
+----------------+---------+
id is the column of unique values of this table.
The table has information about incoming transactions.
The state column is an ENUM (category) 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 (reference column) to the id column of Transactions table.
Each chargeback corresponds to a transaction made previously even if they were not approved.

Problem Definition

Write a solution to the number of approved transactions and their total amount, the number of chargebacks, and their total amount find for each month and country. Return the records in the order of date.

Note: In your solution, given the month and country, ignore rows with all zeros.

Example

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Output

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Try It Yourself

java
-- TODO: Write your user queries here

Solution

To determine the number of approved transactions and their total amount, the number of chargebacks and their total amount for each month and country, we can follow a structured approach that leverages SQL's aggregation and conditional functions. This ensures accurate and efficient computation by combining relevant data from the Transactions and Chargebacks tables.

SQL Query

SELECT month,
       country,
       Sum(CASE
             WHEN state = "approved" THEN 1
             ELSE 0
           END) AS approved_count,
       Sum(CASE
             WHEN state = "approved" THEN amount
             ELSE 0
           END) AS approved_amount,
       Sum(CASE
             WHEN state = "back" THEN 1
             ELSE 0
           END) AS chargeback_count,
       Sum(CASE
             WHEN state = "back" THEN amount
             ELSE 0
           END) AS chargeback_amount
FROM   (SELECT LEFT(Chargebacks.trans_date, 7) AS month,
               country,
               "back"                          AS state,
               amount
        FROM   Chargebacks
               JOIN Transactions
                 ON Chargebacks.trans_id = Transactions.id
        UNION ALL
        SELECT LEFT(trans_date, 7) AS month,
               country,
               state,
               amount
        FROM   Transactions
        WHERE  state = "approved") s
GROUP  BY month,
          country
HAVING approved_count > 0 OR chargeback_count > 0
ORDER BY month;

Step-by-Step Approach

Step 1: Combine Chargebacks with Approved Transactions

Merge the Chargebacks and Transactions tables to create a unified dataset that distinguishes chargebacks from approved transactions. This involves labeling chargebacks with a unique state identifier and ensuring that only approved transactions are included from the Transactions table.

SQL Query:

SELECT LEFT(Chargebacks.trans_date, 7) AS month,
       country,
       "back"                          AS state,
       amount
FROM   Chargebacks
       JOIN Transactions
         ON Chargebacks.trans_id = Transactions.id
UNION ALL
SELECT LEFT(trans_date, 7) AS month,
       country,
       state,
       amount
FROM   Transactions
WHERE  state = "approved";

Explanation:

Output After Step 1:

Based on the provided input data, the combined dataset (s) will be:

monthcountrystateamount
2019-05USback2000
2019-06USback1000
2019-09USback5000
2019-05USapproved1000
2019-06USapproved3000
2019-06USapproved5000

Explanation of Output:

Step 2: Aggregate Data by Month and Country

For each combination of month and country, calculate:

SQL Query:

SELECT month,
       country,
       Sum(CASE
             WHEN state = "approved" THEN 1
             ELSE 0
           END) AS approved_count,
       Sum(CASE
             WHEN state = "approved" THEN amount
             ELSE 0
           END) AS approved_amount,
       Sum(CASE
             WHEN state = "back" THEN 1
             ELSE 0
           END) AS chargeback_count,
       Sum(CASE
             WHEN state = "back" THEN amount
             ELSE 0
           END) AS chargeback_amount
FROM   (
        -- Combined Data from Step 1
        SELECT LEFT(Chargebacks.trans_date, 7) AS month,
               country,
               "back"                          AS state,
               amount
        FROM   Chargebacks
               JOIN Transactions
                 ON Chargebacks.trans_id = Transactions.id
        UNION ALL
        SELECT LEFT(trans_date, 7) AS month,
               country,
               state,
               amount
        FROM   Transactions
        WHERE  state = "approved"
       ) s
GROUP  BY month,
          country
HAVING approved_count > 0 OR chargeback_count > 0
ORDER BY month;

Explanation:

Output After Step 2:

Based on the combined dataset from Step 1, the aggregation would yield:

monthcountryapproved_countapproved_amountchargeback_countchargeback_amount
2019-06US2800011000
2019-05US1100012000
2019-09US0015000

Explanation of Output:

Note:

Step 3: Order the Results by Month

Ensure that the final output is sorted in chronological order based on the month to provide a clear and organized view of the data over time.

SQL Query:

ORDER BY month;

Explanation:

Final Output:

Based on the aggregated data from Step 2, the final output after ordering would be:

monthcountryapproved_countapproved_amountchargeback_countchargeback_amount
2019-05US1100012000
2019-06US2800011000
2019-09US0015000

Explanation of Output:

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