Filtering and Joining Tables with PostgreSQL

In this article, we will explore how to filter a column twice in SQL to create two different columns, and then join them to the columns of another table. We’ll use Python and PostgreSQL as our database management system.

Understanding the Problem

The problem at hand is to take data from two tables (table_purch1 and table_purch2) that have a common column (purch_date). The goal is to filter this column according to two different time periods (June 1st, 2024 to June 30th, 2024) and create two separate numeric columns: one for the sum of transactions during these dates (june_purch), and another for the total amount of transactions before these dates (bal_june). Finally, we want to join these new columns with the item column to create a single result set that includes all items from both tables.

Background Information

To tackle this problem, we need to understand some fundamental concepts in SQL:

• Filtering: This is used to select rows based on certain conditions. We’ll use filtering to restrict our data to only the transactions within the desired date range.
• Grouping: This groups together rows that meet a specific condition and allows us to perform aggregate operations like summing up values.
• UNION: Used to combine the result of two or more SELECT statements into one output.
• FULL JOIN: A type of join that returns all records from both tables, with NULL values in the columns where there is no match.

The Solution

Here’s a step-by-step breakdown of how we can achieve this:

Step 1: Creating a Common Table Expression (CTE)

We’ll start by creating a CTE named purchases. This will be used to define two separate queries for each table (table_purch1 and table_purch2). Inside the CTE, we’ll use CASE statements to filter transactions based on their dates.

WITH purchases AS (
    SELECT item, purch_date_1 AS purch_date,
           SUM(CASE WHEN purch_date_1 BETWEEN '2024-06-01' AND '2024-06-30' THEN purch_amt_1 ELSE 0 END) AS june_purch,
           SUM(purch_amt_1) AS bal_june
    FROM table_purch1
    WHERE purch_date_1 <= '2024-06-30'
    GROUP BY item, purch_date_1

    UNION ALL

    SELECT item2 AS item, purch_date_2 AS purch_date,
           SUM(CASE WHEN purch_date_2 BETWEEN '2024-06-01' AND '2024-06-30' THEN purch_amt2 ELSE 0 END) AS june_purch,
           SUM(purch_amt2) AS bal_june
    FROM table_purch2
    WHERE purch_date_2 <= '2024-06-30'
    GROUP BY item2, purch_date_2
)

Step 2: Joining the CTE with the Final Result

Next, we’ll use another SELECT statement to join our filtered data from the CTE. We want to sum up the two numeric columns (june_purch and bal_june) for each item.

SELECT item,
       purch_date,
       SUM(june_purch) AS june_purch,
       SUM(bal_june) AS bal_june
FROM purchases
GROUP BY item, purch_date
ORDER BY purch_date;

Example Use Case

We’ll create example tables and data to demonstrate how this solution works:

-- Create the table_purch1 table
CREATE TABLE table_purch1 (
    id SERIAL PRIMARY KEY,
    item VARCHAR(255),
    purch_amt_1 DECIMAL(10, 2),
    purch_date_1 DATE
);

-- Create the table_purch2 table
CREATE TABLE table_purch2 (
    id SERIAL PRIMARY KEY,
    item VARCHAR(255),
    purch_amt2 DECIMAL(10, 2),
    purch_date_2 DATE
);

-- Insert sample data into both tables

INSERT INTO table_purch1 (item, purch_amt_1, purch_date_1)
VALUES 
('A', 100.00, '2024-05-16'),
('B', 150.00, '2024-06-05'),
('C', 200.00, '2024-06-11');

INSERT INTO table_purch2 (item, purch_amt2, purch_date_2)
VALUES 
('A', 100.00, '2024-05-16'),
('B', 150.00, '2024-06-05'),
('D', 200.00, '2024-06-12');

-- Now you can run the SQL query to get the desired result

Explanation

In this solution, we’re using a CTE to define two separate queries for each table (table_purch1 and table_purch2). Inside these CTEs, we use CASE statements to filter transactions based on their dates.

The first part of the query filters purch_date_1 values to only include those within the range of June 1st, 2024 to June 30th, 2024. It then sums up the corresponding transaction amounts (purch_amt_1) and calculates a running total (bal_june).

Similarly, for table_purch2, we filter purch_date_2 values based on this date range and perform the same calculations.

The final part of our query joins these two CTEs together using an outer join. We then sum up the transaction amounts from each table to get the desired result.

Note that in PostgreSQL, you can use BETWEEN operator for filtering transactions but it doesn’t support inclusive ranges, so we need to manually include values at both ends of the range (<=) and make sure data is sorted correctly.

Last modified on 2024-10-14