Joining Multiple Tables to Create a Single Row: A Step-by-Step Guide

Combining Rows from Different Tables into a Single Row

In this article, we will explore how to combine rows from different tables into a single row. This is often necessary when dealing with data that has changed over time or when trying to perform complex aggregations.

Introduction

We have two tables: Transactions and Prices. The Transactions table contains information about transactions, such as the transaction number, ID number, price traded, and trade date. The Prices table contains historical prices for each item, including the ID number, theoretical price, and date.

The goal is to combine these rows into a single row, where we can compare the traded price with the theoretical price from that day and the previous day.

Understanding the Problem

Let’s take a closer look at the problem. We want to achieve the following result:

Transaction No	ID No	Price Traded	Trade Date	Price Theo TD	Price Theo TD-1

Here is an example of what the data might look like in our Transactions and Prices tables:

Transactions

Transaction No	ID No	Price Traded	Trade Date
T1	a	10.9	20210720
T2	b	58.7	20210720

Prices

ID No	Price_Theo	Date
a	10.5	20210718
a	10	20210719
a	11	20210720
b	62	20210718
b	59	20210719
b	58	20210720

Solution

To achieve our goal, we can use two joins: one to join the Transactions table with the first instance of prices for each item, and another to join the same transactions with the second instance of prices.

The SQL query would look like this:

SELECT T.Transaction_no, P.ID_no, T.Price_Traded,
       P.Date, P.Price_Theo,
       P1.Date, P1.Price_Theo
FROM Transactions T LEFT JOIN
     Prices P 
     ON P.ID_no = T.ID_no AND
        P.Date = T.Trade_Date LEFT JOIN
     Prices P1
     ON P1.ID_no = T.ID_no AND
        P1.Date = T.Trade_Date - INTERVAL '1' DAY;

Explanation

Let’s break down the query:

The first LEFT JOIN combines rows from the Transactions table with the first instance of prices for each item. This gives us the traded price and trade date.
The second LEFT JOIN combines the same transactions with the second instance of prices, which is one day behind.

By joining these two instances of prices, we can create a new column that contains the theoretical price from both days.

Example Use Case

Suppose we want to analyze the performance of our trading strategy over time. We can use this query to combine the traded prices with the historical prices from the previous day and the previous previous day, allowing us to compare trends and identify patterns.

Conclusion

Combining rows from different tables into a single row is often necessary in data analysis and reporting. By using two joins, we can achieve complex aggregations and create new columns that provide valuable insights into our data.

Last modified on 2025-04-04