Transforming SQL Data with Pivot Queries: How to Restructure Your Database Tables

Learn how to restructure your SQL database tables using pivot queries to combine multiple rows into single rows based on specific columns.
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This video is based on the question https://stackoverflow.com/q/65515738/ asked by the user 'SYAHRIL ASIDIQ FIRDAUS' ( https://stackoverflow.com/u/14916412/ ) and on the answer https://stackoverflow.com/a/65515799/ provided by the user 'Tim Biegeleisen' ( https://stackoverflow.com/u/1863229/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Transforming SQL Data with Pivot Queries: How to Restructure Your Database Tables

Working with databases often involves complex queries to extract and manipulate data. In this guide, we will tackle a common challenge in SQL: how to transform a table's row data into a more structured format using pivot queries.

Understanding the Problem

Suppose you have a database table with the following structure:

[[See Video to Reveal this Text or Code Snippet]]

In this table, we have names associated with days and two value columns. However, you want to transform this structure so that each combination of Day and Value becomes a distinct column. The desired output should look like this:

[[See Video to Reveal this Text or Code Snippet]]

The Solution: Using a Pivot Query

To achieve this restructuring, you can utilize a SQL pivot query. This technique allows you to summarize and transform data, making it easier to analyze.

Step-by-Step Explanation of the Query

Here’s how to write a pivot query for this case:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Query

SELECT Statement: This is where you specify the data you want to retrieve. We select Name and create new columns for each value pair based on the conditions provided.

CASE Statement:

We use the CASE statement to determine which Day corresponds to each value. For example:

MAX(CASE WHEN DAY = 'mon' THEN VALUE1 END) returns the value of VALUE1 for Mondays.

Similar logic applies for VALUE2 on Mondays and both VALUE1 and VALUE2 for Fridays.

MAX Function:

The MAX function is used here as an aggregation function. Since we only expect one result per Name per Day, it helps extract the required value.

GROUP BY: This clause ensures that the results are grouped by Name, providing a single row output for each name with their corresponding values.

Executing Your Query

To execute the provided query, replace yourTable with the actual name of your table in the database. This simple adjustment allows you to generate the desired output effectively.

Conclusion

Using pivot queries in SQL is a powerful method to reshape your data into a more usable format. With just a few lines of code, you can combine multiple rows into a single row while maintaining clarity and accessibility of your data.

With the above example, you should now be able to tackle similar data restructuring tasks in your own databases. Happy querying!

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