How to Pivot/Stack Tables in SQL

Описание: Discover how to transform your SQL tables through pivoting and stacking. Learn the steps to convert your garden data into a user-friendly format.
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This video is based on the question https://stackoverflow.com/q/66218356/ asked by the user 'Pedro Cintra' ( https://stackoverflow.com/u/12694785/ ) and on the answer https://stackoverflow.com/a/66225209/ provided by the user 'Gordon Linoff' ( https://stackoverflow.com/u/1144035/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Pivot/Stack Tables in SQL: A Comprehensive Guide

In the world of data analysis, the ability to manipulate tables efficiently and effectively is crucial. One common challenge that analysts face is pivoting or stacking tables, especially when dealing with multiple columns of data. This article will guide you through how to pivot/stack tables in SQL using a practical example.

Understanding the Problem

Let's imagine that you have a SQL table presenting various fruits within different gardens:

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Your goal is to convert this table so that for every unique fruit, you generate a new column for each garden. If a fruit is present in a garden, it will return 1; if not, it will return 0. This is what the expected output would look like:

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The Solution: Unpivoting and Aggregating

To achieve this transformation, you can use SQL's UNION ALL strategy followed by aggregation. This approach allows you to unpivot your current garden table into a more analytical format.

Step 1: Unpivot with UNION ALL

The first step is to unpivot the data using UNION ALL. Here’s how you can write the SQL query:

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Explanation of the Query

Selecting Fruits: Each SELECT statement pulls the fruits from one garden while creating columns for the other gardens initialized with 0.

UNION ALL: This part of the query merges all three SELECT statements into one set, effectively stacking the garden data on top of one another under a single column called fruit.

Aggregation: After unpivoting, the GROUP BY statement groups all records by the unique fruit names. The SUM function calculates how many times each fruit appears in each garden.

Result

Running this query will yield a new table in line with your expectations, presenting a clear view of which gardens contain which fruits.

Conclusion

Manipulating tables through SQL can seem daunting at first, but by using techniques like UNION ALL and aggregation, you can easily pivot and stack your data into a more meaningful format. This not only makes it more readable but provides a better foundation for analysis.

With practice, you can apply these techniques to a variety of data transformation needs, paving the way for easier and more efficient analysis in your data-driven projects.

If you have any questions or need further assistance, feel free to leave a comment below!