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Polars Cookbook

You're reading from   Polars Cookbook Over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805121152
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Yuki Kakegawa Yuki Kakegawa
Author Profile Icon Yuki Kakegawa
Yuki Kakegawa
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Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Getting Started with Python Polars FREE CHAPTER 2. Chapter 2: Reading and Writing Files 3. Chapter 3: An Introduction to Data Analysis in Python Polars 4. Chapter 4: Data Transformation Techniques 5. Chapter 5: Handling Missing Data 6. Chapter 6: Performing String Manipulations 7. Chapter 7: Working with Nested Data Structures 8. Chapter 8: Reshaping and Tidying Data 9. Chapter 9: Time Series Analysis 10. Chapter 10: Interoperability with Other Python Libraries 11. Chapter 11: Working with Common Cloud Data Sources 12. Chapter 12: Testing and Debugging in Polars 13. Index 14. Other Books You May Enjoy

Inspecting and optimizing the query plan

One feature that Polars provides that tools such as pandas don’t is the ability to inspect the query plan. Lazy evaluation in LazyFrames makes it possible for Polars to optimize the query plan and for us to inspect what it’s trying to do in a query.

In this recipe, we’ll look at how we can inspect and optimize the query plan.

Getting ready

You need the graphviz library installed on your machine to use one of the methods for inspecting the query plan, which is the .show_graph() method. However, the installation process is a bit different than other Python libraries because you need to add a path to graphviz.

On Mac, the easiest way to do all that at once is using Homebrew, a package manager. You just need to run the following and the installation will be complete:

brew install graphviz

If you have a Windows machine or want to know more about the installation process, please refer to this documentation page...

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