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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

Interoperability with Other Python Libraries

Although Polars is an awesome tool that’s fast and efficient, there are times when interoperating with other tools or libraries is crucial in your data projects. The good news is that there are libraries out there already that can work with Polars. In Chapter 9, Time Series Analysis, you‘ve already seen that it works well with the functime and plotly libraries. Polars can also work with other Python libraries such as pandas, NumPy, PyArrow, and DuckDB to name a few. As Polars matures more as a tool, there will be more libraries and tools, making the integration and interoperability between Polars and the whole Python data ecosystem more seamless. For instance, having a seamless integration with other Python libraries benefits Polars by providing functionalities it doesn’t yet have. It’ll give you more options for how you implement your solution.

By the end of this chapter, you’ll gain an understanding...

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