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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

An Introduction to Data Analysis in Python Polars

Data analysis is a broad term that encompasses various steps of inspecting, transforming, and understanding data in order to uncover valuable insights. This chapter focuses on teaching you the fundamentals of data analysis in Python Polars while exploring the dataset. You’ll learn how to inspect your data, generate its summary statistics, adjust data types to suit your needs, and clean the data for further analysis.

In this chapter, we’re going to cover the following main topics:

  • Inspecting the DataFrame
  • Casting data types
  • Handling duplicate values
  • Masking sensitive data
  • Visualizing data using Plotly
  • Detecting and handling outliers
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