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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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Toc

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

What this book covers

Chapter 1, Getting Started with Python Polars, introduces you to Polars’ unique features and fundamental operations. This chapter guides you through the basic workings of DataFrames, LazyFrames, Series, and Expressions, getting you started on your journey with Python Polars.

Chapter 2, Reading and Writing Files, teaches you how to read from and write to various types of files and databases.

Chapter 3, An Introduction to Data Analysis in Python Polars, walks you through the application of common data exploration tasks. This includes, but is not limited to, inspecting the data, generating summary statistics, casting data types, removing duplicate values, and visualizing data.

Chapter 4, Data Transformation Techniques, helps you learn to apply aggregations, window functions, and user-defined functions (UDFs) in your data transformation pipelines. This chapter also introduces you how to use SQL in Polars.

Chapter 5, Handling Missing Data, covers ways to identify and handle missing values.

Chapter 6, Performing String Manipulations, helps you develop your skills in manipulating strings using Polars’ built-in methods.

Chapter 7, Working with Nested Data Structures, teaches you how to work with nested data structures such as lists and structs.

Chapter 8, Reshaping and Tidying Data, introduces you to ways to transform your data from a wide format to a long format and vice versa. This chapter also covers how you can combine or concatenate DataFrames.

Chapter 9, Time Series Analysis, focuses on time series analysis techniques such as rolling calculations and resampling methods. You’ll also learn to work with time-related attributes and how to build a simple time series forecasting model.

Chapter 10, Interoperability with Other Python Libraries, covers how Polars can interoperate with other Python libraries such as pandas, NumPy, PyArrow, and DuckDB.

Chapter 11, Working with Common Cloud Data Sources, gets you started on working with popular cloud object storage systems and databases.

Chapter 12, Testing and Debugging in Polars, teaches you how to use Polars’ built-in testing methods/functions and how to debug and troubleshoot your code using libraries such as pytest and cuallee.

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