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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

Reading and writing JSON files

JavaScript Object Notation (JSON) is an open source file format used to store and transport data. It can easily be parsed into a JavaScript object. JSON is language independent and is used in projects with other programming languages that require a lightweight data exchange format. JSON stores and represents data as key-value pairs. In Python terms, JSON is very much like data that is stored in Python dictionaries.

In this recipe, we’ll cover how to read and write JSON files in Polars. We’ll also cover how to work with a different variation of JSON: Newline Delimited JSON (NDJSON). It is also called JSON Lines (JSONL) or Line-Delimited JSON (LDJSON). As the name suggests, each line is a JSON object.

How to do it...

Next, we’ll dive into how to work with JSON files in Polars:

  1. Read a JSON file, showing the first 10 columns:
    df = pl.read_json('../data/world_population.json')
    df.select(df.columns[:10]).head(...
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