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Polars Cookbook. Over 70 practical recipes to transform, manipulate, and analyze your data using Python Polars - Helion

Polars Cookbook. Over 70 practical recipes to transform, manipulate, and analyze your data using Python Polars
ebook
Autor: Yuki Kakegawa
Tytuł oryginału: Polars Cookbook. Over 70 practical recipes to transform, manipulate, and analyze your data using Python Polars
ISBN: 9781805125150
stron: 114, Format: ebook
Księgarnia: Helion

Cena książki: 139,00 zł

Książka będzie dostępna od grudnia 2023

Polars cookbook is a complete guide that not only helps you get started with Python Polars, but also gives you effective solutions to your day-to-day data problems.
The book begins by teaching you the fundamentals of Polars including its key features, covering essential data operations such as filtering data, selecting columns, and summarising data. It then goes on to teach common data transformations such as aggregations, window functions, and string manipulations. You’ll also discover the ways to handle missing values, work with lists and arrays, and reshape your data. The book gets meaty when you come across chapters teaching you about time series analysis, working with common data sources, and testing and debugging in Polars.
By the end of the book, you will have learned to apply various data transformations in Polars, understanding exactly how to solve common data problems. You unlock the potential of Polars by going through the book, while keeping the practical recipes you can refer to when needed. The book helps you be confident in using Polars to improve your data workflows.

Spis treści

Polars Cookbook. Over 70 practical recipes to transform, manipulate, and analyze your data using Python Polars eBook -- spis treści

  • 1. Getting started with Python Polars
  • 2. Reading and Writing Files
  • 3. Introduction to Data Analysis in Python Polars
  • 4. Data Transformation Techniques
  • 5. Handling Missing Values
  • 6. Performing String Manipulations
  • 7. Working with List and Array Operations
  • 8. Reshaping and tidying data
  • 9. Time Series Analysis
  • 10. Interoperability with other Python Libraries
  • 11. Working with Common Cloud Data Sources
  • 12. Testing and debugging in Polars

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