Leverage a lightning fast DataFrame library for efficient data wrangling in Python 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. This book is for data analysts, data scientists, and data engineers who want to learn to use Polars in their workflows. You should have working knowledge of the Python programming language. Preferably, you have experience working with a DataFrame library such as pandas or PySpark. If you’re looking to improve your data pipelines or data science/analysis workflows with Python Polars, this book is ideal to get you started and be the guide in your journey.
