Python Polars: The Definitive Guide
Jeroen Janssens, Thijs Nieuwdorp
Sold by Rarewaves USA United, OSWEGO, IL, U.S.A.
AbeBooks Seller since 20 June 2025
New - Soft cover
Condition: New
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Quantity: Over 20 available
Add to basketSold by Rarewaves USA United, OSWEGO, IL, U.S.A.
AbeBooks Seller since 20 June 2025
Condition: New
Quantity: Over 20 available
Add to basketWant to speed up your data analysis and work with larger-than-memory datasets? Python Polars offers a blazingly fast, multithreaded, and elegant API for data loading, manipulation, and processing. With this hands-on guide, you'll walk through every aspect of Polars and learn how to tackle practical use cases using real-world datasets. Jeroen Janssens and Thijs Nieuwdorp from Xomnia in Amsterdam show you how this superfast DataFrame library is perfect for efficient data wrangling, ETL pipelines, and so much more. This book helps you quickly learn the syntax and understand Polars' underlying concepts. You don't need to have experience with pandas or Spark, but if you do, this book will help you make a smooth transition. With this definitive guide at your side, you'll be able to: Process larger-than-memory datasets at record speed Apply the eager, lazy, and streaming APIs of Polars and decide when to use them Transition smoothly from pandas or Spark to Polars Integrate Polars into your existing code base Work with Arrow and Parquet to efficiently read and write data Translate complex ETL tasks into efficient and elegant queries.
Seller Inventory # LU-9781098156084
Unlock the power of Polars, a Python package for transforming, analyzing, and visualizing data. In this hands-on guide, Jeroen Janssens and Thijs Nieuwdorp walk you through every feature of Polars, showing you how to use it for real-world tasks like data wrangling, exploratory data analysis, building pipelines, and more.
Whether you're a seasoned data professional or new to data science, you'll quickly master Polars' expressive API and its underlying concepts. You don't need to have experience with pandas, but if you do, this book will help you make a seamless transition. The many practical examples and real-world datasets are available on GitHub, so you can easily follow along.
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