Ultimate Python Polars for Data Analytics

Design Optimized, Large-Scale Data Workflows Using Python PolarsBook DescriptionThis book, Ultimate Python Polars for Data Analytics, is a hands-on guide to mastering this high-performance framework. You will begin by understanding Polars’ architecture, execution engine, and columnar memory model—core concepts that drive its exceptional speed and efficiency. From there, the book moves into advanced data transformations, multi-table joins, window functions, and aggregation strategies designed for large-scale datasets.You will gain deep insight into lazy execution and query planning, learning how Polars optimizes computations before execution to minimize memory usage and maximize throughput.What you will learn● Understand Polars’ architecture, execution engine, and memory model.● Design scalable data pipelines using lazy evaluation strategies.● Perform complex transformations, joins, and aggregations efficiently.Who is This Book For?This book is tailored for data analysts, data engineers, data scientists, and machine learning practitioners who want to build high-performance, scalable data workflows using Python. Readers should be comfortable with Python programming and have basic familiarity with SQL and Pandas for data manipulation.Table of Contents1. Introduction to Polars2. Core Concepts of Data Frames and Data Structures3. Polars Configuration4. I/O Operations and Basic Data Manipulation5. Complex Data Transformation with Polars6. Data Visualization7. SQL Integration with Polars8. Extending Polars with UDF and PyO39. Working with Large Datasets10. Profiling, Optimization, and Testing11. Market Data Analysis Using Polars12. Machine Learning with Polars13. Big Data Analysis with Polars14. Emerging Trends and Best Practices       Index