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{ "item_title" : "Ultimate Python Polars for Data Analytics", "item_author" : [" Sunny Khilare "], "item_description" : "Design Optimized, Large-Scale Data Workflows Using Python PolarsKey Features● Get a free one-month digital subscription to www.avaskillshelf.com● Progress from Polar fundamentals to scalable, production-grade data pipelines.● Leverage lazy execution and query optimization for high-performance analytics.● Apply Polars to real-world ML, big data, and cloud-scale ETL workflows.Book 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.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 PracticesIndex", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/34/988/735/9349887355_b.jpg", "price_data" : { "retail_price" : "39.95", "online_price" : "39.95", "our_price" : "39.95", "club_price" : "39.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Ultimate Python Polars for Data Analytics|Sunny Khilare

Ultimate Python Polars for Data Analytics

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Overview

Design Optimized, Large-Scale Data Workflows Using Python Polars

Key Features

● Get a free one-month digital subscription to www.avaskillshelf.com

● Progress from Polar fundamentals to scalable, production-grade data pipelines.

● Leverage lazy execution and query optimization for high-performance analytics.

● Apply Polars to real-world ML, big data, and cloud-scale ETL workflows.

Book Description

This 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.

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 Contents

1. Introduction to Polars

2. Core Concepts of Data Frames and Data Structures

3. Polars Configuration

4. I/O Operations and Basic Data Manipulation

5. Complex Data Transformation with Polars

6. Data Visualization

7. SQL Integration with Polars

8. Extending Polars with UDF and PyO3

9. Working with Large Datasets

10. Profiling, Optimization, and Testing

11. Market Data Analysis Using Polars

12. Machine Learning with Polars

13. Big Data Analysis with Polars

14. Emerging Trends and Best Practices

Index

This item is Non-Returnable

Details

  • ISBN-13: 9789349887350
  • ISBN-10: 9349887355
  • Publisher: Orange Education Pvt Ltd
  • Publish Date: March 2026
  • Dimensions: 9.25 x 7.5 x 0.7 inches
  • Shipping Weight: 1.27 pounds
  • Page Count: 336

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