Data Analysis with Polars and Python
High-performance data analysis using Polars, Python, and modern DataFrame workflows
Created by Boris Paskhaver
Explore efficient data analysis with Polars and Python, focusing on speed, scalability, and modern DataFrame workflows. Move from Python basics to advanced Polars features like joins, filtering, and lazy evaluation. Gain hands-on experience with real datasets and practical tools for high-performance analytics.
Packt | Jan 2026 | 1333 min
What You Will Learn
You will build skills through hands-on exercises using real-world datasets in Jupyter Lab. Concepts are introduced step by step, with plenty of practice to reinforce each new technique. Quizzes and structured activities help you retain what you learn and apply it confidently.
Key Features
- Work efficiently with large datasets using Polars for fast, scalable analysis
- Master joins, filtering, and GroupBy to transform and summarize complex data
- Apply lazy evaluation and query optimization for memory-efficient workflows
Target Audience
Designed for data analysts, data scientists, and Python developers ready to boost their data analysis skills. If you have a basic understanding of Python and want to work more efficiently with large datasets, you'll find practical tools and workflows to advance your projects.
