From pandas to Polars
1hIntermediate2024-06-18
Authors
Madecraft
Full-Service Learning Content Company
Course details
Navigate the shift from pandas to Polars, uncovering motivations, essential differences, and comparative performance insights. Led by Brett Vanderblock, a seasoned business intelligence manager and data science expert, this course offers an insider's perspective on effective data handling. Learn about the fundamental contrasts and similarities between pandas and Polars. Explore the efficiency and advanced features of Polars, alongside practical applications and optimization techniques. Plus, dive into best practices to maximize data analysis outcomes. After completing this course, you will be adept at leveraging Polars for data aggregation, distinguishing between the data structures of both libraries, and evaluating your performance, empowering you with the skills to navigate the evolving landscape of data analysis with Polars.
Skills covered
pandasData Science FoundationsData AnalysisData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceOne-Off
Concepts
0. Introduction
- 01 - From pandas to Polars
1. Understanding pandas vs. Polars
- 02 - Features, strengths, and limitations of pandas
- 03 - Key features and benefits of transitioning to Polars
2. Polars Core Concepts and Differences
- 04 - Data structures - pandas DataFrame vs. Polars DataFrame
- 05 - Indexing and data selection
- 06 - Comparing data manipulation
- 07 - Handling missing data
- 08 - Apply aggregation and grouping
3. Comparing Performance and Efficiency
- 09 - Memory management in Polars
- 10 - Efficient data processing with Polars
- 11 - Benchmarking performance of pandas vs. Polars
4. Advanced Polars Features
- 12 - Explore advanced Polars functions
- 13 - Time series analysis in Polars
5. Practical Applications
- 14 - Real-world data analysis
- 15 - Transitioning your pandas code to Polars
- 16 - Moving between pandas and Polars
6. Best Practices and Optimization
- 17 - Writing efficient Polars code
- 18 - Debugging and troubleshooting in Polars
Conclusion
- 19 - The future of data analysis with Polars