In the world of data analysis and manipulation, Python has long been the go-to language. With extensive and user-friendly libraries like NumPy, pandas, and PySpark, there’s a solution available for almost any data-driven task. Among these libraries, one name that’s been generating a significant amount of buzz lately is Polars.
Polars is a high-performance DataFrame library, designed to provide fast and efficient data processing capabilities. Inspired by the reigning pandas library, Polars takes things to another level, offering a seamless experience for working with large datasets that might not fit into memory.
In this video course, you’ll learn:
- Why Polars is so performant and attention-grabbing
- How to work with DataFrames, expressions, and contexts
- How to read data into DataFrames
- How to group and aggregate data
- What the lazy API is and how to build lazy queries
What’s Included:
- 7 Lessons
- Video Subtitles and Full Transcripts
- 2 Downloadable Resources
- Accompanying Text-Based Tutorial
- Q&A With Python Experts: Ask a Question
- Certificate of Completion
Downloadable Resources:
