Data Mastery: Polars Unpacked

Explore High-Speed Data Analysis with Polars in Python

Contents

Introduction
Setting Up Your Environment
Loading and Inspecting Your Data
Data Cleaning and Preprocessing
Data Visualization
Descriptive Statistics and Insights
Advanced EDA Techniques
Conclusion and Next Steps

The implementation is available below:

portfolio/eda/polars.ipynb at main · smortezah/portfolio

Introduction

Welcome to the realm of Polars — a fast DataFrame library in Python designed for large datasets. Inspired by pandas, Polars takes it up a notch by offering a more memory-efficient and faster performance, thanks to its implementation in the Rust programming language.

Polars can handle large datasets effortlessly and delivers computations at a lightning-fast speed without the need to load everything in memory. Plus, leveraging Apache Arrow to execute…