Polars for Data Engineering: Faster DataFrames in Python

Partner: Udemy
Affiliate Name:
Area:
Description: Why Learn Polars?If you have worked with data in Python, chances are you have used Pandas for analysis and engineering tasks. While Pandas is widely adopted and feature-rich, it often struggles with performance and scalability when working with larger datasets. This is where Polars comes in. Polars is a modern DataFrame library for Python and Rust, designed to be lightning fast, memory efficient, and highly scalable.This course is designed to teach you how to use Polars effectively for data engineering and analysis. We will start with the fundamentals, including Series, DataFrames, and LazyFrames, and gradually move into more advanced features. You will learn how to filter, group, and aggregate data efficiently, build pipelines with lazy evaluation, and optimize your workflows to handle millions of rows with ease.Along the way, we will compare Polars with Pandas, highlighting the strengths and tradeoffs of each. You will clearly understand when to use Polars and how to transition from Pandas for better performance in your projects.By the end of this course, you will have the skills to build data engineering pipelines with Polars, process large datasets efficiently, and modernize your workflows with next-generation tools. This course is ideal for data engineers, Python developers, analysts, and scientists who want to go beyond Pandas and adopt faster, more scalable approaches to data processing.What you’ll learnPolars basics: Series, DataFrames, and LazyFramesComparing Polars vs. Pandas (and when to switch)Filtering, grouping, and aggregating data efficientlyHandling large datasets with lazy evaluationReal-world data engineering pipelines using PolarsBest practices for performance optimizationWho this course is forData engineers looking to optimize workflowsPython develope
Category: IT & Software > Other IT & Software > Data Engineering
Partner ID:
Price: 39.99
Commission:
Source: Impact
Go to Course