Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

DataCamp

Data Processing and Pipeline Optimization with Polars

via DataCamp Path

Overview

Get hands-on with Polars, a fast and efficient package for processing tabular data in Python, and learn how to take your pipelines from first draft to production. You'll start with the basics of transforming, cleaning, and visualizing data, then build on those skills with intermediate techniques like text manipulation, time series analysis, joins, and custom expressions for deeper analysis. The track finishes by teaching you to scale and optimize your pipelines: reading query plans, working with Parquet, CSV, and database sources, using advanced data types, and streaming large datasets in batches. You'll come away able to build reliable, well-tested pipelines that handle data of any size.

Syllabus

  • Introduction to Polars
    • Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.
  • Data Transformation with Polars
    • Take Polars further with text manipulation, rolling statistics, DataFrame joins, and advanced analytics.
  • Scaling and Optimizing Data Pipelines with Polars
    • Learn to optimize, scale, and test Polars data pipelines for production-ready performance.

Taught by

Liam Brannigan

Reviews

Start your review of Data Processing and Pipeline Optimization with Polars

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.