Mastering Polars: The Beginner's Guide
Mastering Polars: The Beginner's Guide
Last updated 7/2025
Duration: 6h 52m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 2.12 GB
Genre: eLearning | Language: English
Last updated 7/2025
Duration: 6h 52m | .MP4 1920x1080 30 fps(r) | AAC, 44100 Hz, 2ch | 2.12 GB
Genre: eLearning | Language: English
Supercharge Your Data Processing with Polars – The Fastest Alternative to Pandas!
What you'll learn
- Working with larger-than-memory data
- Pandas Vs Polars over billion data
- Taking advantage of parallel and optimised analysis with Polars
- Using Polars expressions for analysis that is easy to read and write
- Learn strategies to optimize memory usage and processing speed when dealing with massive datasets.
- Combining data from different datasets using fast joins operations
- Load data from various sources, including web-based files, CSV, JSON, and Parquet files.
Requirements
- No prior experience is required! This course is designed for beginners, Basic knowledge of Python is good to have, and I'll guide you step by step. All you need is a computer with an internet connection and a willingness to learn."
Description
Unlock the power ofPolars (Version 1.22.x), the next-generation DataFrame library designed forspeed, scalability, and efficiency. Whether you're adata scientist, analyst, or engineer, this course will teach you how toleverage Polarsto process and analyze large datasetsfasterthan traditional tools like Pandas.
Throughhands-on projects and real-world datasets, you'll gain adeep understandingof Polars' capabilities, frombasic operations to advanced data transformations. By the end of this course, you'll be able toreplace Pandas with Polarsfor high-performance data workflows.
In this course, you'llmaster Polars from scratch—learning how to efficiently manipulate, analyze, and transform large datasets with ease. Whether you're dealing with millions of rows or complex queries, Polars'multi-threaded and lazy executionwill supercharge your workflows.
What You'll Learn
Polars vs. Pandas– Why Polars is faster and how it works under the hoodPolars DataFrames & LazyFrames– Understanding efficient data structuresFiltering, Sorting, and Aggregations– Perform operations at blazing speedGroupBy and Joins– Handle complex data transformations seamlesslyTime Series & String Operations– Work with dates, timestamps, and text dataI/O Operations– Read and write CSV, Parquet, JSON, and morePolars Expressions & SQL-like Queries– Unlock powerful data processing techniquesParallel Processing & Lazy Evaluation– Optimize performance for large datasets
Who This Course Is For
Python users working withlarge datasetsData analysts & scientists looking forfasteralternatives to pandasEngineers working withBig Dataor ETL pipelinesAnyone who wants tofuture-prooftheir data skills with a high-performance library
Why Learn Polars?
Blazing-fast performance– 10-100x faster than pandas in many casesBuilt for modern CPUs– Usesmulti-threading and Rust-based optimizationsMemory-efficient– Works well even with limited RAMIdeal for Big Data & ETL– Perfect for processing large-scale datasets
By the end of this course, you'll beconfidently using Polarsfor real-world data analysis,optimizing your workflows, and handling massive datasets like a pro.
Who this course is for:
- Beginners in Polars: Data scientists with no prior experience with Polars who want to quickly and confidently get started.
- Intermediate Users: Those who are already familiar with Polars but are looking to deepen their understanding and unlock more advanced techniques.
- Users of Other Data frame Libraries: Practitioners currently using Pandas or other data frame libraries who wish to explore the modern, efficient capabilities of Polars for enhanced data processing.
More Info