Polars Tutorial 1: Intro to Polars and Your First DataFrame скачать в хорошем качестве

Polars Tutorial 1: Intro to Polars and Your First DataFrame

Polars Tutorial (Python) – Intro & Your First DataFrame Welcome to the first video in this Polars for Python tutorial series! 🐻‍❄️ In this beginner-friendly introduction, you’ll learn what Polars is, why it’s becoming a popular alternative to pandas, and how to create your first Polars Series and DataFrame in Python. Polars is a fast, modern, columnar DataFrame library built on Apache Arrow and written in Rust. It’s designed for performance, scalability, and expressive data transformations—making it ideal for data analysis, data engineering, and analytics workflows. 🔹 Why use Polars? Blazing fast performance (written in Rust) Columnar memory model (Apache Arrow-based) Lazy execution for query optimization and efficiency Lower memory usage than pandas Powerful expression syntax for clean, readable code Great for large datasets and modern data pipelines ⏱️ Video Timeline 0:00 – Intro 0:39 – What is Polars? 1:38 – Google Colab notebook setup & imports 2:44 – Creating a Polars Series 4:52 – Creating your first Polars DataFrame 8:00 – Common exploratory functions in Polars By the end of this video, you’ll understand the core ideas behind Polars and be ready to start working with DataFrames the Polars way. 📌 Subscribe for the rest of the Polars series, where we’ll cover filtering, expressions, groupby, lazy execution, joins, and real-world examples. #polars #python #dataanalysis #dataengineering #dataframes #apachearrow #pandas #machinelearning ***Get the ColLab notebook and data here https://github.com/hthomas229/PurpleC...