Polars for Beginners: DataFrames Made Simple and Fast

Описание: Learn how to create and explore your first Polars DataFrame — the foundation of fast and efficient data analysis in Python.
This video is part of my beginner-friendly Polars Data Science Series, designed to help you start working with Polars or transition smoothly from pandas to Polars.

🚀 What you’ll learn:

Create Polars DataFrames in multiple ways
Avoid common pitfalls (data types and column lengths)
Generate a fake coffee shop sales dataset
Explore data with .head(), .describe(), .schema, and .shape
Read and write CSV and Parquet files
Understand a common CSV pitfall and how to fix it

💻 Code & Resources:

👉 GitHub Repo: https://github.com/zerotodatadev-hub/polar...

👉 Polars documentation: https://docs.pola.rs/


🧠 Before you start:
Make sure you’ve set up Polars and your Python environment.
If not, watch the previous video:
👉 Set up Polars fast with uv — using Python 3.13 and Jupyter in VS Code.
   • Set Up Polars Blazingly Fast (with uv + Py...  

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🕒 Timestamps

0:00 Introduction – Getting Started with Polars
0:40 Creating a Polars DataFrame
3:24 Building a Fake Dataset in Python
4:38 Exploring DataFrames with Polars
8:04 Reading and Writing Data (CSV & Parquet)
9:33 Common I/O Pitfalls and How to Fix Them
10:39 Wrap-Up and Next Steps
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