Polars for Beginners: DataFrames Made Simple and Fast скачать в хорошем качестве

Polars for Beginners: DataFrames Made Simple and Fast

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/... 👉 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...   👉 Full Polars for Beginners Playlist:   • Beginner-Friendly Polars Data Science   If you found this helpful, please give the video a like 👍 and subscribe for more Polars and Python tutorials. —- 🕒 Timestamps 00:00 Introduction – Getting Started with Polars 00:40 Creating a Polars DataFrame 03:24 Building a Fake Dataset in Python 04:38 Exploring DataFrames with Polars 08:04 Reading and Writing Data (CSV & Parquet) 09:33 Common I/O Pitfalls and How to Fix Them 10:39 Wrap-Up and Next Steps —- #Polars #DataScience #Python #DataFrame #Tutorial #JupyterNotebook #VScode #uv #PolarsForBeginners #ZeroToDataDev