Learn how to bin continuous data in Python using pandas cut() and qcut() — two powerful methods every data analyst and data scientist should know! In this tutorial, we break down the difference between equal-width bins (cut) and quantile-based bins (qcut) with clear examples, visuals, and best practices.
By the end of this video, you’ll know:
• ✔️ When to use cut()
• ✔️ When to use qcut()
• ✔️ How to create labels for your bins
• ✔️ How to handle duplicate edges
• ✔️ How to use retbins=True
• ✔️ How binning improves EDA & feature engineering
Whether you're preparing data for machine learning, doing EDA, or learning feature engineering, this video will help you master binning the right way.
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🐍 Code Covered in the Video
• pd.cut() — Equal-width binning
• pd.qcut() — Quantile-based binning
• Creating custom bins
• Adding labels
• Handling duplicates
• Real-world examples using pandas
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