Binning

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AboutBinning

Group continuous numbers into buckets (e.g. Age groups).Category: AI & Machine Learning
Converting exact ages into age brackets for a demographic reportBucketing order amounts into "small/medium/large" tiers for cohort analysisTurning a continuous credit score into risk bands for a scorecard model
The Binning tool is compatible with:.Use Binning to turn a continuous column into buckets, then either aggregate with Group By to compare bucket-level stats, or run the result through Encoding if the buckets need to become model-ready binary columns.
This tool takes a continuous numeric column and discretizes it into a smaller number of labeled ranges, either equal-width bins, equal-frequency (quantile) bins, or custom boundaries you define. It trades precision for interpretability: instead of every distinct age value, you get a handful of meaningful groups like "0-18", "19-35", "36-50" that are easier to chart, filter, or feed into a categorical model. Binning is often the step right before Group By or Encoding, once continuous values become categories, they can be aggregated or one-hot encoded like any other category.

Frequently Asked Questions:

What's a practical example?

Turning a continuous "Age" column into discrete buckets like 0-18, 19-35, 36-50, and so on.

Can I control the bucket boundaries?

Yes, you define how the continuous values get grouped into bins.


Useful for analysts turning granular numeric data into readable categories for dashboards, reports, or simpler models.