Binning
Upload a dataset to begin
Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
Sign in for free for unlimited files, no payment required.
About Binning
Group continuous numbers into buckets (e.g. Age groups).
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.
Category: AI & Machine LearningCommon Use Cases
- Converting exact ages into age brackets for a demographic report
- Bucketing order amounts into "small/medium/large" tiers for cohort analysis
- Turning a continuous credit score into risk bands for a scorecard model
Key Features
- Equal-Width Binning
- Equal-Frequency (Quantile) Binning
- Custom Boundary Definition
- Auto-Generated Bin Labels
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.
Frequently Asked Questions
Turning a continuous "Age" column into discrete buckets like 0-18, 19-35, 36-50, and so on.
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.
Read the related guide →