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Outlier Mgmt
Upload a dataset to begin
Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
AboutOutlier Mgmt
Cap, remove, or flag anomalies in your dataset.Category: AI & Machine LearningCapping extreme salary values before calculating a department averageRemoving sensor glitches before running a regressionFlagging suspicious order amounts for a finance team to review manually
The Outlier Mgmt tool is compatible with:.Detect anomalies with Outliers first, then bring the same column here to cap, remove, or flag them based on what you found, checking Stats afterward to confirm the mean and variance settled down.This is the treatment step that follows outlier detection: once you know which values are extreme, this tool lets you decide what happens to them. Choose to winsorize (cap values at a percentile boundary so they stay in the dataset but stop skewing averages), delete the offending rows entirely, or simply tag them in a new column for manual review later. The right choice depends on context, capping preserves row count for modeling, while removal is often better when you're confident the value is a data-entry error.
Frequently Asked Questions:
What are my options once outliers are found?
You can cap them to a threshold, remove them entirely, or just flag them for review, depending on what fits your analysis.
Does this replace the Outliers tool?
No, it's the action step, pair it with the Outliers tool's detection if you want to inspect anomalies before deciding what to do with them.
Built for analysts and data engineers who need to decide, not just discover, what happens to extreme values before modeling or reporting.