How does the IQR method work?

It sorts a column, finds the first and third quartiles (Q1 and Q3), and computes the inter-quartile range IQR = Q3 minus Q1. Any value below Q1 minus k times IQR or above Q3 plus k times IQR is an outlier; k defaults to 1.5 (the standard fence) and 3.0 marks extreme outliers.

How does the Z-score method work?

It computes each column's mean and standard deviation, then the Z-score (value minus mean, divided by standard deviation) for every cell. Values whose absolute Z-score exceeds the threshold (commonly 3) are flagged as outliers.

Which method should I use?

IQR is robust and works well on skewed data because quartiles are not pulled by extremes. Z-score assumes a roughly normal distribution and is sensitive to the very outliers you are hunting, so a few large outliers can mask others. Try both.

No. The CSV is parsed and all statistics are computed in JavaScript in your browser. Nothing is sent to a server, so it is safe for confidential datasets.

What about empty cells or text in a numeric column?

Non-numeric and empty cells are skipped when computing a column's statistics and are never flagged. A column is treated as numeric only if most of its non-empty cells parse as numbers.

CSV Outlier Detector

Spot anomalies in tabular data

Bad data hides in spreadsheets — a price typed with an extra zero, a sensor that spiked, a duplicated row. This tool reads a CSV, finds the numeric columns, and flags the values that sit far outside the rest of their column using one of two standard statistical methods: the IQR fence or the Z-score. Everything is computed locally, so you can vet a confidential dataset without uploading it.

How it works

The CSV is parsed in the browser (handling quoted fields and commas inside quotes). For each column the tool decides whether it is numeric by checking that most non-empty cells parse as numbers. Then:

IQR method: the column is sorted, Q1 and Q3 are taken at the 25th and 75th percentiles (linear interpolation), and IQR = Q3 − Q1. A value is an outlier if it is below Q1 − k·IQR or above Q3 + k·IQR. The multiplier k defaults to 1.5; 3.0 flags only extreme outliers.
Z-score method: the column’s mean μ and sample standard deviation σ are computed, and each value’s z = (x − μ) / σ. A value is an outlier when |z| exceeds your threshold (default 3).

Empty and non-numeric cells are ignored in the statistics and never flagged.

Tips and notes

IQR is the safer default for skewed or heavy-tailed data because quartiles are not dragged around by the outliers themselves.
With Z-score, a single huge value inflates σ and can hide smaller anomalies — if you suspect that, switch to IQR.
The bounds used for each column are shown so you can sanity-check whether the threshold matches your domain knowledge.