Detect Outliers in CSV Files Online

What methods does the CSV outlier detection tool use?

Z-score (flags rows more than N standard deviations from the mean), IQR (interquartile range — flags values below Q1 − 1.5×IQR or above Q3 + 1.5×IQR), and modified Z-score using MAD (Median Absolute Deviation, more robust for skewed distributions). IQR and MAD are preferred when your data is not normally distributed.

Does the CSV outlier tool remove outliers or just flag them?

By default it adds a boolean flag column marking each row as an outlier or not. You can then filter to keep only the outliers, only the clean rows, or all rows with the flag column. Always inspect the flagged rows before removing them.

Can I detect outliers in multiple columns of a CSV file at once?

Select one column per run. For multi-column outlier detection — flagging rows that are outliers in either price or quantity — run the tool twice and combine the flag columns using the Calculate Column tool, or use the SQL Query tool for a combined condition.

Is my data private?

Yes — completely. Your file is never uploaded to any server. Everything runs locally in your browser using WebAssembly — processing happens entirely inside your tab. Once you close the tab, nothing is retained.

What is the maximum file size?

The free limit is 50 MB. For larger files, performance depends on your device's available memory — most modern machines handle 500 MB to 1 GB comfortably.