Detect Outliers in Excel Files Online
Detect statistical outliers in Excel files directly in your browser. Flag or remove rows where numeric values exceed a chosen number of standard deviations from the mean — no upload required.
How to detect Outliers in Excel files
- Drop your file onto the upload area. It is loaded into the in-browser engine and the first 200 rows are shown.
- Pick a threshold in standard deviations from the mean: 1.5σ, 2σ (the default), 2.5σ or 3σ.
- Pick an action: Flag outliers adds an is_outlier column, Keep outliers returns only the outlier rows, and Remove outliers returns the rest.
- Choose the columns to check. Every numeric column is selected to start with. Click a column to toggle it, or use All and None. A row counts as an outlier if any selected column is beyond the threshold.
- Click Detect Outliers. The count shows how many rows were flagged, kept or left. Review the result, then download it in the same format you uploaded.
Your file is processed locally in your browser and is never uploaded. The free limit is 50 MB per file; larger files work if your device has the memory for them.
Worked example
A food distributor logs one temperature reading from each of six freezer units. One unit has a failing compressor and reads far warmer than the rest.
Input (Excel)
Excel workbook, first sheet (Sheet1)
| unit | location | temp_c |
|---|---|---|
| FZ-01 | Bay 1 | -18.2 |
| FZ-02 | Bay 1 | -18.6 |
| FZ-03 | Bay 2 | -17.9 |
| FZ-04 | Bay 2 | -18.4 |
| FZ-05 | Bay 3 | -9.5 |
| FZ-06 | Bay 3 | -18.1 |
Settings
- Threshold: 2σ
- Action: Flag outliers
- Columns to check: temp_c (the only numeric column)
Result
| unit | location | temp_c | is_outlier |
|---|---|---|---|
| FZ-01 | Bay 1 | -18.2 | false |
| FZ-02 | Bay 1 | -18.6 | false |
| FZ-03 | Bay 2 | -17.9 | false |
| FZ-04 | Bay 2 | -18.4 | false |
| FZ-05 | Bay 3 | -9.5 | true |
| FZ-06 | Bay 3 | -18.1 | false |
The mean is −16.78 °C and the sample standard deviation is 3.58 (both rounded), so 2σ is 7.15 degrees. FZ-05 is 7.28 above the mean, a z-score of 2.04, so it is flagged. The faulty reading also inflates the mean and the deviation it is judged against. At 2.5σ nothing would be flagged in a file this small.
Working with Excel files
The first sheet is read as the text each cell displays, so outliers are judged on displayed values. A reading of −9.54 in a one-decimal format is tested as −9.5. That rarely changes whether a row is flagged, but it does change z-scores slightly. Columns formatted as currency or percentages are read as text and do not appear in the column list. Switch them to General format before uploading if you want them checked. A single error cell such as #N/A is read as text and turns the whole column into text, which removes it from the list.
Formula cells are tested on their last calculated value. In the downloaded Sheet1, is_outlier is written as real TRUE and FALSE cells, so Excel's AutoFilter can show just the flagged rows. Keep outliers is a quick way to produce a short review sheet for a colleague, with every original column intact. Formatting and extra sheets from the original workbook are not carried over.
Frequently Asked Questions
Can I filter the flagged rows in Excel afterwards?
Yes. is_outlier is written as TRUE and FALSE cells, so AutoFilter on that column shows the outliers.
Why is my Excel currency column not in the list?
Currency-formatted cells are read as text such as "$1,250.00", so the column is not numeric. Change the format to General or Number in Excel and upload again.
Which method does the tool use?
A z-score test. A value is an outlier when it is more than the chosen number of sample standard deviations away from its column's mean. The mean and deviation come from the whole file. IQR and median-based methods are not offered.
Why are no outliers found at 3σ in my small file?
With n rows, no value can be more than (n − 1) / √n sample standard deviations from the mean. That means 2σ needs at least 6 rows, 2.5σ needs 9, and 3σ needs 11 before anything can be flagged at all. Extreme values also inflate the deviation they are measured against.
How are blank values handled?
They are ignored when the mean and deviation are computed, and a blank is never an outlier. In Flag mode the row gets false unless another column flags it. Remove outliers keeps the row, and Keep outliers leaves it out.
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