Compute Percentiles for Excel Files Online
Compute percentiles, median, MAD, mode, and kurtosis for numeric columns in Excel files directly in your browser. Optionally group by a category column. Results download as CSV — no upload required.
How to compute Percentiles for Excel files
- Drop your file onto the upload area. The first numeric column is selected, and the panel shows how many numeric columns were found.
- Check the numeric column, and pick a Group by column if you want one row of statistics per category. The default is the whole file.
- Tick the statistics you need. Median, p25, p75, p95 and p99 are ticked by default. p90, MAD, mode and kurtosis are also available.
- Optionally type a custom percentile between 0 and 1, such as 0.8, to add one more column.
- Click Compute Percentiles, review the summary table, and download it as CSV.
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 backend team has a small sample of API request timings and wants the median and tail latency per endpoint to check against a 300 ms target.
Input (Excel)
Excel workbook, first sheet (Sheet1)
| endpoint | latency_ms | status_code |
|---|---|---|
| /search | 120 | 200 |
| /search | 180 | 200 |
| /login | 40 | 200 |
| /search | 200 | 200 |
| /login | 60 | 401 |
| /search | 300 | 200 |
Settings
- Numeric column: latency_ms
- Group by: endpoint
- Statistics: Median and p90 and p99 ticked (p25, p75 and p95 unticked)
Result
| endpoint | median | p90 | p99 |
|---|---|---|---|
| /login | 50 | 58 | 59.8 |
| /search | 190 | 270 | 297 |
Percentiles use linear interpolation between sorted values. /search has four values, so p90 sits 70% of the way from 200 to 300, which is 270, and p99 sits 97% of the way, which is 297. The median of an even count is the average of the middle two. Groups are sorted by name, and the summary downloads as CSV.
Working with Excel files
The tool reads the first sheet as the values Excel displays. A column formatted as currency or with thousands separators, such as "$1,200.00", is read as text and will not appear as numeric. The same goes for percentages shown as "25%". Switch those columns to a plain General or Number format in Excel before uploading, so the underlying values are read. Rounded display formats matter as well: a cell showing 0.1 because of a one-decimal format is read as 0.1, even if the stored value is 0.1234.
Formula cells contribute their last calculated value, which is usually what you want for a results sheet. Error cells like #DIV/0! turn the column into text, so clear or replace them first. Excel's PERCENTILE.INC uses the same linear interpolation as this tool, so the p90 you get here should match =PERCENTILE.INC(range, 0.9) on the same values. The result downloads as CSV, which opens straight back into Excel.
Frequently Asked Questions
Does this match Excel's PERCENTILE function?
Yes for PERCENTILE.INC and the older PERCENTILE, which interpolate in the same way. PERCENTILE.EXC uses a different formula and can give different results on small samples.
Why is my Excel number column not listed as numeric?
The column probably has currency, percentage or thousands formatting, or an error cell. The tool reads displayed text, so change the format to General and remove errors.
Which percentile method does the tool use?
Continuous percentiles with linear interpolation (quantile_cont). A percentile that falls between two values is interpolated, so the result may not appear in your data. The median uses the same method.
What do MAD, mode and kurtosis tell me?
MAD is the median of absolute distances from the median, a spread measure that ignores outliers. Mode is the most frequent value; with ties one of them is returned. Kurtosis measures how heavy the tails are and needs at least four values.
What is the custom percentile column called?
It is named after the value you type, with the dot replaced by an underscore. Typing 0.8 gives a column called p_custom_0_8. Values outside 0 to 1 are ignored.
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