Compute Percentiles for CSV Files Online
Compute percentiles, median, MAD, mode, and kurtosis for numeric columns in CSV files directly in your browser. Optionally group by a category column. Results download as CSV — no upload required.
How to compute Percentiles for CSV 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 (CSV)
endpoint,latency_ms,status_code
/search,120,200
/search,180,200
/login,40,200
/search,200,200
/login,60,401
/search,300,200Settings
- 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 CSV files
A CSV column only counts as numeric if every value in it parsed as a number on load. One stray entry such as "n/a", "timeout" or "1,204" turns the whole column into text. If that leaves no numeric columns, the tool shows "No numeric columns detected". If you pick the text column anyway, the run fails because percentiles need numbers. Fix the stray values with Find & Replace, or convert the column with Cast Column Types, then run again.
Empty fields load as NULL and are left out of every statistic, so they do not drag the median toward zero. A 0 written in the file, by contrast, is a real measurement and counts. If your logging tool writes 0 for "no response", filter those rows out first. Numbers in scientific notation such as 1.2e3 load as numbers, but values with units attached, like 184ms, do not. The CSV you download holds just the summary, one row per group, with one column per ticked statistic.
Frequently Asked Questions
Why does the tool say no numeric columns were detected in my CSV?
At least one value in each column could not be read as a number, so the columns loaded as text. Look for units, thousands separators or words like "n/a", clean them, and reload.
Are empty CSV cells counted as zero?
No. Empty cells are NULL and are ignored. Only values that are present are used for the percentiles.
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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