Your data
Paste a table straight from Excel or Google Sheets, or drop a CSV file. Nothing is uploaded anywhere — the whole calculation runs inside this browser tab.
CSV, TSV or plain text. Files saved in windows-1251 are detected and re-read automatically, so Cyrillic headers do not turn into garbage.
Parsing options
Columns
Result
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The drawing library is downloaded only when you press the button, and only on this page.
This page has no server side at all. The table you paste is parsed by JavaScript inside your own browser, the chart is drawn on a canvas element on your machine, and the export file is assembled locally. Nothing is uploaded, stored or written to any log. You can disconnect from the network after the page has loaded and everything will still work — which is the simplest way to verify the claim yourself.
Facts and limits of this method
| The five numbers | Minimum, Q1, median, Q3, maximum |
|---|---|
| Also returned | IQR (Q3 − Q1) and the full range (max − min) |
| Quantile definition | R type 7, identical to Excel PERCENTILE.INC |
| Distribution assumptions | None — this is the summary you use when you do not know the shape |
| Relation to the box plot | These five numbers are exactly what a box plot draws |
| Minimum rows | 2 |
When it misleads you
- The summary is silent about what happens between the quartiles. Two very different distributions — one with a single peak, one with two — can produce identical five-number summaries, which is why it pairs naturally with a histogram.
- The minimum and maximum are single observations, so they are the least stable numbers here. One typo in the data changes the range completely while leaving the three middle numbers untouched.
- It says nothing about how many observations there are. A five-number summary from 8 rows looks exactly as authoritative as one from 8000, so always report the count alongside it.
- Because it is built on position, it discards magnitude. That is what makes it robust and also what makes it unable to tell you that the maximum is ten times the median rather than merely above it.
How it is calculated
The values are sorted once. The minimum and maximum are the ends of that sorted list, the median is the middle, and Q1 and Q3 are the quartiles computed with the R type 7 definition — the same one Excel uses for PERCENTILE.INC, so the numbers reconcile with your spreadsheet.
The interquartile range, Q3 − Q1, is added because it is the number that actually gets used. It covers the middle half of the observations and is the robust alternative to the standard deviation when the data is skewed or contains outliers.
The full range, maximum minus minimum, is reported separately and should be treated with suspicion: it is determined entirely by the two most extreme observations and grows mechanically as you collect more data, even when nothing about the process has changed.
These are exactly the five numbers a box plot draws, which is why the box plot tool is linked from this page. The summary is the table; the box plot is the same information as a picture.
Questions and answers
Why five numbers and not the mean and standard deviation?
Because the five-number summary makes no assumption about the shape of the distribution. The mean and standard deviation describe a symmetric single-peaked shape well and everything else badly.
Is this the same as a box plot?
Yes, in content. A box plot draws these five numbers — the box spans Q1 to Q3, the line inside is the median, and the whiskers reach towards the extremes. The box plot tool on this site draws it.
Why is my range so much wider than my IQR?
Because the range is set by the two most extreme values and the IQR ignores them. A large gap between the two is a strong hint that outliers are present; the outlier detection tool will identify them.
Do I need to check for normality first?
No, and that is the point. This summary is valid for any distribution, which is why it is the safe first thing to compute on unfamiliar data.
Does my data leave the browser?
No. Sorting and quantile interpolation both happen locally.