đź“Š Box Plot Creator
Free, instant box plot generator for students, researchers, and analysts.
Paste your numbers and get a complete five-number summary, IQR, outlier detection,
and a clean chart — all inside your browser.
No signup · No upload · No tracking · Works offline
Five-number summary
Outlier detection (1.5×IQR)
Canvas rendered
100% private
Step 1 — Enter your dataset
Type or paste your numbers below. Separate values with commas, spaces, or new lines. The chart updates automatically as you type.
Numbers (comma or space separated)
Accepts integers and decimals. Duplicate values are supported. Minimum 3 numbers recommended for a meaningful plot.
Min / max
Q1 / Q3
Median
Whiskers: 1.5×IQR
Outliers as red dots
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Step 2 — Five-number summary & descriptive stats
Min—
Q₁—
Median—
Q₃—
Max—
IQR—
Mean—
Count (n)—
Step 3 — Box plot diagram
The blue box spans Q1 to Q3 (the interquartile range). The dark vertical line marks the median.
Dashed whiskers extend to the last data points within 1.5×IQR. Red dots indicate outliers beyond the fences.
🔒
100% private — your dataset never leaves your device. All calculations run in JavaScript directly in your browser. No server, no storage, no cookies.
What is a box plot?
A box plot (also called a box-and-whisker plot) is a standardised way of displaying the distribution
of a dataset based on five summary numbers: the minimum, first quartile (Q1), median, third quartile (Q3), and maximum.
It was introduced by statistician John Tukey in 1977 and remains one of the most widely used charts in data analysis,
academic research, and quality control.
Box plots are especially useful when you want to compare distributions across multiple groups, identify skewness,
or quickly spot outliers — all without assuming a normal distribution.
How to read a box plot
- Left whisker — the smallest value within 1.5×IQR below Q1 (lower fence).
- Box left edge (Q1) — the 25th percentile; 25% of data falls below this point.
- Median line — the middle value of the dataset (50th percentile).
- Box right edge (Q3) — the 75th percentile; 75% of data falls below this point.
- Right whisker — the largest value within 1.5×IQR above Q3 (upper fence).
- Red dots — individual data points that fall outside the whisker fences; these are outliers.
How to use this tool
- Enter your numbers in the text box above. Separate them with commas, spaces, or line breaks. Decimal numbers are supported.
- Read the summary stats — the eight stat cards update instantly as you type, showing the full five-number summary, IQR, mean, and count.
- Study the chart — the box plot draws automatically on an HTML canvas. Labels are shown above Q1, median, and Q3.
- Check for outliers — if any values fall outside the 1.5×IQR fences, a red alert badge appears listing each outlier value.
- Export your results — click Copy summary to copy all stats as plain text, or Export CSV to download your data with an outlier flag column.
Features
Instant calculation
Quartiles, IQR, and outliers are computed in real time as you type. No submit button needed.
Fully private
Your data never leaves your device. Everything runs in JavaScript with zero network calls.
Tukey method
Uses the standard 1.5×IQR rule for outlier detection and linear interpolation for quartiles.
Copy & export
Copy the full summary as plain text, or export your dataset as a CSV with outlier flags.
Responsive design
Works on desktop, tablet, and mobile. The canvas scales to fit any screen width.
Works offline
Once loaded, the tool works without an internet connection — save the page and use it anywhere.
Frequently asked questions
What is the difference between the median and the mean?
The median is the middle value when data is sorted — it is not affected by extreme values. The mean is the arithmetic average of all values and can be pulled toward outliers. For skewed datasets, the median is usually a better measure of centre.
How are outliers detected?
This tool uses Tukey's fence method. The lower fence is Q1 − 1.5×IQR and the upper fence is Q3 + 1.5×IQR. Any value strictly outside these fences is flagged as an outlier and shown as a red dot on the chart.
How are quartiles calculated?
Quartiles are computed using linear interpolation (equivalent to R's Type 7 and Excel's QUARTILE function). This gives smooth values even for small datasets.
What does a wide box mean?
A wide box (large IQR) means the middle 50% of your data is spread over a large range — the dataset has high variability. A narrow box indicates the data is tightly clustered around the median.
Can I use this for academic work?
Yes. The calculations follow standard statistical conventions used in textbooks and research. You can copy the five-number summary directly into a paper, report, or presentation. Always verify results with your institution's preferred software for critical work.
Is my data saved anywhere?
No. This tool runs entirely in your browser. Your data is never sent to any server, stored in any database, or tracked in any way. You can disconnect from the internet and the tool will still work.
Why use a local box plot tool?
Many online chart tools send your data to a server for processing, store it in a database, or require you
to create an account. This matters when your dataset contains sensitive, confidential, or proprietary information —
for example, medical measurements, student grades, financial figures, or research data under embargo.
This tool processes everything locally in your browser using the HTML5 Canvas API and plain JavaScript.
There are no third-party analytics scripts, no data collection, and no external API calls. You can verify
this yourself by opening the browser's developer tools and checking the Network tab — you will see zero requests
after the page loads.
It is also fast. Because there is no round-trip to a server, the chart and statistics update in real time
as you edit your dataset, making it easy to experiment and explore your data interactively.