Box & Whisker Plot Maker
Paste one or more numerical datasets to create a box plot instantly. Compare distributions, calculate quartiles and IQR, identify outliers, and download the finished chart as a PNG.
Create your box and whisker plot
1. Enter datasets
Put one dataset on each line: name first, then comma- or tab-separated values.
Preview
3 valid datasets
Calculated statistics
| Dataset | n | Min | Q1 | Median | Q3 | Max | IQR | Fences | Outliers |
|---|---|---|---|---|---|---|---|---|---|
| Group A | 8 | 12 | 14.5 | 18.5 | 22.5 | 31 | 8 | 2.5 to 34.5 | None |
| Group B | 8 | 8 | 12 | 16 | 19.5 | 23 | 7.5 | 0.75 to 30.75 | None |
| Group C | 8 | 4 | 6.5 | 9.5 | 11.5 | 38 | 5 | -1 to 19 | 38 |
How to make a box and whisker plot
- Enter each dataset. Paste one named row per group or edit the dataset cards manually.
- Review the calculations. Check the five-number summary, IQR, fences, and detected outliers below the chart.
- Choose an orientation. Use a vertical layout for familiar classroom plots or horizontal boxes when group names are longer.
- Export the result. Show or hide outlier points, add a useful title and axis label, then download the PNG.
What does a box and whisker plot show?
A box and whisker plot summarizes the center and spread of numerical data. The box runs from the first quartile (Q1) to the third quartile (Q3), so it contains the middle 50% of the observations. A line inside the box marks the median. The whiskers extend to the most extreme values that are not classified as outliers.
This compact design makes box plots especially useful when you need to compare distributions. You can quickly see which group has a higher typical value, which group varies more, whether the distribution appears uneven, and whether unusual observations sit beyond the whiskers.
The five-number summary
The traditional five-number summary contains the minimum, Q1, median, Q3, and maximum. ChartMaker lists those five values in the accessible statistics table, along with sample size, IQR, fences, and outliers. When outliers exist, the plotted whiskers stop at the smallest and largest non-outlier values rather than at the raw minimum and maximum.
Median, quartiles, and IQR
The median divides sorted data into a lower and upper half. Q1 is the median of the lower half, while Q3 is the median of the upper half. Their difference, Q3 minus Q1, is the interquartile range (IQR). Unlike the full range, the IQR is based on the central half of the observations and is less affected by extremely high or low values.
Quartile conventions differ slightly between textbooks and software. This calculator uses the exclusive median-of-halves method: when a dataset has an odd number of observations, the overall median is not included in either half before Q1 and Q3 are calculated. Stating the method matters when comparing results from different tools, especially for small datasets.
How this box plot identifies outliers
The lower fence is Q1 − 1.5 × IQR and the upper fence is Q3 + 1.5 × IQR. Values outside those boundaries are shown as individual points when outliers are enabled. The fences are calculation thresholds; they are not necessarily observed values. The whiskers end at the most extreme actual observations that remain inside the fences.
An outlier is a signal to investigate, not an automatic error. It may represent a valid rare case, a measurement problem, or a subgroup that deserves separate analysis. Keep the original context in mind before removing any value.
Interpreting and comparing box plots
Compare centers
Use median lines to compare the typical value of several groups without assuming a normal distribution.
Compare spread
Wider boxes indicate a larger IQR, while longer whiskers show more variation outside the central 50%.
Notice asymmetry
An off-center median or one long whisker can suggest skew, though the raw data should confirm the pattern.
Box plots deliberately hide individual inlier values and the detailed shape of a distribution. For small datasets, inspect the original numbers as well. A histogram is often a useful companion because it shows frequency and distribution shape more directly.
Box plot maker FAQ
How does this box plot maker calculate quartiles?
ChartMaker sorts each dataset and uses the exclusive median-of-halves method. For an odd number of values, the overall median is excluded before calculating Q1 from the lower half and Q3 from the upper half.
How are outliers identified?
A value is marked as an outlier when it is below Q1 minus 1.5 times the IQR or above Q3 plus 1.5 times the IQR. Whiskers end at the most extreme values inside those fences.
Can I compare multiple datasets?
Yes. Paste one named dataset per line or add datasets manually. The chart and statistics table display every valid dataset together for comparison.
Does ChartMaker upload my values?
No. Parsing, quartile calculations, chart rendering, and PNG creation all happen locally in your browser.