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Box Plot Calculator

Paste one or two samples to compare their five-number summaries, interquartile ranges and Tukey outliers. Choose how quartiles are calculated.

Sample 1
Sample 2

Enter up to 2,000 numbers per sample. Separate values with semicolons, spaces or new lines. Semicolons keep decimal commas intact.

Each sample accepts 1–2,000 finite values with absolute magnitude at most 1,000,000,000. The 1.5×IQR fences flag potential outliers; whiskers end at the most extreme in-fence values. Different quartile methods can give different Q1 and Q3 values. This is a descriptive chart, not a significance test or a reason to remove data.

How do you calculate a box plot?

Sort each sample, find its median and quartiles, then calculate the interquartile range (Q3 − Q1). The whiskers reach the most extreme observations within 1.5 IQR fences; values beyond them are shown as outliers.

Frequently asked questions

How do you calculate a box plot?

Sort each sample, find its median and quartiles, then calculate the interquartile range (Q3 − Q1). The whiskers reach the most extreme observations within 1.5 IQR fences; values beyond them are shown as outliers.

Are my data uploaded?

No. Statistics and the chart are calculated in this browser. Your values are not uploaded or saved by this tool.

What does the box in a box plot show?

The box runs from the first quartile (Q1) to the third quartile (Q3). The line inside marks the median, and the box length is the interquartile range (IQR). Whiskers show the in-fence range; points beyond the fences are marked as outliers.

Why can quartile results differ?

There is more than one accepted quartile convention. This calculator labels each method: median of halves excluding the overall median, median of halves including it, or linear interpolation using type 7. Choose the convention required by your class or analysis.

Does an outlier mean I should delete that value?

No. The 1.5×IQR rule only flags values for review. Check the data and context before deciding what to do; unusual values may be valid observations.