How do I make a violin plot?

Use the generator above: paste the raw numbers for each group, separated by commas, spaces, or new lines. The kernel-density violin shape, the interquartile box, and the median render instantly, and you can add more groups to compare. Download it as a scalable SVG — free, with no sign-up.

What is the difference between a violin plot and a box plot?

A box plot summarizes a distribution with quartiles, a median, and outliers, but hides its shape — two very different distributions can produce the same box. A violin plot adds a mirrored kernel-density curve around that box, so you also see skew, spread, and any second peak (bimodality). A violin plot is a box plot plus the shape.

What does the width of a violin mean?

The width at a given height is the estimated density of the data at that value: wide sections mean many observations fall there, narrow sections mean few. The shape is a kernel density estimate, so it is a smoothed version of a histogram turned on its side and mirrored.

What is inside the violin?

Inside each violin is a small box spanning the interquartile range (Q1 to Q3), a dot marking the median, and a thin line showing the full minimum-to-maximum range. These summary statistics are computed directly from your numbers, while the outer shape is the kernel density estimate.

How many data points do I need for a violin plot?

A violin plot needs enough points for the density estimate to be meaningful — roughly 20 or more per group. With only a handful of observations the kernel density estimate produces a wide, misleading shape, so for very small samples a box plot or a dot plot is a better choice.

Can I export the violin plot for a paper?

Yes. Download it as an SVG — a vector format that stays sharp at any size and drops straight into a manuscript, thesis, poster, slide deck, or Jupyter notebook, or opens in Illustrator or Inkscape for final edits. Every version is free to download.

Data Science Tool

Violin Plot Generator with Density & Quartiles

Free violin plot generator — paste your numbers to draw a kernel-density violin with quartile box and median, and compare groups. Export SVG.

Paste numbers — exact kernel-density violin SVGInner quartile box and median markerCompare several groups on one axisDownload a publication-ready SVG — free

Paste your numbers — renders an exact violin plot with density, quartiles & median, free

TitleValue axis label

Paste raw values for each group — the kernel-density shape, quartile box, and median are computed for you.

Violin Plot Examples

Exact engine renders — single distributions, group comparisons, and skew

View:

Two-Group Comparison

Exact engine render — two groups with density shapes and inner quartile boxes.

comparisondensityquartiles

Single Distribution

Exact engine render — one distribution as a kernel-density violin.

singlekdedistribution

Four-Group Comparison

Exact engine render — four groups compared on one value axis.

four-groupcomparisonmulti

Skewed Distribution

Exact engine render — a right-skewed distribution with a long tail.

skewtailasymmetric

Test Scores by Class

Exact engine render — test-score distributions across two classes.

educationscoresclasses

Gene Expression

Exact engine render — gene expression across three conditions.

biologyexpressionconditions

What is a violin plot?

A violin plot shows the full distribution of a numeric variable. It looks like a box plot with a mirrored density curve wrapped around it: the width at any height is the estimated density of the data at that value, so wide sections mean many observations and narrow sections mean few. Inside each violin, a small box marks the interquartile range (Q1 to Q3) and a dot or line marks the median, combining the summary statistics of a box plot with the shape information of a histogram. Violin plots are the standard way to compare distributions across groups — they reveal skew, multiple peaks (bimodality), and spread that a box plot alone would hide. This generator computes the kernel density estimate and the quartiles from the numbers you paste in and draws one violin per group.

How to read a violin plot

Width at a given height = density — the wider the violin there, the more data points fall near that value.
The inner box spans the interquartile range (Q1 to Q3); half the data lies inside it.
The dot marks the median; the thin line is the full min-to-max range.
A long tail or a second bulge reveals skew or bimodality that a box plot would flatten out.

Violin plot vs box plot vs histogram

All three show distribution, but at different resolutions. A histogram shows the shape of one distribution in detail but is awkward for comparing many groups side by side. A box plot summarizes each group compactly with quartiles and outliers but hides the shape — two very different distributions can share the same box. A violin plot is the middle ground: it keeps the box plot's compact per-group summary while adding the density shape, so it is ideal when you want to compare several groups and still see whether each is skewed or bimodal. Use a histogram to study one distribution closely, a box plot for a quick five-number comparison, and a violin plot when shape and comparison both matter.

How to make your violin plot

Paste the raw numbers for each group into its box — separated by commas, spaces, or new lines.
Set the title and value-axis label; the density shape, quartile box, and median update as you type.
Add a second or third group to compare distributions on the same axis, each with its own color.
Download a clean, scalable SVG for your paper, report, or slides — free, with no sign-up.

Kernel density estimation behind the shape

The smooth outline of each violin is a kernel density estimate (KDE): every data point contributes a small Gaussian bump, and the bumps are summed to form a continuous curve, with the bandwidth chosen by Silverman's rule of thumb. That is why a violin looks smooth even from a handful of points, and why very small samples produce wide, uninformative shapes — with only a few observations, prefer a box plot or a dot plot. This tool normalizes each violin to the same maximum width so groups are easy to compare; the quartile box and median inside are computed directly from your data, not from the smoothed curve.

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