🎻 Violin Plot Generator

Enter comma-separated values for each group, then generate your chart.

Show Box Plot
Show Mean Line
Show Data Points
Mirror Violin
Show Grid Lines
Animate on Render
Ready — add data and generate your violin plot.

Powerful Features

Everything you need to create professional violin plots — right in your browser, no install required.

📊

Multi-Group Support

Compare multiple data series side-by-side with unique colors, labels, and full KDE distributions per group.

🎨

Custom Color Schemes

Pick individual colors per series or choose from curated palettes — Cool Blues, Warm Sunset, Earthy, and Neon.

📦

Box Plot Overlay

Toggle a built-in box plot overlay showing median, IQR, and whiskers on top of each violin shape.

🔵

Data Point Scatter

Optionally render individual data points with jitter for full transparency of your raw data distribution.

📐

KDE Bandwidth Control

Adjust kernel density estimation bandwidth from narrow to wide to best represent your distribution's shape.

💾

Export SVG & PNG

Download publication-ready charts as lossless SVG or high-resolution PNG — perfect for reports and presentations.

📈

Live Statistics

Instant computed stats per series: mean, median, standard deviation, min, max, and quartiles.

📱

Fully Responsive

Works perfectly on mobile, tablet, and desktop. Charts scale to fit any screen size without overflow.

How to Create a Violin Plot

Four simple steps to visualize your data distribution.

1

Add Your Data Series

Click Add Series and enter comma-separated numbers (e.g. 12, 15, 18, 22, 25). Name each group and pick a color. Add as many series as needed for comparison.

2

Configure Display Options

Set chart title, axis labels, bandwidth, color scheme. Toggle box plot overlay, mean line, data points, and animation on or off to match your needs.

3

Generate Your Chart

Click Generate Violin Plot. The chart renders instantly using kernel density estimation — statistics are computed automatically below.

4

Export & Share

Download your violin chart as SVG or PNG, or copy the SVG code directly. Use in presentations, reports, publications, or websites.

What Is a Violin Plot? A Complete Guide to Violin Chart Maker

A violin plot is a powerful statistical visualization that merges the best of a box plot with a kernel density estimate (KDE), giving analysts and researchers a complete picture of data distribution. Unlike a box plot that only shows summary statistics, a violin graph reveals the full shape, modality, and density of your data — making it invaluable for spotting bimodal distributions, skewness, and outliers at a glance.

Our free violin chart maker lets you build publication-ready violin plots directly in your browser using real KDE algorithms powered by D3.js. There's no account needed, no software to install, and no technical expertise required. Simply paste your comma-separated values, pick your colors, and hit generate.

Violin plot examples span many fields: comparing test scores across classrooms, analyzing salary distributions by job title, studying biological measurements across species, evaluating A/B test results, and exploring sensor readings in engineering. Wherever you need to compare distributions between groups, a violin chart is the ideal visualization choice.

Unlike traditional histograms, which depend heavily on bin size, or box plots, which compress distribution shape into five numbers, a violin plot uses KDE to produce smooth, interpretable curves that scale with your data. Our tool lets you control bandwidth, add box plot overlays, scatter individual data points, and mirror violin halves — covering every common violin plot use case.

Whether you're a data scientist, educator, researcher, or analyst, our online violin plot maker makes it easy to explore and communicate data distributions. Export to SVG or PNG for flawless embedding in any document. All computation happens client-side — your data never leaves your device.

Frequently Asked Questions

A violin plot is used to visualize the full distribution of a dataset — showing density, median, IQR, and outliers. It's ideal for comparing distributions across multiple groups, detecting multimodality, and understanding data spread in statistics, research, and data science.
A box plot shows 5 summary statistics: minimum, Q1, median, Q3, and maximum. A violin chart adds a kernel density estimate alongside, so you can see the actual distribution shape — including bimodal peaks and skewness that a box plot hides.
Enter comma-separated numbers for each series (e.g. 10, 15, 22, 18, 30). You can also use newline-separated values. The tool validates input in real-time and shows errors for non-numeric or empty entries.
Yes. After generating, you can download your violin chart as SVG (scalable vector, perfect for print and web) or PNG (raster image for presentations and documents). You can also copy the raw SVG code to clipboard.
Completely free, with no account or signup required. All computation runs in your browser using D3.js. Your data never leaves your device — full privacy guaranteed.
Bandwidth controls the smoothness of the kernel density estimate. A narrow bandwidth gives a spiky, detailed shape revealing small peaks. A wide bandwidth produces a smoother, more generalized curve. "Auto" uses Silverman's rule of thumb for a balanced result.

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