Kernel Density Estimation
Adjustable KDE bandwidth controls how smooth or detailed each violin shape appears, letting you highlight fine-grained patterns or show broader trends.
Violin Plot Chart
Free Online Violin Plot Chart Maker
What is a Violin Plot Chart?
A violin plot chart combines a box plot with a kernel density estimate to show the full distribution of numeric data across categories. Unlike a box plot alone, the width of each 'violin' reveals where values are most concentrated, making it easy to spot skews, multiple peaks, and outliers. It is especially useful when comparing distributions across two or more groups side by side. Use it whenever the shape of your data matters, not just the median or range.
Key Features
Inner Box Plot Overlay
Toggle an embedded box plot inside each violin to display median, quartiles, and whiskers alongside the full distribution shape.
Individual Data Point Display
Optionally render each raw data point inside the violin so viewers can see the actual observations behind the distribution curve.
Multi-Group Comparison
Place multiple violins side by side with distinct colors to compare distributions across groups at a glance.
Vertical and Horizontal Orientation
Switch between vertical and horizontal layouts to fit your slide, report, or dashboard without reformatting your data.
Best For
Comparing test score distributions across student cohorts
Analyzing salary ranges by job title or department
Visualizing clinical trial measurement distributions by treatment group
Exploring sensor or IoT reading patterns across conditions
Comparing response time distributions in A/B experiment results
Showing seasonal variation in environmental measurements
When to Use
- When you need to compare distributions across two or more groups, not just summary statistics
- When your data may be bimodal or multimodal and a box plot would hide those peaks
- When you have enough data points (typically 30+) for a density estimate to be meaningful
- When outliers matter but so does the overall shape of the distribution
- When a histogram per group would be too cluttered side by side
Common Mistakes
- Using a violin plot with very small samples (under 20 points) — the density estimate becomes unreliable
- Setting bandwidth too low, creating spiky shapes that overfit noise in the data
- Setting bandwidth too high, smoothing out real bimodal patterns into a single hump
- Forgetting to show the sample size per group, leaving viewers unable to judge reliability
- Using nearly identical colors for adjacent violins, making groups hard to distinguish
- Omitting axis labels or units, which makes the value scale uninterpretable
Templates
Start with professionally designed templates
Start Free
Create Your Violin Plot Chart with AI
Describe your data or paste values — our AI generates a violin plot chart in seconds.
Free, no sign-up required