Phone: (617) 982 1253
Email: adrian@violinplot.com
Free Violin Plot Analyzer
Professional violin plots in seconds — no coding, no software, no sign up
Step 1: Choose Analysis Type
Step 2: Enter Your Data
ℹ️ For single variable analysis, you only need numbers.
Step 3: Choose Plot Style
Step 4: Create Visualization
This free tool lets you create publication-quality violin plots directly in your browser. Paste your numbers, choose a style, and get a downloadable chart with full statistics instantly. It uses Python and seaborn under the hood — the same library used by data scientists and researchers worldwide.
How to Use the Tool
1
Choose your analysis type
Select Single Variable Analysis for one dataset, or Compare Multiple Categories to compare groups side by side.
2
Enter your numbers
Paste values separated by commas — e.g. 12, 15, 18, 20, 25. For categories also add a label per number — e.g. Group A, Group A, Group B, Group B.
3
Choose a plot style
Pick from Basic Violin, Violin with Quartiles, Median Highlighted, or Horizontal. Basic Violin is a great starting point.
4
Click Create Violin Plot
Your chart appears instantly with 8 statistics. Click Download PNG to save a 300 DPI image ready for reports and presentations.
What is a Violin Plot?
A violin plot is a statistical chart that shows the full distribution of a dataset. It combines a box plot (median and quartiles) with a kernel density estimate (where data is most concentrated). The result looks like a violin — wide where data clusters, narrow where data is sparse.
Unlike a bar chart or box plot, a violin plot reveals the complete shape of your data — whether it’s symmetric, skewed, or has multiple peaks.
What the shape tells you
- Wide sections — more data points at that value
- Narrow sections — fewer data points at that value
- Multiple bulges — data has more than one cluster
- Long thin tail — a few extreme values exist
- Symmetric shape — data evenly distributed
Parts of a violin plot
- Outer shape — kernel density, shows distribution
- Center line — the median value
- Inner box — Q1 to Q3, middle 50% of data
- Whiskers — full range from min to max
- Width — wider = more data at that level
Violin Plot vs Box Plot
Feature
Shows distribution shape
Reveals data density
Shows median & quartiles
Detects bimodal data
Good for small datasets
Violin Plot
Box Plot
What the Results Look Like
How to Read a Violin Plot
Reading a violin plot is straightforward once you know what each part means. Start from the overall shape then look at the inner details.
Step 1 — Look at the overall shape
Wide in the middle means data clusters around the center. Wide at top or bottom means data is skewed that way. Two bulges means two groups exist within the data.
Step 2 — Find the inner lines
The thickest center line is the median. The two outer dashed lines are Q1 (25th percentile) and Q3 (75th percentile). The space between them contains the middle 50% of your data.
Step 3 — Check the width at different heights
The wider the violin at any point, the more data values exist there. Very wide at 25 and narrow at 50 means far more data points sit around the value 25.
Step 4 — Look at the tips
The very top and bottom show max and min values. Very thin pointy tips suggest rare outliers. A rounded tip suggests values gradually trail off.
Common Shapes and What They Mean
Single Peak (Unimodal)
One wide bulge in the center. Data clusters around one main value. Common in heights, test scores, and natural measurements.
Two Peaks (Bimodal)
Two separate bulges. Data has two distinct groups. Example: exam scores where half the class prepared and half didn’t.
Skewed Right
Wide at the bottom, narrow long tail at top. Most values are low with a few very high. Common in income and sales data.
Skewed Left
Wide at top, narrow long tail at bottom. Most values are high with a few very low. Common in age-at-retirement data.
When to Use a Violin Plot
Violin plots work best when the shape of your data matters — not just the average
- You have 15 or more data points per group
- Comparing 2–6 groups side by side
- You suspect data is skewed or bimodal
- Writing a research paper or report
- Distribution shape matters to your analysis
- Fewer than 15 data points total
- Exact values matter more than distribution
- Your audience is non-technical
- Comparing more than 8 groups at once
- A simple bar chart would communicate better
Who Uses Violin Plots?
Academic Research
Comparing experimental results across treatment groups, visualizing student performance, and presenting findings in papers.
Business Analytics
Comparing sales across regions, evaluating A/B test results, and analyzing customer segments or KPI distributions.
Healthcare & Medicine
Comparing patient outcomes between treatments, visualizing clinical trial results, and supporting evidence-based decisions.
Data Science
Exploratory data analysis, feature distribution visualization, and model performance comparison across datasets.
Frequently Asked Questions
Yes — 100% free. No account, no registration, no payment. Just open the page, enter your data, and create your violin plot. There are no limits on how many times you can use it.
You need a minimum of 3 values, but violin plots work best with 15 or more. For group comparisons, aim for at least 15 values per group for a meaningful result.
Select Compare Multiple Categories in Step 1. Enter all your numbers first, then a category label for each number. For example: values 85, 90, 78, 95 with categories Class A, Class A, Class B, Class B.
Basic Violin is clean and simple. With Quartiles is best for research showing Q1, median, Q3. Median Highlighted is best when the median is the key number. Horizontal is useful for long category names.
No. Your data is only used to generate the chart and is never saved, logged, or shared. Once the plot is created the data is discarded immediately.
Yes. The PNG download is 300 DPI — publication quality. Use it freely in academic papers, reports, or presentations. No attribution required.
Yes. The tool is fully responsive and works on any screen size — phone, tablet, or desktop.
Just numbers separated by commas — for example: 12, 15, 18, 20, 25. Decimals work too: 1.5, 2.3, 4.7. No headers, no spreadsheets, no special formatting needed.
