What is a Violin Plot and When Should You Use It?
The violin plot is one of the most elegant and informative charts in modern data science. It combines the summary statistics of a box plot with the density estimation of a histogram. But for many, it remains a mystery.
What is a Violin Plot?
A violin plot depicts distributions of numeric data for one or more groups using density curves. The width of each curve corresponds to the approximate frequency of data points in each region. Densely populated areas are wider, while sparsely populated areas are narrower.
Violin Plot vs Box Plot
Why use a violin plot instead of the classic box plot?
Box Plot
Shows summary statistics: Median, IQR (25th-75th percentile), and outliers.
Limitation: It hides the shape of the distribution. A bimodal distribution (two peaks) looks the same as a unimodal one.
Violin Plot
Shows the full distribution shape (KDE) plus summary statistics inside.
Advantage: Reveals hidden patterns like multiple peaks (multimodality) that box plots miss.
When to Use a Violin Plot
- Large Datasets: When you have enough points to estimate density smoothly.
- Comparing Distributions: When you want to compare the shape of data across groups (e.g., gene expression in Control vs Treated).
- Detecting Multimodality: When you suspect your data has subpopulations (e.g., fast and slow responders).
How to Create One
Creating violin plots in Excel is difficult (see our guide here).
The easiest way is to use Plotivy. Just upload your data and ask for a violin plot. You can even combine it with a box plot inside for the ultimate data summary.
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