The “Violin plot”

I came across a fascinating topic called “violin plot” when dealing with box and whisker plots. As a violinist, I was immediately intrigued by the topic. This article is an attempt to introduce my fellow analysts and machine learning aficionados to this really interesting and helpful plot. I hope you find it enjoyable.

A box plot corresponds to actual data points, it depicts the distribution of quantitative data in such a way that it is easy to compare variables or levels of a categorical variable. Except for points that are found to be “outliers”, the box depicts the dataset’s quartiles, while the whiskers extend to represent the rest of the distribution.

Violin Plots show how numerical data from various variables are distributed. It’s comparable to a Box Plot, except on each side there’s a rotated plot that provides additional information on the density estimate on the y-axis.

Violin Plots visualize the distribution of numerical data of different variables. It is similar to Box Plot but with a rotated plot on each side, giving more information about the density estimate on the y-axis. The density is mirrored and flipped over, and the resulting shape is filled in to form a violin-like picture. A violin plot has the benefit of being able to illustrate subtleties in the distribution. Although violin plots provide more information when compared to box plots, they are less popular.