Violin plots are yet another way to represent categorical data. Violin plots combine both box plot and kernel distribution estimation

In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable. Kernel density estimation is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample.

We can obtain a lot of information from these plots and have an idea about the relationship between several variables by plotting them.