A violint plot allow to visualize the distribution of a numeric variable for one or several groups.
Seaborn is particularly adapted to build it thanks to its
violin() function. Violinplots deserve more attention compared to boxplots that can sometimes hide features of the data.
⏱ Quick start
Seaborn is definitely the best library to quickly build a violin plot. It offers a dedicated
violinplot() function that roughly works as follows:🔥
# library & dataset import seaborn as sns df = sns.load_dataset('iris') # plot sns.violinplot(x=df["species"], y=df["sepal_length"])
Violin charts with
Seaborn is a python library allowing to make better charts easily. It is well adapted to build density charts thanks to its
violin function. The following charts will guide you through its usage, going from a very basic violin plot to something much more customized.
violin function parameters→ see full doc
string→ color under the curve
From the web
The web is full of astonishing charts made by awesome bloggers, (often using R). The Python graph gallery tries to display (or translate from R) some of the best creations and explain how their source code works. If you want to display your work here, please drop me a word or even better, submit a Pull Request!
👋 This document is a work by Yan Holtz. Any feedback is highly encouraged. You can fill an issue on Github, drop me a message onTwitter, or send an email pasting