How to create seaborn violinplot with mean,median and mode displayed?

Is there a way to add a mean and a mode to a violinplot ? I have categorical data in one of my columns and the corresponding values in the next column. I tried looking into matplotlib violin plot as it technically offers the functionality I am looking for but it does not allow me to specify a categorical variable on the x axis, and this is crucial as I am looking at the distribution of the data per category. I have added a small table illustrating the shape of the data.

plt.figure(figsize=10,15)
ax=sns.violinplot(x='category',y='value',data=df)

Solution

First we calculate the the mode and means:

import seaborn as sns
import pandas as pd
from matplotlib import pyplot as plt

df = pd.DataFrame({'Category':[1,2,5,1,2,4,3,4,2],
                   'Value':[1.5,1.2,2.2,2.6,2.3,2.7,5,3,0]})

Means = df.groupby('Category')['Value'].mean()
Modes = df.groupby('Category')['Value'].agg(lambda x: pd.Series.mode(x)[0])

You can use seaborn to make the basic plot, below I remove the inner boxplot using the inner= argument, so that we can see the mode and means:

fig, ax = plt.subplots()
sns.violinplot(x='Category',y='Value',data=df,inner=None)
plt.setp(ax.collections, alpha=.3)
plt.scatter(x=range(len(Means)),y=Means,c="k")
plt.scatter(x=range(len(Modes)),y=Modes)