We can pass various parameters to violinplot like hue, split, inner (quartile, stick), scale, scale_hue, bandwidth (bw), palette, order etc.
Lets explore Violin Plot using Tips dataset.
Step 1: Import required libraries
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
Step 2: Load Tips datasets
tips=sns.load_dataset(‘tips')
tips.head()
Step 3: Explore data using Violin Plot
sns.violinplot(x=tips[‘tip'])
sns.violinplot(x='day', y='total_bill', data=tips)
Add hue and split parameter
sns.violinplot(x='day', y='total_bill', data=tips, hue='sex')
sns.violinplot(x='day', y='total_bill', data=tips, hue='sex', split=True)
sns.violinplot(x='day', y='total_bill', data=tips, hue='sex', palette='RdBu')
sns.violinplot(x='day', y='total_bill', data=tips, hue='sex', order=[‘Sat', ‘Sun', ‘Thur', ‘Fri'])
Add inner and scale parameter
sns.violinplot(x='day', y='total_bill', data=tips, hue='smoker', inner='quartile')
sns.violinplot(x='day', y='total_bill', data=tips, hue='smoker', inner='quartile', split='True')
sns.violinplot(x='day', y='total_bill', data=tips, hue='smoker', inner='quartile', split='True', scale='count')
sns.violinplot(x='day', y='total_bill', data=tips, hue='smoker', inner='stick', split='True', scale='count')
sns.violinplot(x='day', y='total_bill', data=tips, hue='smoker', inner='stick', split='True', scale='count', scale_hue=False)
sns.violinplot(x='day', y='total_bill', data=tips, hue='smoker', inner='stick', split='True', scale='count', scale_hue=False, bw=0.1)
You can download my Jupyter notebook from here. I recommend to also try above code with Iris dataset.
