Lets load the dataset
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import pandas as pd
import seaborn as sns
df = sns.load_dataset('tips')
df.head()
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
Lets say we want to distinguish the peoples preference for lucnch or dinner based on days. We can do that combining the pandas with seaborn
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df['time'].groupby(df['day']).value_counts(normalize=True).rename('proportion').reset_index().set_axis(['day','time','proportion'], axis=1).pipe((sns.barplot,'data'),x='day',y='proportion',hue='time')
