Python Seaborn Categorical distribution plots: Boxen Plot

Boxen Plot is used to draw an enhanced version of the box plot for larger datasets.  This style of the plot was named "letter value" because it displays a large number of quantiles that are known as "letter value". By plotting more quartiles it becomes more informative about the shape of the distribution particularly in the tails.


seaborn.boxenplot(*, x=None, y=None, hue=None, data=None, order=None, 
hue_order=None, orient=None, color=None, palette=None, saturation=0.75, 
width=0.8, dodge=True, k_depth='tukey', linewidth=None, scale='exponential', 
outlier_prop=0.007, trust_alpha=0.05, showfliers=True, ax=None, **kwargs


  • x,y: It is input for plotting long-from data
  • data: It is used for input of Dataset for plotting.
  • orient: It is used for the orientation of the plot (vertical or horizontal).
  • color: It is the color for all of the elements.
  • palette: It is the colors to use for the different levels of the hue variable.
  • saturation: It is used as the proportion of the original saturation to draw colors at.
  • dodge : When hue nesting is used, whether elements should be shifted along the categorical axis.
  • outlier_prop : It is the proportion of data believed to be outliers.
  • showfliers : It is a boolean value. If False, it will suppress the plotting of outliers.


import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
data = sns.load_dataset("taxis")

Creating a simple boxen plot 




Creating a boxen plot for all the numerical variables present in the dataframe




Creating a boxen plot for a numerical value and two categorical variables




Creating boxen plot by using orientation which will be horizontally

sns.boxenplot(x="total",y='payment',hue='color',data=data, orient ="h")



Fri, 03/05/2021 - 22:38

Authored by

Devanshi, is working as a Data Scientist with iVagus. She has expertise in Python, NumPy, Pandas and other data science technologies.