Python – seaborn.boxenplot() method

Last Updated : 18 Aug, 2020

Prerequisite : Fundamentals of Seaborn

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. There is just something extraordinary about a well-designed visualization. The colors stand out, the layers blend nicely together, the contours flow throughout, and the overall package not only has a nice aesthetic quality, but it provides meaningful insights to us as well.

seaborn.boxenplot()

Draw an enhanced box plot for larger datasets. This style of plot was originally named a “letter value” plot because it shows a large number of quantiles that are defined as “letter values”. It is similar to a box plot in plotting a nonparametric representation of a distribution in which all features correspond to actual observations. By plotting more quantiles, it provides more information about the shape of the distribution, particularly in the tails.

Syntax : seaborn.boxenplot(parameters)

Parameters :

x, y, hue : Inputs for plotting long-form data.

data : Dataset for plotting.

order, hue_order : Order to plot the categorical levels in, otherwise the levels are inferred from the data objects.

orient : Orientation of the plot (vertical or horizontal).

color : Color for all of the elements, or seed for a gradient palette.

palette : Colors to use for the different levels of the hue variable.

saturation : Proportion of the original saturation to draw colors at.

width : Width of a full element when not using hue nesting, or width of all the elements for one level of the major grouping variable.

dodge : When hue nesting is used, whether elements should be shifted along the categorical axis.

k_depth : The number of boxes, and by extension number of percentiles, to draw.

linewidth : Width of the gray lines that frame the plot elements.

scale : Method to use for the width of the letter value boxes.

outlier_prop : Proportion of data believed to be outliers.

showfliers : If False, suppress the plotting of outliers.

ax : Axes object to draw the plot onto, otherwise uses the current Axes.

kwargs : Other keyword arguments

Returns : Returns the Axes object with the plot drawn onto it.

Below is the implementation of above method with some examples :

Example 1:

# importing packages 
import seaborn as sns 
import matplotlib.pyplot as plt 
  
# loading dataset 
data = sns.load_dataset("tips") 
  
# plot the boxenplot 
sns.boxenplot(x = "day", y = "total_bill",  
              data = data) 
plt.show() 

Output :

Example 2:

# importing packages 
import seaborn as sns 
import matplotlib.pyplot as plt 
  
# loading dataset 
data = sns.load_dataset("tips") 
  
# plot the boxenplot 
# hue by sex 
# width of 0.8 
sns.boxenplot(x ="day", y = "total_bill", hue = "sex",  
              data = data, width = 0.8) 
plt.show() 

Output :

Example 3:

# importing packages 
import seaborn as sns 
import matplotlib.pyplot as plt 
  
# loading dataset 
data = sns.load_dataset("tips") 
  
# plot the boxenplot 
# orient to horizontal 
sns.boxenplot(x = "total_bill", y = "size",  
              data = data, orient ="h") 
plt.show() 