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Python – seaborn.pairplot() method

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  • Difficulty Level : Medium
  • Last Updated : 11 Nov, 2022
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Prerequisite: Seaborn Programming Basics

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps resolve the two major issues while working with Matplotlib:

  • Default Matplotlib parameters
  • Working with data frames

As Seaborn compliments and enhances Matplotlib, the learning curve is quite gradual. If you are familiar with Matplotlib, you are already halfway done with Seaborn.

seaborn.pairplot() :

To plot multiple pairwise bivariate distributions in a dataset, you can use the .pairplot() function. 

The diagonal plots are the univariate plots, and this displays the relationship for the (n, 2) combination of variables in a DataFrame as a matrix of plots.

                        seaborn.pairplot( data, \*\*kwargs )

Seaborn.pairplot uses many arguments as input, main of which are described below in form of table:

Arguments                          DescriptionValue                                                                                                        
dataTidy (long-form) dataframe where each column is a variable, and each row is an observation.DataFrame
hueVariable in “data“ to map plot aspects to different colors.string (variable name), optional
paletteSet of colors for mapping the “hue“ variable. In case of a dict, the keys should be values in the “hue“ variable. vars: list of variable names, optionaldict or seaborn color palette
{x, y}_varsVariables within “data“ to use separately for the rows and columns of the figure, i.e., to make a non-square plot.lists of variable names, optional
dropnaDrop missing values from the data before plotting.boolean, optional

Below is the implementation of above method:

Example 1:

Python3




# importing packages
import seaborn
import matplotlib.pyplot as plt
 
############# Main Section ############
# loading dataset using seaborn
df = seaborn.load_dataset('tips')
# pairplot with hue sex
seaborn.pairplot(df, hue ='sex')
# to show
plt.show()
 
# This code is contributed by Deepanshu Rustagi.

 
 

Output :

Example 2:

 

Python3




# importing packages
import seaborn
import matplotlib.pyplot as plt
 
############# Main Section ############
# loading dataset using seaborn
df = seaborn.load_dataset('tips')
# pairplot with hue day
seaborn.pairplot(df, hue ='day')
# to show
plt.show()
 
# This code is contributed by Deepanshu Rustagi.

 
 

Output :

 


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