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Python – seaborn.pairplot() method

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  • Difficulty Level : Medium
  • Last Updated : 15 Jul, 2020
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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 problems faced by Matplotlib; the problems are ?

  • Default Matplotlib parameters
  • Working with data frames

As Seaborn compliments and extends Matplotlib, the learning curve is quite gradual. If you know Matplotlib, you are already half way through Seaborn.

seaborn.pairplot() :

To plot multiple pairwise bivariate distributions in a dataset, you can use the pairplot() function. This shows the relationship for (n, 2) combination of variable in a DataFrame as a matrix of plots and the diagonal plots are the univariate 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. If a dict, 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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