Python – seaborn.pairplot() method

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	Description	Value
data	Tidy (long-form) dataframe where each column is a variable and  each row is an observation.	DataFrame
hue	Variable in “data“ to map plot aspects to different colors.	string (variable name), optional
palette	Set of colors for mapping the “hue“ variable. If a dict, keys should be values  in the “hue“ variable. vars : list of variable names, optional	dict or seaborn color palette
{x, y}_vars	Variables 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
dropna	Drop 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 :