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.PairGrid() :

• Subplot grid for plotting pairwise relationships in a dataset.
• This class maps each variable in a dataset onto a column and row in a grid of multiple axes. Different axes-level plotting functions can be used to draw bivariate plots in the upper and lower triangles, and the marginal distribution of each variable can be shown on the diagonal.
• It can also represent an additional level of conditionalization with the hue parameter, which plots different subsets of data in different colors. This uses color to resolve elements on a third dimension, but only draws subsets on top of each other and will not tailor the hue parameter for the specific visualization the way that axes-level functions that accept hue will.

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

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

Below is the implementation of above method:

Example 1:

# importing packages
import seaborn
import matplotlib.pyplot as plt

# loading dataset
df = seaborn.load_dataset('tips')

# PairGrid object with hue
graph = seaborn.PairGrid(df, hue ='day')
# type of graph for diagonal
graph = graph.map_diag(plt.hist)
# type of graph for non-diagonal
graph = graph.map_offdiag(plt.scatter)
# to add legends
graph = graph.add_legend()
# to show
plt.show()
# This code is contributed by Deepanshu Rusatgi.

Output :

Example 2:

# importing packages
import seaborn
import matplotlib.pyplot as plt

# loading dataset
df = seaborn.load_dataset('tips')

# PairGrid object with hue
graph = seaborn.PairGrid(df)
# type of graph for non-diagonal(upper part)
graph = graph.map_upper(sns.scatterplot)
# type of graph for non-diagonal(lower part)
graph = graph.map_lower(sns.kdeplot)
# type of graph for diagonal
graph = graph.map_diag(sns.kdeplot, lw = 2)
# to show
plt.show()
# This code is contributed by Deepanshu Rusatgi.

Output: