We can pass various parameters to PairGrid like hue, hue_kws, vars, x_vars, y_vars, palette, marker (diamond, plus sign, circle, square) etc.
We can pass various parameters to pairplot like kind, diag_kind, hue, vars, x_vars, y_vars, height etc.
Lets explore Pair Grid and Pair Plot using Iris dataset.
Step 1: Import required libraries
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
Step 2: Load Tips datasets
iris=sns.load_dataset(‘iris')
iris.head()
Step 3: Explore data using Pair Grid
Draw scatter plots on all grid cells
x = sns.PairGrid(iris)
x = x.map(plt.scatter)
Draw histograms on diagonals and scatter plots on rest of the grid cells
x = sns.PairGrid(iris)
x = x.map_diag(plt.hist)
x = x.map_offdiag(plt.scatter)
Draw histograms on diagonals, scatter plots at top and KDE plots at bottom
x = sns.PairGrid(iris)
x = x.map_diag(plt.hist)
x = x.map_upper(plt.scatter)
x = x.map_lower(sns.kdeplot)
Add hue and legend
x = sns.PairGrid(iris, hue='species')
x = x.map_diag(plt.hist)
x = x.map_offdiag(plt.scatter)
x = sns.PairGrid(iris, hue='species')
x = x.map_diag(plt.hist)
x = x.map_offdiag(plt.scatter)
x = x.add_legend()
x = sns.PairGrid(iris, hue='species')
x = x.map_diag(plt.hist)
x = x.map_upper(plt.scatter)
x = x.map_lower(sns.kdeplot)
x = x.add_legend()
x = sns.PairGrid(iris, hue='species', palette='Blues_d')
x = x.map_diag(plt.hist, histtype='step', linewidth=2, edgecolor='black')
x = x.map_offdiag(plt.scatter, edgecolor='black')
x = x.add_legend()
x = sns.PairGrid(iris, hue='species', hue_kws={‘marker‘ : [‘D', ‘s', ‘+']})
x = x.map(plt.scatter, s=30, edgecolor='black')
x = x.add_legend()
Add specific variables
x = sns.PairGrid(iris, vars=[‘petal_length', ‘petal_width'])
x = x.map_diag(plt.hist)
x = x.map_offdiag(plt.scatter)
x = sns.PairGrid(iris, x_vars=[‘petal_length', ‘petal_width'], y_vars=[‘sepal_length', ‘sepal_width'])
x = x.map(plt.scatter)
Step 4: Explore data using Pair Plot
sns.pairplot(iris)
Add regression line to scatter plot
sns.pairplot(iris, kind='reg')
Change diagonal to KDE, by default its histogram
sns.pairplot(iris, diag_kind='kde')
Add hue parameter
sns.pairplot(iris, hue='species')
sns.pairplot(iris, hue='species', kind='reg')
sns.pairplot(iris, hue='species', kind='reg', diag_kind='kde')
sns.pairplot(iris, hue='species', kind='reg', diag_kind='hist')
Add specific variables
sns.pairplot(iris, vars=[‘petal_length', ‘petal_width'], height=4)
sns.pairplot(iris, x_vars=[‘petal_length', ‘petal_width'], y_vars=[‘sepal_length', ‘sepal_width'])
You can download my Jupyter notebook from here. I recommend to also try above code with Tips dataset.
