Correlation values in pairplot()

Question

Is there a way to show pair-correlation values with seaborn.pairplot(), as in the example below (created with ggpairs() in R)? I can make the plots using the attached code, but cannot add the correlations. Thanks

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

iris = sns.load_dataset('iris')
g = sns.pairplot(iris, kind='scatter', diag_kind='kde')
# remove upper triangle plots
for i, j in zip(*np.triu_indices_from(g.axes, 1)):
    g.axes[i, j].set_visible(False)
plt.show()

Does this answer your question? [Show correlation values in pairplot using seaborn in python](https://stackoverflow.com/questions/50832204/show-correlation-values-in-pairplot-using-seaborn-in-python) — iacob, Mar 18 '21 at 09:17

score 13 · Accepted Answer · answered Aug 16 '20 at 05:35

If you use PairGrid instead of pairplot, then you can pass a custom function that would calculate the correlation coefficient and display it on the graph:

from scipy.stats import pearsonr
def reg_coef(x,y,label=None,color=None,**kwargs):
    ax = plt.gca()
    r,p = pearsonr(x,y)
    ax.annotate('r = {:.2f}'.format(r), xy=(0.5,0.5), xycoords='axes fraction', ha='center')
    ax.set_axis_off()

iris = sns.load_dataset("iris")
g = sns.PairGrid(iris)
g.map_diag(sns.distplot)
g.map_lower(sns.regplot)
g.map_upper(reg_coef)

Correlation values in pairplot()

1 Answers1