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()
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)
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