Is there a way that I can easily add the axes labels for each of the subplots in Seaborn pair plot? This is related to this question but instead of adding the tick labels I want to add the axes labels as the pairplot I am having is 9*9 and I dont want to scroll down every time to check the column name.
I was hoping that it would be some thing easy like
for ax in g.axes.flat:
_ = plt.setp(ax.get_ylabels(), visible=True)
_ = plt.setp(ax.get_xlabels(), visible=True)
You first need to get all the labels from the axes (e.g. ax.xaxis.get_label_text()
) and the set the label text (ax.xaxis.set_label_text()
).
I've used a for loop and i
, j
indexing here. Its possible there's a cleaner vectorised way to do this, but at least it works.
Using the iris
sample dataset from seaborn
:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
iris = sns.load_dataset("iris")
g = sns.PairGrid(iris)
g = g.map(plt.scatter)
xlabels,ylabels = [],[]
for ax in g.axes[-1,:]:
xlabel = ax.xaxis.get_label_text()
xlabels.append(xlabel)
for ax in g.axes[:,0]:
ylabel = ax.yaxis.get_label_text()
ylabels.append(ylabel)
for i in range(len(xlabels)):
for j in range(len(ylabels)):
g.axes[j,i].xaxis.set_label_text(xlabels[i])
g.axes[j,i].yaxis.set_label_text(ylabels[j])
plt.show()
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