Hi all,
In matplotlib, there is this functionality:
ax.set_visible(False)
which allows to show/hide plots in a subplot environment. This full example from Müller&Guido 2016 shows how it works:
from sklearn.datasets import load_iris
iris = load_iris()
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import numpy as np
X_train, X_test, y_train, y_test = train_test_split(iris['data'], iris['target'], random_state=0)
fig, ax = plt.subplots(3, 3, figsize=(15, 15))
plt.suptitle("iris_pairplot")
for i in range(3):
for j in range(3):
ax[i, j].scatter(X_train[:, j], X_train[:, i + 1], c=y_train, s=60)
ax[i, j].set_xticks(())
ax[i, j].set_yticks(())
if i == 2:
ax[i, j].set_xlabel(iris['feature_names'][j])
if j == 0:
ax[i, j].set_ylabel(iris['feature_names'][i + 1])
if j > i:
ax[i, j].set_visible(False)
Which gives:
Subplots to the right (j > i) are hidden.
Is there a similar function in plotly? That would be super helpful in my opinion.
Thanks in advance.