iris-subplots.py

import matplotlib.pyplot as plt
import numpy as np
from sklearn.datasets import load_iris

data = load_iris()
fig, axes = plt.subplots(nrows=2, ncols=2)
fig.subplots_adjust(hspace=0.5)
fig.suptitle('Distributions of Iris Features')

for ax, feature, name in zip(axes.flatten(), data.data.T, data.feature_names):
    ax.hist(feature, bins=len(np.unique(data.data.T[0]))//2)
    ax.set(title=name[:-4].upper(), xlabel='cm')