In [1]:

    

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


    

In [2]:

    

data = load_iris()
x = data['data']
plt.close('all')

fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.boxplot(x)
ax.set_xticklabels(data['feature_names'])
plt.show()


    

In [5]:

    

import numpy as np
y = data['target']
class_labels = data['target_names']

fig = plt.figure(2,figsize=(18,10))
sub_plt_count = 321
for t in range(0,3):
    ax = fig.add_subplot(sub_plt_count)
    y_index = np.where(y==t)[0]
    x_ = x[y_index,:]
    ax.boxplot(x_)
    ax.set_title(class_labels[t])
    ax.set_xticklabels(data['feature_names'])
    sub_plt_count +=1
plt.show()