from matplotlib import pyplot as plt

from sklearn.datasets import load_iris

import numpy as np

data = load_iris()

features = data['data']

feature_names = data['feature_names']

target = data['target']

target_names = data['target_names']

labels = target_names[target]

pairs = [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]

for i, (p0, p1) in enumerate(pairs):

plt.subplot(2, 3, i + 1)

for t, marker, c in zip(range(3), ">ox", "rgb"):

plt.scatter(features[target == t, p0],

features[target == t, p1],

marker = marker, c=c)

plt.xlabel(feature_names[p0])

plt.ylabel(feature_names[p1])

plt.xticks([])

plt.yticks([])

plt.show()