import numpy as np;
from sklearn import datasets;
import matplotlib.pyplot as plt;
import scipy.stats as st;

#第3章第3.1.1节，例3.2
Iris_ds = datasets.load_iris();
X = Iris_ds.data;
y = Iris_ds.target;

fig = plt.figure();
ax1 = fig.add_subplot(231);
ax1.scatter(X[:, 0], X[:, 1]);
ax2 = fig.add_subplot(232);
ax2.scatter(X[:, 0], X[:, 2]);
ax3 = fig.add_subplot(233);
ax3.scatter(X[:, 0], X[:, 3]);
ax3 = fig.add_subplot(234);
ax3.scatter(X[:, 1], X[:, 2]);
ax3 = fig.add_subplot(235);
ax3.scatter(X[:, 1], X[:, 3]);
ax3 = fig.add_subplot(236);
ax3.scatter(X[:, 2], X[:, 3]);
plt.show();

展示矩阵（略），结果参见《数据分析与数据挖掘建模与工具》。