用python 画出sklearn生成的不同类的数据的二维图像

Question

生成数据

import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
from sklearn.datasets.samples_generator import make_blobs
center = [[1, 1],[-1, -1],[1, -1]]
cluster_std = 0.3
X, labels = make_blobs(n_samples=100, centers=center, n_features=2, \
                       cluster_std=cluster_std, random_state=0)

画出数据集

unique_lab = set(labels)
colors = plt.cm.Spectral(np.linspace(0, 1, len(unique_lab)))
for k, col in zip(unique_lab, colors):
    x_k = X[labels == k]
    plt.plot(x_k[:, 0], x_k[:, 1], 'o', markerfacecolor=colors, markeredgecolor='k',\
             markersize=14)
plt.title('dataset by make_blob')
plt.show()  

报错：

Answer 1

更换了另一种方法，就好了
plt.scatter(X[:,0],X[:,1],'o',c=lables)