kmeans聚類分析python

def myfunction():
    import numpy as np
    import pandas as pd
    import matplotlib.pyplot as plt
    from sklearn.cluster import KMeans
    from sklearn import datasets
    iris = datasets.load_iris()
    iris_X = iris.data
    iris_y = iris.target
    print(iris_X[:2,:])
    print(iris_y)
    X = iris_X
    y = iris_y
    #kmeans聚類
    estimator = KMeans(n_clusters=3)#構造聚類器
    estimator.fit(X)#聚類
    label_pred = estimator.labels_ #獲取聚類標簽
    print(label_pred)
    #繪制k-means結果
    x0 = X[label_pred == 0]
    x1 = X[label_pred == 1]
    x2 = X[label_pred == 2]
    plt.scatter(x0[:, 0], x0[:, 1], c="red", marker='o', label='label0')
    plt.scatter(x1[:, 0], x1[:, 1], c="green", marker='*', label='label1')
    plt.scatter(x2[:, 0], x2[:, 1], c="blue", marker='+', label='label2')
    plt.xlabel('petal length')
    plt.ylabel('sepal length')
    plt.legend(loc=2)
    plt.show()