import matplotlib.pyplot as plt 
from matplotlib import style 
style.use("ggplot")
import numpy as np 
from sklearn.cluster import KMeans

X = np.array([[1,2],[1.5, 1.8],[5, 8],[8,8],[1, 0.6],[9,11]])

clf = KMeans(n_clusters=2)
clf.fit(X)

centroids = clf.cluster_centers_
labels = clf.labels_

colors = 10*["g.", "r.", "c.", "b.", "k."]

for i in range(len(X)):
    plt.plot(X[i][0], X[i][1], colors[labels[i]], markersize = 25)

plt.scatter(centroids[:,0], centroids[:,1], marker='x', s=150, linewidths=5)
plt.show()
import matplotlib.pyplot as plt 
from matplotlib import style 
style.use("ggplot")
import numpy as np 
from sklearn.cluster import KMeans

X = np.array([[1,2],[1.5, 1.8],[5, 8],[8,8],[1, 0.6],[9,11]])

clf = KMeans(n_clusters=2)
clf.fit(X)

centroids = clf.cluster_centers_
labels = clf.labels_

colors = 10*["g.", "r.", "c.", "b.", "k."]

for i in range(len(X)):
    plt.plot(X[i][0], X[i][1], colors[labels[i]], markersize = 25)

plt.scatter(centroids[:,0], centroids[:,1], marker='x', s=150, linewidths=5)
plt.show()