Applied Data Analysis in Python
In [1]:
%matplotlib inline
from pandas import Series, DataFrame
import pandas as pd
from sklearn.cluster import KMeans
from sklearn.datasets import make_blobs
data, true_labels = make_blobs(n_samples=500, centers=4, random_state=6)
points = DataFrame(data, columns=["x", "y"])
inertia_values = []
r = pd.RangeIndex(2, 8)
for n_clusters in r:
kmeans = KMeans(n_clusters=n_clusters).fit(points)
inertia_values.append(kmeans.inertia_)
inertia = Series(inertia_values, name="inertia", index=r)
inertia.plot()
Out[1]:
