means.py

from sklearn.cluster import KMeans

import geocoding

max_k = len(geocoding.coordenadas)
inertias = []
for k in range(2, max_k + 1):
    modelo = KMeans(n_clusters=k, random_state=42)
    modelo.fit(geocoding.coordenadas)
    inertias.append(modelo.inertia_)