Run k-means

You will now build a 3 clusters with k-means clustering. We have loaded the pre-processed RFM dataset as datamart_normalized. We have also loaded the pandas library as pd.

You can explore the dataset in the console to get familiar with it.

This exercise is part of the course

Customer Segmentation in Python

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Exercise instructions

Import KMeans from the scikit-learn library.
Initialize KMeans with 3 clusters and random state 1.
Fit k-means clustering on the normalized data set.
Extract cluster labels and store them as cluster_labels.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import KMeans 
from ____.____ import ____

# Initialize KMeans
kmeans = ____(____=3, ____=1) 

# Fit k-means clustering on the normalized data set
____.____(datamart_normalized)

# Extract cluster labels
cluster_labels = ____.____

Edit and Run Code