Exercise

K-means segmentation averages

In this exercise, you will explore the average column values for a 3-segment solution with K-means. As part of the test & learn exploration process, visually inspecting the segmentation solutions is critical to identify the most business relevant option.

The seaborn as sns, and matplotlib.pyplot as plt. Also, we have run a 3-segment solution with K-means and loaded the dataset with assigned segment labels as wholesale_kmeans3 DataFrame.

Instructions

100 XP

Group by the segment label and calculate average column values.
Print the average column values per each segment.
Create a heatmap on the average column values per each segment.
Display the chart.