In this chapter we implemented the K-means algorithm—a simple and easy-to-implement cluster analysis technique that is vulnerable to problems in some cases. This approach can be applied to a wide variety of application domains and performs in a fairly efficient manner. Other techniques for cluster analysis do exist, and we urge you to consider some of them for comparison purposes.

As part of the implementation, we revisited the notion of iteration and presented a more detailed view of the while statement. We utilized lists—specifically, parallel lists—and dictionaries as a means of organizing our data. Finally, we created a visualization for our cluster analysis results.