# Using K‐Means to Solve Real‐Life Problems

Suppose you are a clothing designer, and you have been tasked with designing a new series of Bermuda shorts. One of the design problems is that you need to come up with a series of sizes so that it can fit most people. Essentially, you need to have a series of sizes of people with different:

- Waist Circumference
- Upper Leg Length

So, how do you find the right combination of sizes? This is where the K‐Means algorithm comes in handy. The first thing you need to do is to get ahold of a dataset containing the measurements of a group of people (of a certain age range). Using this dataset, you can apply the K‐Means algorithm to group these people into clusters based on the specific measurement of their body parts. Once the clusters are found, you would now have a very clear picture of the sizes for which you need to design.

For the dataset, you can use the Body Measurement dataset from `https://data.world/rhoyt/body‐...`