# k-means clustering on percentages

Can we do k-means clustering on percentage data (like 56%, 44%, 22%, 13%, etc.)?
There is a data set, and data in various parts are measured in percentages.

• You can apply K-Means on any data as long as your covariates are expressed as numericals. Is it a good idea?! We don't know by simply examining the data range (i.e. percentages), data visualization, domain knowledge and testing are imperative. – Ramalho Oct 17 '14 at 11:20

Because many clustering algorithms (very much including k-means) are thrown off by data in which the variables have different ranges (cf., this excellent CV thread: Why does gap statistic for k-means suggest one cluster, even though there are obviously two of them?), it is very common to normalize all variables first (i.e., convert the range to $[0,\ 1]$, see here). In this way, it is common to run k-means on data where all variables are expressed in essence as percentages.