How to do K-Means clustering on data that goes beyond 3 dimensions?

I have done K-means clustering before but always on datasets that could be plotted in a 2D or 3D space. Right now I have a 35*6 matrix and need to make clusters based on those 6 dimensions. How can I program these clusters and still be able to retrieve the data to know which data point is in which group? Since I don't have any idea how to cluster past these 3 dimensions I don't have written any script yet, that's why I am only looking for some guidance and direction to understand how to do it and begin writing.

Thanks in advance, I really appreciate the help!

[Kelly Kearney]

The process is exactly the same as for 2 or 3 dimensions:

idx = kmeans(rand(35,6), 6);

Visualizing the results may be more complicated...

[Pietro Quinzani]

@Kelly Kearney Oh cool, so it's easier than I thought. I don't really need to visualize it though but how can I track through idx in which group is each data point?