While using K-means, how do I represent IP addresses and languages on the coordinate axis?
If your data doesn't map in an obvious way onto vectors of continuous real numbers, don't use K-means.

To use K-means clustering you need to have a well defined distance between any two points in the space.  To do that you need to have a notion of distance for each axis.

Typically discrete classifications like "language" don't have any natural mapping onto real numbers.