Visualising K-Means clusters for 3D data in R I have an excel file that contains 485k rows x 3 columns of integer values. Sample data:
cluster.x    cluster.y    cluster.z
1            3            3
3            1            4
4            2            5
...

I did a kmeans clustering with 6 clusters, but I am figuring out what is the best way to display the result. I plotted it using plot3d() as shown below, but it is hard to differentiate different clusters since the values are all integers.
Does anyone have any suggestions? If possible, I also want it to be able to visualise how many data points there are in each cluster (e.g a bubble plot where the size of the bubble depicts the number of data points).
Is it necessary to plot all points? If not, you can use plot3d to display 6 bubbles centered at each clusters center. You can use mean within distance for each cluster to set the radius of each cluster (you will have to normalize this) and a color range to display the number of points in each cluster.