How to get Principal Component Data in PAM in R

Question

I create a graph using autoplot function using mtcars data and get graph like this

here my code:

library(cluster)
library(NbClust)
library(ggplot2)
library(ggfortify)
x <- mtcars
number.cluster <- NbClust(x, distance = "euclidean", min.nc = 1, max.nc = 5, method = "complete", index = "ch")
best.cluster <- as.numeric(number.cluster$Best.nc[1])
x.pam <- pam(x, best.cluster)
autoplot(x.pam, data = x, frame = T) + ggtitle("PAM MTCARS")

my question is how do i get PC1 & PC2 data Coordinate based on this graph? thank you

Answer 1

You can use layer_data() to get the data used for a ggplot object:

p <- autoplot(x.pam, data = x, frame = T) + ggtitle("PAM MTCARS")
layer_data(p, 1L) # coordinates of all points
layer_data(p, 2L) # coordinates of points that contribute to polygons

Answer 2

Your entire process is flawed. First you use complete linkage to estimate the number of clusters; but rather than using the "best" clustering found you then cluster again with PAM instead. You use Euclidean distance, but in Euclidean space k-means will usually work better than PAM - PAM shines when you don't have Euclidean geometry and cannot use k-means.

And then you want to use this PCA plot, which is heavily distorted (almost the entire variance is in the first component, the y axis is visualizing pretty much random deviation). Just use PCA if you want these coordinates, not reconstruct this from the plot.