Doing PCA with varimax rotation in R - r

Question

My code has gone south.
I'm importing a data 578x17 sheet from csv using the:
Data=read.csv("Data.csv", header=TRUE, sep=',', dec='.', row.names= 1 , stringsAsFactors=TRUE)
My correlations and covariance matrices are the same.
When I try to do a PCA and a PCA with a Varimax Rotation, I get the same results:
PCA=princomp(x = Data, cor = TRUE, scores = TRUE)
Varimax<-princomp(Data, rotation="varimax")
When I try to do a Varimax rotation in a different way, I get:
varimax<-varimax(PCA$rotation[,1:5])
Error in if (nc < 2) return(x) : argument is of length zero
I'm not sure whether the problem is my code, or my .csv file, but any help would be greatly appreciated!

Answer 1

varimax rotation in PCA with vegan's rda()
The basics of this answer has been taken from:
https://stats.stackexchange.com/questions/59213/how-to-compute-varimax-rotated-principal-components-in-r
suppose that the data matrix name is mydata
library(vegan)
library(pracma)
pca.env = rda(mydata, scale=T)
loading = scores(pca.env, choices=c(1,2))$species #choices determines which pc to be taken
rloading = varimax(loading)$loadings
iloading = t(pinv(rloading))
scores = scale(mydata) %*% iloading
biplot
r = range(c(rloading, scores))
plot(scores, xlim = r, ylim= r, xlab= "PC1 ", ylab= "PC2 ")
arrows(0,0, rloading[,1], rloading[,2], length=0.1, col=2)
text(rloading[,1], rloading[,2], labels = colnames(mydata), pos=3, col=2)
text(scores[,1], scores[,2], labels = rownames(mydata), pos = 3)
abline(h=0, lty=3)
abline(v=0, lty=3)