I was studying about principal component analysis and while studying it I came to know that varimax function helps in understanding the PCA but I am not able to understand it and how it helps in PCA .
my.wines <- read.csv(“http://steviep42.bitbucket.org/YOUTUBE.DIR/wines.csv”, header=TRUE
my.prc <- prcomp(my.wines[,-1], center=TRUE, scale=TRUE)
screeplot(my.prc, main=“Scree Plot”, xlab=“Components”)
screeplot(my.prc, main=“Scree Plot”, type=“line” )
biplot(my.prc, cex=c(1, 0.7))
my.var <- varimax(my.prc$rotation)