center has the mean of our data before scaling. # Get row coordinates head ( get_coordinates ( X, margin = 1 ) ) #> F1 F2. PCA is based on finding the eigenvectors of the sample. # Load data data ( 'iris' ) # Compute principal components analysis X 1 qualitative variable was removed: Species. Centering the data is not a requirement it does however simplify notation and computations.
