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## Load data
data("iris")
## Compute principal components analysis
X <- pca(iris, scale = TRUE, sup_row = sample(150, 10), sup_col = 2)
## Get row coordinates
head(get_coordinates(X, margin = 1))
## Get column coordinates
head(get_coordinates(X, margin = 2))
## Get correlations between variables and dimensions
head(get_correlations(X))
## Get eigenvalues
get_eigenvalues(X)
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