library(FactoMineR)
# PCA
data(decathlon)
res_pca <- FactoMineR::PCA(decathlon, scale.unit = TRUE, quanti.sup = 11:12,
quali.sup = 13, graph = FALSE)
## Get results summary for the first 10 individuals along the first 3 factors
summarize(res_pca, "ind", rows = 1:10, axes = 1:3)
## Get results summary for variables
summarize(res_pca, "var")
## Get results summary for supplementary continuous variables
summarize(res_pca, "quanti")
## Get results summary for supplementary categories
summarize(res_pca, "quali")
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