pca_interpret {ggfacto} | R Documentation |
Colored Table to Help Interpretation of Principal Component Analysis
pca_interpret(res.pca, axes = 1:3)
res.pca |
The result of |
axes |
The axes to print, as a numeric vector. |
A tibble of class tabxplor
data(mtcars, package = "datasets")
mtcars <- mtcars[1:7] |> dplyr::rename(weight = wt)
res.pca <- FactoMineR::PCA(mtcars, graph = FALSE)
pca_interpret(res.pca)