pca_interpret {ggfacto}

Colored Table to Help Interpretation of Principal Component Analysis

Description

Colored Table to Help Interpretation of Principal Component Analysis

Usage

pca_interpret(res.pca, axes = 1:3)

Arguments

res.pca

The result of FactoMineR::PCA.

axes

The axes to print, as a numeric vector.

Value

A tibble of class tabxplor

Examples

data(mtcars, package = "datasets")
mtcars <- mtcars[1:7] |> dplyr::rename(weight = wt)
res.pca <- FactoMineR::PCA(mtcars, graph = FALSE)
pca_interpret(res.pca)