ggpca_cor_circle: Correlation Circle Plot for Principal Component Analysis

In ggfacto: Graphs for Correspondence Analysis

Correlation Circle Plot for Principal Component Analysis

Description

Correlation Circle Plot for Principal Component Analysis

Usage

ggpca_cor_circle(
  res.pca,
  axes = c(1, 2),
  proj = FALSE,
  interactive = TRUE,
  text_size = 3
)

Arguments

res.pca	The result of FactoMineR::PCA.
axes	The axes to print, as a numeric vector of length 2.
proj	Set to 'TRUE' to print projections of vectors over the two axes.
interactive	By default an html interactive plot is done. Set to 'FALSE' to get a normal ggplot graph.
text_size	Size of the texte.

Value

A ggplot.

Examples

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

ggfacto documentation built on Oct. 3, 2024, 1:08 a.m.