ggpca_cor_circle: Correlation Circle Plot for Principal Component Analysis

In ggfacto: Graphs for Correspondence Analysis

Correlation Circle Plot for Principal Component Analysis

Description

The active variables of a principal component analysis as arrows in the circle of correlations: the coordinate of a variable on an axis is its correlation with it. Hovering a variable shows its coordinates, and its projections on the two axes. ggfacto draws it for a principal component analysis with 'profiles = FALSE' and nothing else asked for; by default, it draws the same arrows over the cloud of individuals.

Usage

ggpca_cor_circle(
  res.pca,
  axes = c(1, 2),
  proj = FALSE,
  interactive = FALSE,
  text_size = 3.5,
  lang = NULL,
  axes_names = NULL,
  axes_reverse = NULL,
  title,
  xlim,
  ylim
)

Arguments

res.pca	An analysis made with principal_component_analysis or 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	Set to 'TRUE' to get the interactive graph at once, as ggi would make it. By default, a ggplot, to which elements can be added with '+' before passing it to ggi.
text_size	Size of the text.
lang	NULL (the session's language), "en" or "fr".
axes_names	Names of all the axes, as a character vector.
axes_reverse	'1' to invert left and right, '2' to invert up and down, '1:2' for both.
title	The title of the graph.
xlim, ylim	Horizontal and vertical limits, as numeric vectors of length 2.

Value

A ggplot, or an html widget with 'interactive = TRUE'.

Examples

data(mtcars, package = "datasets")
mtcars <- mtcars[1:7] |> dplyr::rename(weight = wt)
res.pca <- principal_component_analysis(mtcars, 1:7)
ggpca_cor_circle(res.pca)
ggpca_cor_circle(res.pca) |> ggi()  # interactive

ggfacto documentation built on Sept. 23, 2026, 1:08 a.m.