plot_pca: Create principal components analysis plot.

In pentalibra/ggcluster: Tools for creating cluster plots, tree plots and dendrograms using ggplot.

Description

Create principal components analysis plot.

Usage

  plot_pca( data, labeltext = names(data), xLabel =
  "Principal component 1", yLabel = "Principal component 2",
  pca_function = princomp, labels_at_edge = TRUE,
  explode = 1.1, textsize = 3)

Arguments

data	The data used for clustering
labeltext	The labels to use for each column in the data. Defaults to names(data).
xLabel	x-axis label
yLabel	y-axis label
pca_function	The function to use for principal component analysis. This could be princomp, prcomp or factanal.
labels_at_edge	If TRUE, labels are printed at at edge of plot, otherwise labels are printed next to each point.
explode	A multiplication factor that determines the distance of each label from the point. If over-plotting of labels is a problem, then use a larger explode factor.
textsize	Text label size passed to geom_text

pentalibra/ggcluster documentation built on May 25, 2019, 12:46 a.m.