plot.PCA: Draw the Principal Component Analysis (PCA) graphs

In FactoMineR: Multivariate Exploratory Data Analysis and Data Mining

Draw the Principal Component Analysis (PCA) graphs

Description

Plot the graphs for a Principal Component Analysis (PCA) with supplementary individuals, supplementary quantitative variables and supplementary categorical variables.

Usage

## S3 method for class 'PCA'
plot(x, axes = c(1, 2), choix = c("ind","var","varcor"),
    ellipse = NULL, xlim = NULL, ylim = NULL, habillage="none", 
    col.hab = NULL, col.ind="black", col.ind.sup="blue", 
    col.quali="magenta", col.quanti.sup="blue", col.var="black",
    label = c("all","none","ind","ind.sup","quali","var","quanti.sup"),
	invisible = c("none","ind","ind.sup","quali","var","quanti.sup"), 
    lim.cos2.var = 0., title = NULL, palette=NULL,
    autoLab = c("auto","yes","no"), new.plot = FALSE, select = NULL, 
	unselect = 0.7, shadowtext = FALSE, legend = list(bty = "y", x = "topleft"),
	graph.type = c("ggplot","classic"), ggoptions = NULL, ...)
    

Arguments

x	an object of class PCA
axes	a length 2 vector specifying the components to plot
choix	the graph to plot ("ind" for the individuals, "var" for the variables, "varcor" for a graph with the correlation circle when scale.unit=FALSE)
ellipse	boolean (NULL by default), if not null, draw ellipses around the individuals, and use the results of coord.ellipse
xlim	range for the plotted 'x' values, defaulting to the range of the finite values of 'x'
ylim	range for the plotted 'y' values, defaulting to the range of the finite values of 'y'
habillage	give no color for the individuals ("none"), a color for each individual ("ind"), or color the individuals among a categorical variable (give the number of the categorical variable)
col.hab	a vector with the color to use for the individuals
col.ind	a color for the individuals only if there is not habillage
col.ind.sup	a color for the supplementary individuals only if there is not habillage
col.quali	a color for the categories of categorical variables only if there is not habillage
col.quanti.sup	a color for the quantitative supplementary variables
col.var	a color for the variables
label	a list of character for the elements which are labelled (by default, all the elements are labelled ("ind", ind.sup", "quali", "var", "quanti.sup"))
invisible	string indicating if some points should not be drawn ("ind", "ind.sup" or "quali" for the individual graph and "var" or "quanti.sup" for the correlation circle graph)
lim.cos2.var	value of the square cosinus under the variables are not drawn
title	string corresponding to the title of the graph you draw (by default NULL and a title is chosen)
palette	the color palette used to draw the points. By default colors are chosen. If you want to define the colors : palette=palette(c("black","red","blue")); or you can use: palette=palette(rainbow(30)), or in black and white for example: palette=palette(gray(seq(0,.9,len=25)))
autoLab	if autoLab="auto", autoLab is equal to "yes" if there are less than 50 elements and "no" otherwise; if "yes", the labels of the drawn elements are placed in a "good" way (can be time-consuming if many elements), and if "no" the elements are placed quickly but may overlap
new.plot	boolean, if TRUE, a new graphical device is created; only used when graph.type="classic"
select	a selection of the elements that are drawn; see the details section
unselect	may be either a value between 0 and 1 that gives the transparency of the unselected objects (if unselect=1 the transparceny is total and the elements are not drawn, if unselect=0 the elements are drawn as usual but without any label) or may be a color (for example unselect="grey60")
shadowtext	boolean; if true put a shadow on the labels (rectangles are written under the labels which may lead to difficulties to modify the graph with another program); only used when graph.type="classic"
legend	a list of arguments that defines the legend if needed (when individuals are drawn according to a variable); see the arguments of the function legend
graph.type	a character that gives the type of graph used: "ggplot" or "classic"
ggoptions	a list that gives the graph options when grah.type="ggplot" is used. See the optines and the default values in the details section
...	further arguments passed to or from other methods, such as cex, cex.main, ...

Details

The argument autoLab = "yes" is time-consuming if there are many labels that overlap. In this case, you can modify the size of the characters in order to have less overlapping, using for example cex=0.7.
The select argument can be used in order to select a part of the elements (individuals if you draw the graph of individuals, or variables if you draw the graph of variables) that are drawn. For example, you can use:
select = 1:5 and then the elements 1:5 are drawn.
select = c("name1","name5") and then the elements that have the names name1 and name5 are drawn.
select = "coord 10" and then the 10 elements that have the highest (squared) coordinates on the 2 chosen dimensions are drawn.
select = "contrib 10" and then the 10 elements that have the highest contribution on the 2 dimensions of your plot are drawn.
select = "cos2 5" and then the 5 elements that have the highest cos2 on the 2 dimensions of your plot are drawn.
select = "dist 8" and then the 8 elements that have the highest distance to the center of gravity are drawn.

ggoptions is a list that gives some ggplot2 options when the graph.type="ggplot" is used. Use for instance ggoptions(list(size=3,title.size=10,bg.color="orange")) if you want to modify the size of the points and labels, the title size and the background color.
Below you can see the options and the default values:
size = 4, #label size (point size = size/3)
point.shape = 19, #points shape
line.lty = 2, #origin linetypes (0="blank", 1="solid", 2="dashed", 3="dotted",...)
line.lwd = 0, #origin lines width
line.color = "black", #origin lines color
segment.lty = 1, #arrow linetypes (0="blank", 1="solid", 2="dashed", 3="dotted",...)
segment.lwd = 0, #arrow width
circle.lty = 1, #circle linetypes (0="blank", 1="solid", 2="dashed", 3="dotted",...)
circle.lwd = 0, #circle width
circle.color = "black", #circle color
low.col.quanti = "blue", #for quantitative variables, low color to be used
high.col.quanti = "red3", #for quantitative variables, high color to be used

Value

Returns the individuals factor map and the variables factor map.

Author(s)

Francois Husson [e-mail]

See Also

PCA

Examples

data(decathlon)
res.pca <- PCA(decathlon, quanti.sup = 11:12, quali.sup = 13)
plot(res.pca, habillage = 13, cex=0.8)
## Not run: 
plot(res.pca, habillage = "cos2")
plot(res.pca, habillage = "100m")
plot(res.pca, habillage = c("Competition","100m"))

## End(Not run)
## To automatically draw ellipses around the barycentres of the categorical variables
plotellipses(res.pca)

## Not run: 
## Selection of some individuals
plot(res.pca,select="contrib 7") # plot the 7 individuals with the highest contribution 
plot(res.pca,select="cos2 0.8")  # plot the individuals with cos2 greater than 0.8
plot(res.pca,select="cos2 5")    # plot the 5 individuals with the highest cos2 
plot(res.pca,choix="var",select="cos2 0.6")  # plot the variables with cos2 greater than 0.6

plot(res.pca,habillage="100m",
   ggoptions=list(low.col.quanti="grey90",high.col.quanti="grey10"),legend=list(x="bottom"))

## You can modify the ggplot graphs as ususal with ggplot2
require(ggplot2)
gr <- plot(res.pca)
gr + theme(panel.grid.major = element_blank(),
   plot.title=element_text(size=14, color="blue"),
   axis.title = element_text(size=12, color="red"))

## To draw classical R graphs
plot(res.pca, graph.type = "classic")

## End(Not run)

FactoMineR documentation built on May 29, 2024, 3:36 a.m.