## Decathlon example from the documentation of the 'FactoMineR' package

library(FactoMineR)
data(decathlon)

es.pca = PCA(decathlon[ , 1:10], scale.unit=TRUE, ncp=5, graph=T)
#decathlon: the data set used
#scale.unit: to choose whether to scale the data or not
#ncp: number of dimensions kept in the result
#graph: to choose whether to plot the graphs or not 

res.pca = PCA(decathlon[,1:12],
              scale.unit=TRUE, ncp=5, quanti.sup=c(11: 12), graph=T) 

#decathlon: the data set used
#scale.unit: to choose whether to scale the datas or not
#ncp: number of dimensions kept in the result
#quanti.sup: vector of the indexes of the quantitative supplementary variables
#graph: to choose whether to plot the graphs or not

plot.PCA(res.pca, axes=c(1, 2), choix="ind", habillage="ind")#13)
#res.pca: the result of a PCA
#axes: the axes to plot
#choix: the graph to plot ("ind" for the individuals, "var" for the variables)
#habillage: to choose the colours of the individuals: no colour ("none"), a colour for each individual ("ind") or to colour the individuals according to a categorical variable (give the number of the qualitative variable)

dimdesc(res.pca, axes=c(1,2))
#res.pca: the result of a PCA
#axes: the axes chosen