Graph for PCA

[Mahmood Naderan]

Hi,

When I use PCA() with graph=T I see two separate graphs, one for individuals and one for variables.

Is it possible to have both in one graph, which is called biplot?

Regards,
Mahmood

[Meinhard H. Schroeder]

Yes, it’s possible with the package factoextra.

 

http://www.sthda.com/english/articles/31-principal-component-methods-in-r-practical-guide/112-pca-principal-component-analysis-essentials/#biplot

 

install.packages("FactoMineR")

library("factoextra")

library("FactoMineR")

decathlon2.active <- decathlon2[1:23, 1:10]

head(decathlon2.active[, 1:6], 4)

res.pca <- PCA(decathlon2.active, graph = FALSE)

 

fviz_pca_biplot(res.pca, repel = TRUE,

                col.var = "#2E9FDF", # Variables color

                col.ind = "#696969"  # Individuals color

)

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[Francois Husson]

Hi,
This biplot representation is not proposed in FactoMineR because it is subject to too many misinterpretations. Voluntarily, it is not proposed.
FH

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[Mahmood Naderan]

Thanks but it seems that your method doesn't show the qualitative variables.

Please see the picture at https://pasteboard.co/JROiQYi.png

> mydata <- read.csv('test.csv', header=T,row.names=1)
> mydata
     V1  V2   V3  V4 CTG
P1 73.6 0.7 74.6 3.1  A1
P2 75.2 0.7 75.8 2.8  B1
P3  6.5 0.0  7.3 2.5  B1
P4 41.4 0.3 39.2 8.9  C1
P5  5.4 0.1 18.2 1.1  A1
P6 18.8 0.3 30.3 7.3  C1
> res.pca = PCA(mydata, quali.sup=5, graph=F)
> plot(res.pca, choix="ind")
> fviz_pca_biplot(res.pca, repel = TRUE, col.var = "#FF0000", col.ind = "#0000FF")

Regards,
Mahmood

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