if (!(require(FactoMineR))) install.packages("FactoMineR") if (!(require(Factoshiny))) install.packages("Factoshiny") if (!(require(FactoInvestigate))) install.packages("FactoInvestigate") if (!(require(missMDA))) install.packages("missMDA") ### Import dataset setwd("C:/Users/husson/AOBox/Travail/huss/Divers/site_Facto/more/") Expert <- read.table("http://factominer.free.fr/more/Expert_wine.csv", header=TRUE, sep=";", row.names=1) Expert <- read.table("Expert_wine.csv", header=TRUE, sep=";", row.names=1) ### Perform PCA library(FactoMineR) res.pca <- PCA(Expert,quanti.sup=29:30,quali.sup=1) summary(res.pca) plot(res.pca,hab=1,cex=.8) ### Use of Factoshiny to draw interactive graphs library(Factoshiny) res.shiny <- PCAshiny(Expert) ## Automatic interpretation library(FactoInvestigate) Investigate(res.pca,"Automatic.html") ### Import dataset for Multple Factor Analysis (MFA) Expert <- read.table("http://factominer.free.fr/more/Expert_wine.csv",header=TRUE, sep=";", row.names=1) Consu <- read.table("http://factominer.free.fr/more/Consumer_wine.csv",header=T,sep=";",row.names=1) Stud <- read.table("http://factominer.free.fr/more/Student_wine.csv",header=T,sep=";",row.names=1) Pref <- read.table("http://factominer.free.fr/more/Preference_wine.csv",header=T,sep=";",row.names=1) Expert <- read.table("Expert_wine.csv",header=TRUE, sep=";", row.names=1) Consu <- read.table("Consumer_wine.csv",header=T,sep=";",row.names=1) Stud <- read.table("Student_wine.csv",header=T,sep=";",row.names=1) Pref <- read.table("Preference_wine.csv",header=T,sep=";",row.names=1) complet <- cbind.data.frame(Expert[,1:28],Consu[,2:16],Stud[,2:16],Pref) palette(c("black","red","blue","orange","darkgreen","maroon","darkviolet")) ### Perform MFA res.mfa <- MFA(complet,group=c(1,27,15,15,60),type=c("n",rep("s",4)), num.group.sup=c(1,5), name.group=c("Label","Expert","Consumer","Student","Preference")) summary(res.mfa) resMFA.shiny <- MFAshiny(res.mfa)