What does “argument to 'which' is not logical” mean in FactoMineR MCA?

Question

I'm trying to run an MCA on a datatable using FactoMineR. It contains only 0/1 numerical columns, and its size is 200.000 * 20.

require(FactoMineR)
result <- MCA(data[, colnames, with=F], ncp = 3)

I get the following error :

Error in which(unlist(lapply(listModa, is.numeric))) : argument to 'which' is not logical

I didn't really know what to do with this error. Then I tried to turn every column to character, and everything worked. I thought it could be useful to someone else, and that maybe someone would be able to explain the error to me ;)

Cheers

Answer 1

It's difficult to tell without further input, but what you can do is:

• Find the function where the error occurred (via traceback()),

• Set a breakpoint and debug it:

  trace(tab.disjonctif, browser)
  

I did the following (offline) to find the name of tab.disjonctif:

• Found the package on the CRAN mirror on GitHub
• Search for that particular expression that gives the error

Answer 2

Are the classes of your variables character or factor?I was having this problem. My solution was to change al variables to factor.

#my data.frame was "aux.da"
i=0
while(i < ncol(aux.da)){
  i=i+1  aux.da[,i] = as.factor(aux.da[,i])
}

Answer 3

I just started to learn R yesterday, but the error comes from the fact that the MCA is for categorical data, so that's why your data cannot be numeric. Then to be more precise, before the MCA a "tableau disjonctif" (sorry i don't know the word in english : Complete disjunctive matrix) is created. So FactomineR is using this function :

https://github.com/cran/FactoMineR/blob/master/R/tab.disjonctif.R

Where i think it's looking for categorical values that can be matched to a numerical value (like Y = 1, N = 0).

For others ; be careful : for R categorical data is related to factor type, so even if you have characters you could get this error.

Answer 4

Same problem as well and changing to factor did not solve my answer either, because I had put every variable as supplementary.

What I did first was transform all my numeric data to factor :

Xfac = factor(X[,1], ordered = TRUE)
for (i in 2:29){
  tfac = factor(X[,i], ordered = TRUE)
  Xfac = data.frame(Xfac, tfac)
}
colnames(Xfac)=labels(X[1,])

Still, it would not work. But my 2nd problem was that I included EVERY factor as supplementary variable ! So these :

MCA(Xfac, quanti.sup = c(1:29), graph=TRUE)
MCA(Xfac, quali.sup = c(1:29), graph=TRUE)

Would generate the same error, but this one works :

MCA(Xfac, graph=TRUE)

Not transforming the data to factors also generated the problem.

I posted the same answer to a related topic : https://stackoverflow.com/a/40737335/7193352