how to deal with large lists

I have a list of length 100. Each entry is itself a list containing 31 matrices with 10 rows and five columns.

>length(dati_fault)
[1] 100

> length(dati_fault[[1]])
[1] 31

I should get 100 averages of the variables summarizing the 31 matrices each element of the list

media_1<-list()
for(i in nrow(dati_fault)){
  for(j in nrow(dati_fault[[i]]))
  media_1[[i]]<-lapply(dati_fault, colMeans(j))
  
}
media_1

But I get nothing because the media_1 list remains empty

>Solution :

you don’t need for loops to do so. You can directly work with lapply:

lapply(dati_fault, \(x) colMeans(do.call(rbind, x)))

This does the following: for each entry of dati_fault (i.e. each sublist of 31 matrices) these matrices are bound together (using rbind) into one single matrix with 310 rows and 5 columns. Then, colMeans is applied to this matrix.

If you are not familiar with the shorthand notation for anonymous functions (i.e. \(x)) you can read about it here.