R - a basic understanding of using "apply" instead of a nested loop

Question

So, I'm new to R (I'm starting out from the Python background), and I'm still having problems understanding how / when to implement the apply functions (lapply, sapply, rapply, etc.) instead of nested loops.

As an example, suppose you want to execute a FUN function that compares each item in a list with each item in another list. I would write something like:

 n = 1 m = 1 sameList = NULL for(i in 1:length(list1)){ for(j in 1:length(list2)){ if(list1[n]==list2[m]){ sameList<-c(sameList, list1[n]} n = n+1 } m = m+1 } 

In other words, some nested loop that iterates through each element of each list.

What I'm learning is that concatenating an intermediate list loop is a very inefficient process in R, so apply used.

So, how would I use apply (or any version of it) to replace the example code above?

Answer 1

To use lapply , you must run:

 sameList = lapply(list1, function(x) lapply(list2, function(y) if (x==y) x else NULL)) 

Answer 2

In this particular case, I would use

 sameList <- intersect(list1, list2) 

In addition, the terminology in R means that we use vector for collections of the same type; list allowed to contain different types.

Avoiding loops is probably an aesthetic problem, since loop performance is better than before than using it, but the performance degradation you noticed is probably due to the constant resizing of the sameList (and subsequent memory reallocation) than anything essentially boils down to your code.