Assigning NULL to a list element in R?

Question

I found this behaviour odd and wanted more experienced users to share their thoughts and workarounds. On running the code sample below in R:

sampleList <- list() d<- data.frame(x1 = letters[1:10], x2 = 1:10, stringsAsFactors = FALSE) for(i in 1:nrow(d)) {         sampleList[[i]] <- d$x1[i] }  print(sampleList[[1]]) #[1] "a" print(sampleList[[2]]) #[1] "b" print(sampleList[[3]]) #[1] "c" print(length(sampleList)) #[1] 10  sampleList[[2]] <- NULL print(length(sampleList)) #[1] 9 print(sampleList[[2]]) #[1] "c" print(sampleList[[3]]) #[1] "d" 

The list elements get shifted up. Maybe this is as expected, but I am trying to implement a function where I merge two elements of a list and drop one. I basically want to lose that list index or have it as NULL.

Is there any way I can assign NULL to it and not see the above behaviour?

Thank you for your suggestions.

Answer 1

Good question.

Check out the R-FAQ:

In R, if x is a list, then x[i] <- NULL and x[[i]] <- NULL remove the specified elements from x. The first of these is incompatible with S, where it is a no-op. (Note that you can set elements to NULL using x[i] <- list(NULL).)

consider the following example:

> t <- list(1,2,3,4) > t[[3]] <- NULL          # removing 3'd element (with following shifting) > t[2] <- list(NULL)      # setting 2'd element to NULL. > t [[1]] [2] 1  [[2]] NULL  [[3]] [3] 4 

UPDATE:

As the author of the R Inferno commented, there can be more subtle situations when dealing with NULL. Consider pretty general structure of code:

# x is some list(), now we want to process it. > for (i in 1:n) x[[i]] <- some_function(...) 

Now be aware, that if some_function() returns NULL, you maybe will not get what you want: some elements will just disappear. you should rather use lapply function. Take a look at this toy example:

> initial <- list(1,2,3,4) > processed_by_for <- list(0,0,0,0) > processed_by_lapply <- list(0,0,0,0) > toy_function <- function(x) {if (x%%2==0) return(x) else return(NULL)} > for (i in 1:4) processed_by_for[[i]] <- toy_function(initial[[i]]) > processed_by_lapply <- lapply(initial, toy_function) > processed_by_for   [[1]]   [1] 0    [[2]]   [1] 2    [[3]]   NULL    [[4]]   [1] 4  > processed_by_lapply   [[1]]   NULL    [[2]]   [1] 2    [[3]]   NULL    [[4]]   [1] 4 

Answer 2

Your question is a bit confusing to me.

Assigning null to an existing object esentially deletes that object (this can be very handy for instance if you have a data frame and wish to delete specific columns). That's what you've done. I am unable to determine what it is that you want though. You could try

sampleList[[2]] <- NA 

instead of NULL, but if by "I want to lose" you mean delete it, then you've already succeeded. That's why, "The list elements get shifted up."