处理嵌套在R中的嵌套列表中的处理向量

Question

I have a list of list s of vector s like the following:

myList = list(id1 = list(a=6:10,b=1:5),
              id2 = list(a=3:8,b = 4:9))

I would like to process the second vector named 'b' in each list with an arbitrary function (eg, mean , sum , etc.) and append the result to a third named vector within each nested list to achieved something like:

myList2 = list(id1 = list(a=6:10,b=1:5,c = mean(1:5)),
          id2 = list(a=3:8,b = 4:9,c = mean(4:9)))

Thus, my question has two parts. First, how can I process only the second named vector in each nested list ? Second, how can I append the result to each nested list ?

I know I can write a for loop that always indexes myList[[i]][[2]] , but I am looking for a vectorized solution. I've tried using various combinations apply -family with an anonymous function that first tests the name of the vector , for example:

rapply(myList, function(x) ifelse(names(x) == "b",
                              print("yes"),  #process vector
                              print("no")),  #move on to next x
   how = "list"
)

but the result doesn't make much sense.

Additional information: I'm using nested list s instead of a data.frame because I don't have the same number of observations for each id, but I am open to alternative approaches that might bypass these issues and accommodate different numbers of observations.

Answer 1

This should do it

lapply(myList, function(x) {
  x$c <- mean(x$b)
  return(x)
})