average elements of sublists in a nested list in R - r

Question

I need to average the elements of the nested sublist in the following way. For the example below I have list lll. I would like to have for lll[[1]] compute average of sublists (1+3+5+7)/4 =4, (2+4+6+8)/4=5. Similarly for lll[[2]] compute average of sublists we have (2+4+6+8)/4=5, (1+3+5+7)=4. I could do this using a for loop but the result is not as desired. Since I would like to have list or dataframe which is horizontal for example list(c(4,5),c(5,4)).Also when I have a list of 5000 elements for loop is not efficient. Will really appreciate a smarter way to do this.
l1<-as.matrix(c(1,2))
l2<-as.matrix(c(3,4))
l3<-as.matrix(c(5,6))
l4<-as.matrix(c(7,8))
l5<-as.matrix(c(2,1))
l6<-as.matrix(c(4,3))
l7<-as.matrix(c(6,5))
l8<-as.matrix(c(8,7))
ll1<-list(l1,l2,l3,l4)
ll2<-list(l5,l6,l7,l8)
lll<-list(ll1,ll2)
### using for loop
sum_k_a_<-list()
sum_k_b_<-list()
for (l in 1:2){
sum_k_a<-0
sum_k_b<-0
for (k in 1:4){
sum_k_a=lll[[l]][[k]][1]+sum_k_a
sum_k_b=lll[[l]][[k]][2]+sum_k_b
}
sum_k_a_[[l]]<-sum_k_a/4
sum_k_b_[[l]]<-sum_k_b/4
}

Answer 1

A couple of options:
lapply(lll, function(x) Reduce(`+`, x)/length(x) )
#[[1]]
# [,1]
#[1,] 4
#[2,] 5
#
#[[2]]
# [,1]
#[1,] 5
#[2,] 4
lapply(lll, function(x) rowMeans(do.call(cbind, x)))
#[[1]]
#[1] 4 5
#
#[[2]]
#[1] 5 4

Answer 2

You could do it using lapply and sapply:
lapply(lll,function(x) rowSums(sapply(x,function(y) c(y[1],y[2]))/4))
This returns a list of 2 elements:
[[1]]
[1] 4 5
[[2]]
[1] 5 4

Answer 3

We can also use tidyverse syntax
library(tidyverse)
lll %>%
map(~Reduce(`+`, .)/length(.))
#[[1]]
# [,1]
#[1,] 4
#[2,] 5
#[[2]]
# [,1]
#[1,] 5
#[2,] 4

Answer 4

Would really be much more simply done with an implicit sapply loop that applies mean to the unlist-ed values that are "deeper" in the list structures:
L_means <- sapply( lll, FUN=function(items) {mean( unlist(items))})
L_means
[1] 4.5 4.5
I guess I misunderstood the question, so this is what was desired:
(L_means <- sapply( lll, FUN=function(top){ apply( as.data.frame(top), 1, mean)}) )
[,1] [,2]
[1,] 4 5
[2,] 5 4