Extracting specific group value from a data.table list and returning as a vector in R

Question

I have a list of some data, Its looks like:

library(data.table)

dt1 <- data.table(age_group = c("young", "old"), ratio = runif(2))
dt2 <- data.table(age_group = c("young", "old"), ratio = runif(2))

dt_list <- list(
    list(ratio_by_group = dt1),
    list(ratio_by_group = dt2),
    list(ratio_by_group = NA)
)

dt_list
[[1]]
[[1]]$ratio_by_group
   age_group     ratio
1:     young 0.5956572
2:       old 0.5053023


[[2]]
[[2]]$ratio_by_group
   age_group     ratio
1:     young 0.4632962
2:       old 0.2356656


[[3]]
[[3]]$ratio_by_group
[1] NA

I want tp exact the ratio information for a specific group (i.e., 'young') and return it as a vector. I used the following code:

sapply(dt_list, function(x) ifelse(!is.na(x$ratio_by_group), x$ratio_by_group[age_group=='young', ratio], NA))

          [,1]      [,2]
[1,] 0.5956572 0.4632962
[2,] 0.5956572 0.4632962
[3,] 0.5956572 0.4632962
[4,] 0.5956572 0.4632962

My expected output is

[1] "0.5956572" "0.4632962" NA 

Answer 1

use Recursion:

fn <- function(x){
    if(is.data.table(x)) x[age_group == 'young', ratio]
    else if(is.list(x[[1]])) unlist(lapply(x, fn),use.names = FALSE)
}

fn(dt_list)
[1] 0.6224014 0.8436315