Get row in paired sublists by ID

Question

This can be tricky:

I need to restructure a list containing an unknown number of subscriptions (although 2 in the sample data). However, each sublist contains ID-Column. For each IDin any of the subscriptions, I now need to create a list containing a line in which it IDcorresponds IDin the sublist, but also the corresponding lines in it are siblings.

This is my initial list:

> str(myList1)
List of 2
 $ 1:'data.frame':  2 obs. of  5 variables:
  ..$ ID     : num [1:2] 13369 13599
  ..$ subject: num [1:2] 2 2
  ..$ gender : num [1:2] 1 1
  ..$ age    : num [1:2] 18 18
  ..$ score  : num [1:2] 30 28
 $ 2:'data.frame':  2 obs. of  5 variables:
  ..$ ID     : num [1:2] 13370 14342
  ..$ subject: num [1:2] 3 3
  ..$ gender : num [1:2] 1 1
  ..$ age    : num [1:2] 28 28
  ..$ score  : num [1:2] 27 32

This is the result that I hope to get:

> str(myList2)
List of 4
 $ 13369:List of 2
  ..$ 1:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 13369
  .. ..$ subject: num 2
  .. ..$ gender : num 1
  .. ..$ age    : num 18
  .. ..$ score  : num 30
  ..$ 2:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 13599
  .. ..$ subject: num 2
  .. ..$ gender : num 1
  .. ..$ age    : num 18
  .. ..$ score  : num 28
 $ 13370:List of 2
  ..$ 1:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 14342
  .. ..$ subject: num 3
  .. ..$ gender : num 1
  .. ..$ age    : num 28
  .. ..$ score  : num 27
  ..$ 2:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 13370
  .. ..$ subject: num 3
  .. ..$ gender : num 1
  .. ..$ age    : num 28
  .. ..$ score  : num 32
 $ 13599:List of 2
  ..$ 1:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 13369
  .. ..$ subject: num 2
  .. ..$ gender : num 1
  .. ..$ age    : num 18
  .. ..$ score  : num 30
  ..$ 2:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 13599
  .. ..$ subject: num 2
  .. ..$ gender : num 1
  .. ..$ age    : num 18
  .. ..$ score  : num 28
 $ 14342:List of 2
  ..$ 1:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 14342
  .. ..$ subject: num 3
  .. ..$ gender : num 1
  .. ..$ age    : num 28
  .. ..$ score  : num 27
  ..$ 2:'data.frame':   1 obs. of  5 variables:
  .. ..$ ID     : num 13370
  .. ..$ subject: num 3
  .. ..$ gender : num 1
  .. ..$ age    : num 28
  .. ..$ score  : num 32

I have absolutely no information on how to achieve this, and I don’t even know where to direct my research on this issue.

Playable Code:

myList1 <- list(
    '1' = data.frame('ID' = c(13369,13599), 'subject' = c(2,2), 'gender' = c(1,1), 'age' = c(18,18), 'score' = c(30,28)),
    '2' = data.frame('ID' = c(13370,14342), 'subject' = c(3,3), 'gender' = c(1,1), 'age' = c(28,28), 'score' = c(27,32))
    )

Reproducible code for the result, if necessary:

myList2 <- list(
    '13369' = list('1' = data.frame('ID' = 13369, 'subject' = 2, 'gender' = 1, 'age' = 18, 'score' = 30), '2' = data.frame('ID' = 13599, 'subject' = 2, 'gender' = 1, 'age' = 18, 'score' = 28)),
    '13370' = list('1' = data.frame('ID' = 14342, 'subject' = 3, 'gender' = 1, 'age' = 28, 'score' = 27), '2' = data.frame('ID' = 13370, 'subject' = 3, 'gender' = 1, 'age' = 28, 'score' = 32)),
    '13599' = list('1' = data.frame('ID' = 13369, 'subject' = 2, 'gender' = 1, 'age' = 18, 'score' = 30), '2' = data.frame('ID' = 13599, 'subject' = 2, 'gender' = 1, 'age' = 18, 'score' = 28)),
    '14342' = list('1' = data.frame('ID' = 14342, 'subject' = 3, 'gender' = 1, 'age' = 28, 'score' = 27), '2' = data.frame('ID' = 13370, 'subject' = 3, 'gender' = 1, 'age' = 28, 'score' = 32))
    )

Answer 1

:

purrr::flatten(
  lapply(
    myList1, function(l){
      setNames(
        apply(l, 1, function(x){
          setNames(split(l, l$ID),seq_along(l$ID))}), 
        l$ID)}))