R transpose 2 matrices into a list of tibbles (for a nested df)

Question

I have two matrices, of latitude and longitude, both of which are 50 column x 1 million (e.g.) rows. I need to create a list of 1 million tibbles, each 2 columns - lon and lat - and 50 rows. My current code is:

lonlat <- list()
for (i in 1:nrow(lon)) {
  lonlat[[i]] <- tibble(lon = lon[i, ], lat = lat[i, ])
    }

I'm aware that this is incredibly inefficient, but I can't get my head around how I'd do this with purrr. I feel like map2 could be the answer, but I suspect I'm not thinking about this the right way, and possibly I should reorganise the input matrices in order to make it a simpler task.

Does anyone have any experience with purrr/map2, or this kind of problem? Thanks in advance for any ideas.

Answer 1

Here is an option using asplit + array (borrow data from @r2evans)

> asplit(array(cbind(lat, lon), c(dim(lat), 2)), 1)
[[1]]
     [,1] [,2]
[1,]    1   51
[2,]    5   55
[3,]    9   59
[4,]   13   63
[5,]   17   67

[[2]]
     [,1] [,2]
[1,]    2   52
[2,]    6   56
[3,]   10   60
[4,]   14   64
[5,]   18   68

[[3]]
     [,1] [,2]
[1,]    3   53
[2,]    7   57
[3,]   11   61
[4,]   15   65
[5,]   19   69

[[4]]
     [,1] [,2]
[1,]    4   54
[2,]    8   58
[3,]   12   62
[4,]   16   66
[5,]   20   70