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.
Your "50 columns" is 5 here; your "1 million rows" is 4 here.
lat <- matrix(1:20, nr=4)
lon <- matrix(50 + 1:20, nr=4)
lat
# [,1] [,2] [,3] [,4] [,5]
# [1,] 1 5 9 13 17
# [2,] 2 6 10 14 18
# [3,] 3 7 11 15 19
# [4,] 4 8 12 16 20
lon
# [,1] [,2] [,3] [,4] [,5]
# [1,] 51 55 59 63 67
# [2,] 52 56 60 64 68
# [3,] 53 57 61 65 69
# [4,] 54 58 62 66 70
There your 1-million-long list is 4-long here, each with 2 columns and 5 rows.
Map(tibble, lat=asplit(lat, 1), lon=asplit(lon, 1))
# [[1]]
# # A tibble: 5 x 2
# lat lon
# <int> <dbl>
# 1 1 51
# 2 5 55
# 3 9 59
# 4 13 63
# 5 17 67
# [[2]]
# # A tibble: 5 x 2
# lat lon
# <int> <dbl>
# 1 2 52
# 2 6 56
# 3 10 60
# 4 14 64
# 5 18 68
# [[3]]
# # A tibble: 5 x 2
# lat lon
# <int> <dbl>
# 1 3 53
# 2 7 57
# 3 11 61
# 4 15 65
# 5 19 69
# [[4]]
# # A tibble: 5 x 2
# lat lon
# <int> <dbl>
# 1 4 54
# 2 8 58
# 3 12 62
# 4 16 66
# 5 20 70
If you really want to use purrr, then
purrr::map2(asplit(lat, 1), asplit(lon, 1), ~ tibble(lat=.x, lon=.y))