I have a named list containing tibbles as elements. I would like to bind_cols of those tibbles whose names are the same within that list. For example:
list(A = tibble(alpha = 1:5, beta = 2:6), B = tibble(delta = 1:8), A = tibble(gamma = 3:7))
> list(A = tibble(alpha = 1:5, beta = 2:6), B = tibble(delta = 1:8), A = tibble(gamma = 3:7))
$A
# A tibble: 5 × 2
alpha beta
<int> <int>
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6
$B
# A tibble: 8 × 1
delta
<int>
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
$A
# A tibble: 5 × 1
gamma
<int>
1 3
2 4
3 5
4 6
5 7
I would like to transform this into, i.e. this is my desired output:
list(A = tibble(alpha = 1:5, beta = 2:6, gamma = 3:7), B = tibble(delta = 1:8))
$A
# A tibble: 5 × 3
alpha beta gamma
<int> <int> <int>
1 1 2 3
2 2 3 4
3 3 4 5
4 4 5 6
5 5 6 7
$B
# A tibble: 8 × 1
delta
<int>
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
How this could be achieved?
We can split on the names of L, then use bind_cols:
library(dplyr)
split(L, names(L)) |>
lapply(bind_cols)
# $A
# # A tibble: 5 × 3
# alpha beta gamma
# <int> <int> <int>
# 1 1 2 3
# 2 2 3 4
# 3 3 4 5
# 4 4 5 6
# 5 5 6 7
# $B
# # A tibble: 8 × 1
# delta
# <int>
# 1 1
# 2 2
# 3 3
# 4 4
# 5 5
# 6 6
# 7 7
# 8 8
Note: in this case, bind_cols works well because they have the same number of rows. If the row-counts are different or if there is another condition on which they should be combined (aka "merged" or "joined"), then you will need another function such as *_join or merge.
Also, I inferred dplyr from your use of tibble(..), though this can be done with base R as well:
split(L, names(L)) |>
lapply(\(x) do.call(cbind, unname(x)))