Keywords:
### ** Examples # Chop ============================================================== df <- tibble(x = c(1, 1, 1, 2, 2, 3), y = 1:6, z = 6:1) # Note that we get one row of output for each unique combination of # non-chopped variables df %>% chop(c(y, z))
# A tibble: 3 × 3
x y z
<dbl> <list<int>> <list<int>>
1 1 [3] [3]
2 2 [2] [2]
3 3 [1] [1]
# cf nest df %>% nest(data = c(y, z))
# A tibble: 3 × 2
x data
<dbl> <list>
1 1 <tibble [3 × 2]>
2 2 <tibble [2 × 2]>
3 3 <tibble [1 × 2]>
# Unchop ============================================================ df <- tibble(x = 1:4, y = list(integer(), 1L, 1:2, 1:3)) df %>% unchop(y)
# A tibble: 6 × 2
x y
<int> <int>
1 2 1
2 3 1
3 3 2
4 4 1
5 4 2
6 4 3
df %>% unchop(y, keep_empty = TRUE)
# A tibble: 7 × 2
x y
<int> <int>
1 1 NA
2 2 1
3 3 1
4 3 2
5 4 1
6 4 2
7 4 3
# Incompatible types ------------------------------------------------- # If the list-col contains types that can not be natively df <- tibble(x = 1:2, y = list("1", 1:3)) try(df %>% unchop(y))
Error in list_unchop(x = x, indices = indices, ptype = ptype, name_spec = name_spec, : Can't combine `x[[1]]` <character> and `x[[2]]` <integer>.
# Unchopping data frames ----------------------------------------------------- # Unchopping a list-col of data frames must generate a df-col because # unchop leaves the column names unchanged df <- tibble(x = 1:3, y = list(NULL, tibble(x = 1), tibble(y = 1:2))) df %>% unchop(y)
# A tibble: 3 × 2
x y$x $y
<int> <dbl> <int>
1 2 1 NA
2 3 NA 1
3 3 NA 2
df %>% unchop(y, keep_empty = TRUE)
# A tibble: 4 × 2
x y$x $y
<int> <dbl> <int>
1 1 NA NA
2 2 1 NA
3 3 NA 1
4 3 NA 2