Does pivot_wider allows values_fill the last known values?

Question

Rather than the current 0 fill for NAs, Is there anything in pivot_wider where it can replace it with the last known values from the same column?

library('tidyr')
library('dplyr')

fish_encounters %>%
  group_by(station) %>% 
  mutate(seen = cumsum(seen)) %>%
  pivot_wider(names_from = station, values_from = seen,values_fill = list(seen = 0))

# A tibble: 19 x 12
   fish  Release I80_1 Lisbon  Rstr Base_TD   BCE   BCW  BCE2  BCW2   MAE   MAW
   <fct>   <int> <int>  <int> <int>   <int> <int> <int> <int> <int> <int> <int>
 1 4842        1     1      1     1       1     1     1     1     1     1     1
 2 4843        2     2      2     2       2     2     2     2     2     2     2
 3 4844        3     3      3     3       3     3     3     3     3     3     3
 4 4845        4     4      4     4       4     0     0     0     0     0     0
 5 4847        5     5      5     0       0     0     0     0     0     0     0
 6 4848        6     6      6     5       0     0     0     0     0     0     0
 7 4849        7     7      0     0       0     0     0     0     0     0     0
 8 4850        8     8      0     6       5     4     4     0     0     0     0
 9 4851        9     9      0     0       0     0     0     0     0     0     0
10 4854       10    10      0     0       0     0     0     0     0     0     0
11 4855       11    11      7     7       6     0     0     0     0     0     0
12 4857       12    12      8     8       7     5     5     4     4     0     0
13 4858       13    13      9     9       8     6     6     5     5     4     4
14 4859       14    14     10    10       9     0     0     0     0     0     0
15 4861       15    15     11    11      10     7     7     6     6     5     5
16 4862       16    16     12    12      11     8     8     7     7     0     0
17 4863       17    17      0     0       0     0     0     0     0     0     0
18 4864       18    18      0     0       0     0     0     0     0     0     0
19 4865       19    19     13     0       0     0     0     0     0     0     0

I understand this can be achieved with the code below, but i'd like to do this in multidplyr environment which has yet to support mutate_at or summarise_at functions.

fish_encounters %>%
  pivot_wider(names_from = station, values_from = seen,values_fill = list(seen = 0)) %>% 
  mutate_at(.vars = vars(-fish),cumsum)

Answer 1

Can you use fill ?

library(dplyr)
library(tidyr)

fish_encounters %>%
   group_by(station) %>% 
   mutate(seen = cumsum(seen)) %>%
   pivot_wider(names_from = station, values_from = seen) %>%
   fill(-fish)