dplyr group_by_ lazy .drop = F - r

Question

I am trying to incorporate the drop = F into the following dplyr function
dspreadN = function(data, ...) {
data %>% group_by_(.dots = lazyeval::lazy_dots(...), .drop = F) %>%
summarise(n = n()*100) %>% spread(value, n, fill = 0)
}
Basically, the function transform this
id x
1 1 A
2 1 A
3 1 A
4 1 A
5 2 A
6 2 A
7 2 B
8 2 B
9 3 A
10 3 A
11 3 B
12 3 A
into that
id drop A B
<dbl> <lgl> <dbl> <dbl>
1 1 FALSE 400 0
2 2 FALSE 200 200
3 3 FALSE 300 100
I use the function in this way dff %>% dspreadN(id, value = x)
(my real example is much more complicated that why I need the dplyr function).
What I would like is to keep all the levels of the x variable, here the C is missing.
id A B C
<dbl> <dbl> <dbl> <dbl>
1 1 400 0 0
2 2 200 200 0
3 3 300 100 0
Why is the drop = F not working?
library(tidyverse)
# data
dff = data.frame(id = c(1,1,1,1, 2,2,2,2, 3,3,3,3, 4,4,4,4),
x = c('A','A','A','A', 'A','A','B','B', 'A','A','B','A', 'C', 'C', 'C', 'C'))
# remove the case to keep the C level
dff = dff[dff$id != 4, ]

Answer 1

You can use .drop = FALSE argument in count instead of group_by.
group_by + summarise with n() is equal to count.
spread has been deprecated in favour of pivot_wider.
Thanks to #Edo for useful tips in improving the post
library(dplyr)
library(tidyr)
dspreadN = function(data, ...) {
data %>%
count(id, x, .drop = FALSE, wt = n() * 100) %>%
pivot_wider(names_from = x, values_from = n, values_fill = 0)
}
dspreadN(dff, id, x)
# id A B C
# <dbl> <dbl> <dbl> <dbl>
#1 1 400 0 0
#2 2 200 200 0
#3 3 300 100 0