When I use diff(), it breaks summarise() - r

Question

One of the columns I want to have after using summarise() is the difference between the (two) values. Each group is ALWAYS going to have two or less rows, in m case. The function I found online was diff(). However, I ran into a problem.
Look at this example:
df <- data.frame(value = runif(198),
id = c(
sample(1:100, 99),
sample(1:100, 99))
)
find <- df %>%
group_by(id) %>%
summarise(count = n()) %>%
filter(count != 2)
find
In this case, since I'm not using diff(), I get this:
> find
# A tibble: 2 x 2
id count
<int> <int>
1 14 1
2 39 1
It works fine. Now, if I include diff():
> find <- df %>%
+ group_by(id) %>%
+ summarise(diference = diff(value), count = n()) %>%
+ filter(count != 2)
`summarise()` regrouping output by 'id' (override with `.groups` argument)
> find
# A tibble: 0 x 3
# Groups: id [0]
# … with 3 variables: id <int>, diference <dbl>, count <int>
It comes up with nothing. If I don't filter (it was a relatively short data frame, so I went one by one), I see those rows disappear. In a shorter example, it would be:
> df <- data.frame(value = runif(10),
+ id = c(
+ sample(1:6, 5),
+ sample(1:6, 5))
+ )
> find <- df %>%
+ group_by(id) %>%
+ summarise(diference = diff(value), count = n())
`summarise()` regrouping output by 'id' (override with `.groups` argument)
> find
# A tibble: 4 x 3
# Groups: id [4]
id diference count
<int> <dbl> <int>
1 2 -0.309 2
2 3 0.474 2
3 4 -0.148 2
4 6 0.291 2
As you can see, the 1 and 5 rows (id) disappeared. I believe apllying diff() causes it, since without it, that doesn't happen:
> find <- df %>%
+ group_by(id) %>%
+ summarise(count = n())
`summarise()` ungrouping output (override with `.groups` argument)
> find
# A tibble: 6 x 2
id count
<int> <int>
1 1 1
2 2 2
3 3 2
4 4 2
5 5 1
6 6 2
That was the exact same data.
However, if I do it manually, diff() gives me an output, though in a slightly different way:
> diff(5)
numeric(0)
> diff(c(5, 4))
[1] -1
My question, then, is whether or not there is a better function to do this, or just some way for me to get the output without it erasing the one-item groups, like this:
id count diference
1 1 1 1
2 58 1 58
I know the differenc will be the same as the id, but the reason I'm interested in this is because this is just one of the arguments I will put in filter(). It will be: filter(diference != 0 || count != 2) (once again, this isn't my original data).

Answer 1

Maybe this is what the question wants. It uses ifelse to compute the difference between values only if the groups have 2 rows, else it returns value unchanged.
library(dplyr)
set.seed(2020)
df <- data.frame(value = runif(10),
id = c(
sample(1:6, 5),
sample(1:6, 5))
)
find <- df %>%
group_by(id) %>%
summarise(count = n(),
diference = ifelse(count > 1, c(0, diff(value)), value),
.groups = 'drop') %>%
filter(count != 2 | diference != 0)
find
## A tibble: 2 x 3
# id count diference
# <int> <int> <dbl>
#1 1 1 0.647
#2 6 1 0.0674