R Function behaves differently than the code entered line by line - r

Question

I am at a loss. Googling has failed me because I'm not sure I know the right question to ask.
I have a data frame (df1) and my goal is to use a function to get a moving average using forecast::ma.
Here is str(df1)
'data.frame': 934334 obs. of 6 variables:
$ clname : chr ...
$ dos : Date, format: "2011-10-05" ...
$ subpCode: chr
$ ch1 : chr "
$ prov : chr
$ ledger : chr
I have a function that I am trying to write.
process <- function(df, y, sub, ...) {
prog <- df %>%
filter(subpCode == sub) %>%
group_by(dos, subpCode) %>%
summarise(services = n())
prog$count_ts <- ts(prog[ , c('services')])
}
The problem is that when I run the function, my final result is data object that is 1x1798 and it's just a time series. If I go a run the code line by line I get what I need but my function that hypothetically does the same thing wont work.
Here is my desired result
Classes ‘grouped_df’, ‘tbl_df’, ‘tbl’ and 'data.frame': 1718 obs. of 4 variables:
$ dos : Date, format: "2010-09-21" "2010-11-18" "2010-11-19" "2010-11-30" ...
$ subpCode: chr "CII " "CII " "CII " "CII " ...
$ services: int 1 1 2 2 2 2 1 2 1 3 ...
$ count_ts: Time-Series [1:1718, 1] from 1 to 1718: 1 1 2 2 2 2 1 2 1 3 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr "services"
- attr(*, "vars")= chr "dos"
- attr(*, "drop")= logi TRU
And here is the code that gets it.
CII <- df1 %>%
filter(subpCode == "CII ") %>%
group_by(dos, subpCode) %>%
summarise(services = n())
CII$count_ts <- ts(CII[ , c('services')])
Could someone point me in the right direction. I've exhausted my usual places.
Thanks!

Answer 1

Following the vignette pointed out by #CalumYou, you should use more something like this:
process <- function(df, sub) {
## Enquoting sub
sub <- enquo(sub)
## Piping stuff
prog <- df %>%
filter(!! subpCode == sub) %>%
group_by(dos, subpCode) %>%
summarise(services = n())
prog$count_ts <- ts(prog[ , c('services')])
## Returning the prog object
return(prog)
}