Summarize an ordered factor

I have a column in a dataframe that contains an ordered factor. I summarize the number of entries in the column for each factor by melting the data, then casting it. So far, so good. But I need to include factors for which no rows exist, so that the summarized data shows all possible factors, not just the utilized ones.

The data frame:

> str(instats)
'data.frame':   75 obs. of  5 variables:
$ incident     : Factor w/ 75 levels "INC000000503771",..: 1 2 3 4 5 6 7 8 9 10 ...
$ submit.date  :Class 'Date'  num [1:75] 14907 14907 14907 14907 14907 ...
$ resolved.date:Class 'Date'  num [1:75] 14910 14907 14910 14907 14907 ...
$ closed.date  :Class 'Date'  num [1:75] 14开发者_开发问答913 14910 14913 14910 14910 ...
$ status       : Ord.factor w/ 6 levels "Opened"<"Resolved Pending Customer Action"<..: 5 5 5 5 5 5 5 5 5 5 ...
> 

what I've done so far:

> df.melt <- melt(instats,id=c('status'),measure=c('incident'))
> cast(df.melt, status ~ .,length)

and I get:

                            status (all)
1 Resolved Pending Customer Action    11
2               Pending xxx Action     3
3               Pending yyy Action     7
4                           Closed    54

what I want is:

                            status (all)
1                           Opened     0
2 Resolved Pending Customer Action    11
3               Pending xxx Action     3
4               Pending yyy Action     7
5                           Closed    54
6                         Canceled     0

I understand why the melting/casting gives me the results it does. But how else can I do this to get my desired results?

You could just use table

instats <- data.frame(status=sample(letters[1:5],75,TRUE))
instats$status <- factor(instats$status,levels=letters[1:6])

table(instats$status)
as.data.frame(table(instats$status))

# or summary
summary(instats$status)