grouping on string fields in R

Question

I have a data frame like this:

         date      time userid        status
1  02/25/2012  09:22:10   aabc     logged_in
2  02/25/2012  09:30:10   aabc    logged_out
3  02/25/2012  09:29:20   abbc    logged_out
4  02/25/2012  09:27:30    abc     logged_in
5  02/25/2012  09:26:29    abc  login_failed
6  02/25/2012  09:26:39    abc  login_failed
7  02/25/2012  09:26:52    abc  login_failed
8  02/25/2012  09:27:09    abc  login_failed
9  02/25/2012  09:27:20    abc  login_failed
10 02/25/2012  09:24:10   abdc     logged_in
11 02/25/2012  09:24:12   abdc    logged_out
12 02/25/2012  09:22:10   abhc     logged_in
13 02/25/2012  09:30:10   abuc     logged_in
14 02/25/2012  09:30:14   abuc    logged_out
15 02/25/2012  09:29:40    baa     logged_in

I want to the userids, status and "count" of the login_failures for each userid. I did this:

ddply(mytbl, c('userid', 'status'), function(x) c(count=nrow(x))) , but this gives the count for all userids. I want to restrict my output to only those userids whose status is 'login _failed'. Any ideas? I have seen questions on grouping by numeric fields, but, none on strings.

I am not very familiar with all the plyr features. It will great to see how this can be done using summarize, aggregate, sqldf, data.table etc. Slowly understanding each of them.

Thanks Sri

Answer 1

require(data.table)
DT = as.data.table(mytbl)

DT[status=="login_failed", .N, by=userid]

To name the column :

DT[status=="login_failed", list(failed_logins=.N), by=userid]

Answer 2

Slightly different approach than @Maiasaura. I filter to just the failed logins and then summarize. The difference would be whether those userid's with logins, but no failed logins, appear in the final result with 0's or not.

ddply(mytbl[mytbl$status=="login_failed",], .(userid), 
  summarise, failed_logins=length(status))

This gives

> ddply(mytbl[mytbl$status=="login_failed",], .(userid), 
+   summarise, failed_logins=length(status))
  userid failed_logins
1    abc             5

To complete the approaches, if you want all the userid's:

ddply(mytbl, .(userid), 
  summarise, failed_logins = sum(status=="login_failed"))

which gives

> ddply(mytbl, .(userid), 
+   summarise, failed_logins = sum(status=="login_failed"))
  userid failed_logins
1   aabc             0
2   abbc             0
3    abc             5
4   abdc             0
5   abhc             0
6   abuc             0
7    baa             0