Hello all,

I have a data frame with the following columns: timestamp, activity,
interval.

Each row contains information about an activity that occured over a time
interval. "Timestamp" is when the interval ended, "Activity" is a factor
that represents the type of activity, and "Interval" is a double which
represents an interval in time. The data frame is sorted by timestamp.
For example:

Timestamp        Activity Interval
2004-02-12 08:59:08 A      5
2004-02-12 09:23:03 A      7
2004-02-12 09:56:04 A      4
2004-02-12 10:39:00 B      5
2004-02-12 11:23:06 B      3
2004-02-12 12:56:01 A      4
2004-02-12 12:59:01 A      2
...

I would like to know how much time was spent on an activity before the
activity changed (to compute time, I just care about the lengths of the
intervals, not the values of the timestamps). For example, given the
table above, I would like to get an output that looks like:


Activity    TotalTime
A         16
B         8
A         6

Is this possible to do in R without resorting to a for loop or recursion
(i.e. what's the R-ish way to do this?) I know I can use the "diff"
function to identify which rows represent a change in activity, but is
there anything I can do with that?

Lorin

----------
Lorin Hochstein
Graduate Research Assistant
Experimental Software Engineering Group
Computer Science Dept., University of Maryland
email:lorin@(protected)

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