[R] a vectorized solution to some simple dataframe math?

[Dgnn]

I have a data frame containing the results of time measurements taken from
several cells. Each cell was measured in conditions A and B, and there are
an arbitrary number of measurements in each condition. I am trying to
calculate the difference of each measurement from the mean of a given cell
in a given condition without relying on loops.

>my.df
           id       cond    time
1         cell1     A       343.5
2         cell1     A       355.2
...
768      cell1     B       454.0
...
2106    cell2     A       433.9
...

as a first approach I tried:

> mews<-aggregate(my.df$time, list(cond=data$id, id=data$cond), mean)
id      cond      time
cell1    A         352
cell1    B         446
cell2    A         244
cell2    B         ...

I then tried to use %in% to match id and cond of mews with my.df, but I
haven't been able to get it to work.
Am I on the right track? What are some other solutions?

Thanks for any help.

jason


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