Hi:

Does this do what you want?

# Create some fake data...

df <- data.frame(id = factor(rep(c('cell1', 'cell2'), each = 10)),
                  cond = factor(rep(rep(c('A', 'B'), each = 5), 2)),
                  time = round(rnorm(20, 350, 10), 2))

# Create a function to subtract each element of a vector from its mean
 f <- function(x) x - mean(x)
# Load the plyr package, which contains the function ddply():
library(plyr)
df2 <- ddply(df, .(id, cond), transform, dev = f(time))

# output
> df2
      id cond   time     dev
1  cell1    A 353.01   7.226
2  cell1    A 351.06   5.276
3  cell1    A 343.59  -2.194
4  cell1    A 341.50  -4.284
5  cell1    A 339.76  -6.024
6  cell1    B 351.18   0.644
7  cell1    B 340.53 -10.006
8  cell1    B 345.09  -5.446
9  cell1    B 347.44  -3.096
10 cell1    B 368.44  17.904
11 cell2    A 343.48  -3.776
12 cell2    A 352.35   5.094
13 cell2    A 350.78   3.524
14 cell2    A 340.38  -6.876
15 cell2    A 349.29   2.034
16 cell2    B 364.45  15.524
17 cell2    B 354.52   5.594
18 cell2    B 350.41   1.484
19 cell2    B 345.78  -3.146
20 cell2    B 329.47 -19.456

# cell means
> with(df, aggregate(time, list(id = id, cond = cond), mean))
     id cond       x
1 cell1    A 345.784
2 cell2    A 347.256
3 cell1    B 350.536
4 cell2    B 348.926

HTH,
Dennis

On Fri, Mar 26, 2010 at 1:31 PM, Dgnn <sharkbrain...@gmail.com> wrote:

>
> 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
>
>
> --
> View this message in context:
> http://n4.nabble.com/a-vectorized-solution-to-some-simple-dataframe-math-tp1692810p1692810.html
> Sent from the R help mailing list archive at Nabble.com.
>
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