Dear Daniela,

Try this:

set.seed(123)
myD<-data.frame(code=sample(letters[1:5],200,replace=T),value=rnorm(200))
tapply(myD$value,myD$code,mean)
          a           b           c           d           e
 0.04401465  0.07813648  0.07018791 -0.14508544 -0.02369875

See ?tapply for more information.

HTH,

Jorge




On Tue, Jul 8, 2008 at 9:18 AM, Daniela Ottaviani <d.ottaviani@yahoo.it>
wrote:

> Dear All,
>
> I have a database of 200 observations named myD.
> In the dataframe there are a column named code (with codes varying from 1
> to 77), a column named "prevalence" with some quantitative measurements are
> given and an column named Pr_mean, with no values.
>
> I would like to set a cycle to compute the average of prevalence values for
> each different code and store the averages under the empty field Pr_mean.
>
> This is what I wrote:
>
> # Set a cycle
> for (i in 1:nrow(myD)) {
> mycode = myD$code[i]
> mymean[i] = mean(prevalence)
> myD$Pr_mean[i] = mymean[i]
> }
>
> With the above cycle I am able to compute the average of all 200
> observations which is then written in every cell.
> I understand that a condition is missing, that indicates that the average
> has to be computed amongst the observations showing  the same codes values.
>
> Could you please help me ?
>
>
> D.
>
>
>
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