> On May 21, 2016, at 7:41 AM, ch.elahe via R-help <r-help@r-project.org> wrote:
>
> Hi all,
>
> Here is my df and I want to make an averaged model of my variables based on
> Time like the following:
>
>
> $ Protocol : Factor w/ 48 levels "DP FS QTSE SAG",..: 2 3 43 42
> $ Time : num 182 185 189 234 186 ...
>
> $ Systemtype : Factor w/ 2 levels "Aera XJ","AERA XQ": 1 1 1
> $ ADJ : Factor w/ 2 levels "auto","manu": 1 1
> $ BR : int 384 384 384 384 512 384
> $ TF : int 10 10 13 7 7 5 5
> I split my df into quartiles for time,
>
>
> df$quant=findInterval(df$Time, quantile(df$Time), rightmost.closed=TRUE)
> by the column df$quant I see quartiles 1 to 4 for time, next I want to create
> a new column for example for BR and if df$quant==1 then put mean of first
> quartile of BR in that,if df$quant==2 put mean of second quartile of BR in
> that and so on. I do the same for every numeric variable. Does anyone know
> how to that?
>
Perhaps, but untested in the absence of a reproducible example and choosing to
instead use a name for the dataframe which is not also a function name:
aggregate( dfrm[ , sapply( dfrm, inherits, "numeric")], # logical indexing
for `[, j]`
dfrm['quant'] # using "[" keeps it a list
mean)
--
David Winsemius
Alameda, CA, USA
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