Hi
>
> I have a list of data frames like the following:
>
> set.seed(123)
> a<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10))
> b<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10))
> L<- list(a,b)
>
> All data frames in the list have the same dimensions. I need to
calculate> the sample means for x and y. The real data are lists of several
thousand> quite large dataframes, so I need something that is pretty fast. Here
is> what I have so far:
>
> y<- rowMeans(sapply(L,'[[','y'))
> x<- rowMeans(sapply(L,'[[','x'))
>
> this works great, but I'm only able to get the sample means for one
column> at a time. Is there a way to automate things a bit so that I can get
the> sample means for several columns with one call?
I am not sure if it is suitable for you but plyr package can be used.
Maybe somebody could do better
aaply(laply(L, as.matrix), 3, colMeans)
shall give you an array with rows of means for columns of your data
frames.
Regards
Petr
>
> Thanks for any suggestions,
>
> Matthew
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.