I think
?tapply
and friends: ?by ?aggregate ?ave
is what you want.
-- Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll
On Fri, Feb 20, 2015 at 9:33 AM, Tim Richter-Heitmann
<trich...@uni-bremen.de> wrote:
> Dear List,
>
> Consider this example
>
> df <- data.frame(matrix(rnorm(9*9), ncol=9))
> names(df) <- c("c_1", "d_1", "e_1", "a_p", "b_p", "c_p", "1_o1", "2_o1",
> "3_o1")
> row.names(df) <- names(df)
>
>
> indx <- gsub(".*_", "", names(df))
>
> I can split the dataframe by the index that is given in the column.names
> after the underscore "_".
>
> list2env(
> setNames(
> lapply(split(colnames(df), indx), function(x) df[x]),
> paste('df', sort(unique(indx)), sep="_")),
> envir=.GlobalEnv)
>
> However, i changed my mind and want to do it now by rownames. Exchanging
> colnames with rownames does not work, it gives the exact same output (9 rows
> x 3 columns). I could do
> as.data.frame(t(df_x),
> but maybe that is not elegant.
> What would be the solution for splitting the dataframe by rows?
>
> Thank you very much!
>
> --
> Tim Richter-Heitmann
>
> ______________________________________________
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