On Jan 11, 2012, at 3:55 PM, Christopher G Oakley wrote:
I need some help summarizing complex data frames (small example
below):
m1_1 m2_1 m3_1 m1_2 m2_2 m3_2
i1 1 1 1 2 2 2
i1 2 1 1 2 2 2
i2 2 2 1 2 2 2
For an arbitrary number of columns (say m1 …. m199) where the column
names have variable patterns,
and such that each set of columns is repeated (with potentially
unique data) an arbitrary number of times (say _1 … _1000),
I would like to summarize by row the mean values of (m1, m2, m3, …
m199) over all replicates (_1, _2, _3, … _1000). I need to do this
with a large number of dataframes of variable nrow, ncolumn, and
colnames.
Something along the lines of this untested code:
sapply(unique(sub("_.+$", "", names(dfrm))),
function(x) rowMeans( dfrm[ , grep(x, names(dfrm)) ] )
)
Post a reproducible example and we can test it.
I've tried various loops creating new dataframes and reassigning
cell values in loops or using rbind and bind, but run into trouble
in each case.
Any ideas?
Thanks,
Chris
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David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
