Dear R-help, I have an xts data set that i have subset by date.
now it contains a date-time-stamp, and two columns (price and volume traded): my objective is to create tables of volume traded at a price - and i've been successfully using aggregate to do so in interactive use. say the data looks as follows: px_ym1 vol_ym1 2012-06-01 09:37:00 97.91 437 2012-06-01 09:37:00 97.91 64 2012-06-01 09:37:00 97.91 1 2012-06-01 09:37:00 97.91 5 2012-06-01 09:37:00 97.91 5 2012-06-01 09:37:00 97.92 174 2012-06-01 09:37:00 97.92 64 2012-06-01 09:37:00 97.92 125 2012-06-01 09:37:00 97.92 124 2012-06-01 09:37:00 97.92 64 2012-06-01 09:37:00 97.92 109 2012-06-01 09:37:00 97.92 64 2012-06-01 09:37:00 97.92 19 2012-06-01 09:37:00 97.92 45 2012-06-01 09:37:00 97.92 75 2012-06-01 09:37:00 97.92 3 2012-06-01 09:37:00 97.92 47 2012-06-01 09:37:00 97.91 26 2012-06-01 09:37:00 97.92 4 2012-06-01 09:37:00 97.92 1 the the following gives me what i'm looking for: > adf <- aggregate(.~px_ym1, data=mm, sum) which is this table: px_ym1 vol_ym1 1 97.91 538 2 97.92 918 however now i'm trying to code it to run automatically, and use of the templated version: > adf <- aggregate(.~mm[,1], data=mm, sum) yields the following - which contains what i'd like, but is has also summed across the price column (not ideal). px_ym1 px_ym1 vol_ym1 1 97.91 587.46 538 2 97.92 1370.88 918 how do i code this so that i can enter an xts data-frame with arbitrary names and still obtain the table with only the information i desire? on a related point, is there a way to combine the two steps? the function i've written splits by date and then returns a list containing data-frames that report the volume traded at each price on each date - am i re-creating the wheel here? is there canned function that does this? thanks + best regards matt johnson [[alternative HTML version deleted]] ______________________________________________ R-help@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.