[R] searching for data.frame rows / processing of rows

[Gabor Grothendieck]

Grouping the data frame by the first two columns, apply colMeans
and then rbind the resulting by-structure together:

do.call(rbind, by(DF, DF[2:1], colMeans, na.rm = TRUE))


On 10/5/06, Greg Tarpinian <sasprog474 at yahoo.com> wrote:
> R 2.3.1, WinXP:
>
> I have a puzzling problem that I suspect may be solved using
> grep or a regular expression but am at a loss how to actually do it...
> My data.frame looks like
>
>  Location   Time    X    Y
>  --------   ----   ---  ---
>  1          0      1.6  9.3
>  1          3      4.2  10.4
>  1          6      2.7  16.3
>  2          0      0.5  2.1
>  2          3      NA   3.6
>  2          3      5.0  0.06
>  2          6      3.4  14.0
>
> and so forth.  I would like to search for duplicate Time values
> within a Location and take the numerical average (where possible)
> of the elements in X and Y.  These numerical averages should
> then be used to create a single row where multiple rows once
> existed.  So, I would like to obtain
>
>  2          3      5.0  1.83
>
> for the two Time = 3 rows for Location = 2 and use it to replace
> these two rows.  Ideally, avoiding for(i in 1:blah) loops would be
> nice because the data.frame has about 10,000 rows that need to
> be searched and processed.  My intent is to do some comparing of
> SAS to R -- the DATA step processing in SAS is quite fast and
> using the RETAIN statement along with the LAG( ) function allows
> this sort of thing to be done rapidly.
>
>
> Thanks in advance,
>
>       Greg
>
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