[R] separation depending on equal contents in more than one field

[jim holtman]

One way is to 'split' the indices of the rows to determine which ones
to use.  For example from the data give, I got the following:

> split(seq(nrow(obs)), list(obs$a, obs$b), drop=T)
$`1.1`
[1] 1

$`2.2`
[1] 2

$`2.3`
[1] 3

$`3.4`
[1] 4 5

$`3.5`
[1] 6

You can then use this resulting list and find all entries with more
than one value and use this to do your calculations.

On 10/2/06, Florian Jansen <jansen at uni-greifswald.de> wrote:
> Hi,
>
> I have a dataframe:
>
> (obs <- data.frame(a=c(1,2,2,3,3,3), b=c(1,2,3,4,4,5), c=1:2))
> attach(obs)
>
> In reality its about 1 million rows.
>
> Some of the datasets have same contents in col a and! b like row 4 and 5.
> I want to do some calculations on col c within the duplicated rows and
> merge them afterwards:
>
> layer <- function(x) round((1-prod(1-x/100))*100,0)
> (covnew <- aggregate(c, list(a=a, b=b), layer))
>
> This works fine, but not with 1 mill. rows because of memory space
> limitations.
> So I thought to split the dataframe into the majority of unique rows on
> one hand and all duplicated rows on the other:
>
> With
> subset(obs, a %in% a[duplicated(a)])
> and !a respectively this works fine for single column comparison.
> This must be also possible for two column comparison, but I can`t get it.
>
> Thanks
> Florian
>
> --
> Dr. Florian Jansen
> Geobotany & Nature Conservation
> Institute for Botany and Landscape Ecology
> Ernst-Moritz-Arndt-University
> Grimmer Str. 88
> 17487 Greifswald - Germany
> +49 (0)3834 86 4147
>
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-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

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