Did you have something like this in mind?

#prepare the data
traits <- data.frame(letters[1:9],
        sample(letters, 9),
        sample(letters, 9),
        sample(letters, 9),
        sample(letters, 9),
        sample(letters, 9),
        sample(letters, 9),
        sample(letters, 9),
        sample(letters, 9))
colnames(traits) <- c("species", 1:8)
comcops <- data.frame(community = paste("com", rep(1:3, each = 3), sep =
""),
        species = sample(letters[1:9], 9, replace = TRUE))

> traits
  species 1 2 3 4 5 6 7 8
1       a c u j f e x w s
2       b k w w v m l d k
3       c j x q r a t a n
4       d b v o w p o c a
5       e h g g a n n r d
6       f x d b p v i p j
7       g r i m k g r l v
8       h p l n l t p m z
9       i g a l d x h z q

> comcops
  community species
1      com1       f
2      com1       c
3      com1       b
4      com2       c
5      com2       a
6      com2       h
7      com3       h
8      com3       d
9      com3       e

all(comcops$species %in% traits$species) #check

#mambo jumbo
traits[as.character(comcops$species), ]
mix.all <- apply(comcops, 1, function(x, df.traits) {
            out <- df.traits[which(df.traits$species == x[2]), ]
            return(out)
        }, df.traits = traits)
mix.all <- do.call("rbind", mix.all)

final <- cbind(community = comcops$community, mix.all)

> split(final, final$community)
$com1
  community species 1 2 3 4 5 6 7 8
6      com1       f x d b p v i p j
3      com1       c j x q r a t a n
2      com1       b k w w v m l d k

$com2
   community species 1 2 3 4 5 6 7 8
31      com2       c j x q r a t a n
5       com2       a c u j f e x w s
8       com2       h p l n l t p m z

$com3
   community species 1 2 3 4 5 6 7 8
81      com3       h p l n l t p m z
4       com3       d b v o w p o c a
51      com3       e h g g a n n r d


To maximize your chances of getting a reply, I would suggest you provide the
list with a minimal working example of (fake) data you're working with.


Cheers,
Roman



On Thu, Jan 6, 2011 at 12:39 PM, Peter Francis <peterfrancis@me.com> wrote:

> Dear List,
>
> I have a data frame called trait with roughly 800 species in, each species
> have 15 columns of information:
>
> Species         1       2       3       etc..
> a                       t       y       h
> b                       f       j       u
> c                       r       y       u
>
> etc..
>
>
> I then have another data frame called com with the composition of species
> in each region, there are 506 different communities:
>
> community       species
> NA1102          a
> NA1102          c
> NA0402          b
> NA0402          c
> AT1302          a
> AT1302          b
>
> etc..
>
>
> What i want to do is extract the information held in the first data frame
> for each community and save this as a new data frame.
>
> Resulting in : -
>
> community_NA1102
>
> a                       t       y       h
> c                       r       y       u
>
> community_NA0402
>
> b                       f       j       u
> c                       r       y       u
>
> Thanks in advance for any suggestions / code.
>
> _______________________________________________
> R-sig-ecology mailing list
> R-sig-ecology@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>



-- 
In God we trust, all others bring data.

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