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 <peterfran...@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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