Ahhh, I see my error, thanks to Steve and others who mailed me off list.
Perhaps reading a little too quickly, I mis-interpreted the help for
ddply, in particular, the second argument:
> ".variables: variables to split data frame by, as quoted variables, a
> formula or character vector"
I assumed that I could select entire columns (i.e. the *variables*
that comprise my data.frame) using this argument.
Thx again,
- S.
On Apr 7, 2010, at 6:13 PM, Steve Lianoglou wrote:
Howdy,
I'm no plyr master, but here's my 2 cents ...
On Wed, Apr 7, 2010 at 5:15 PM, Stuart Andrews
<stu.andr...@gmail.com> wrote:
Hi,
I am confused by results from:
ddply(aa, names(aa), colwise(sum))
I thought ddply was just calling colwise(sum)() with each column.
However
ddply() returns a 13 x 5 result !!
The general result I expected is similar to that of apply() , or
using
colwise(sum)() alone. Shouldn't ddply() produce the same ?
Not sure what exactly is happening, but I don't think I'd expect ddply
to produce the same as the example you gave, since the second arg to
ddply determines how the aa data.frame should be split (row-wise)
before the colwise(...) do-hicky is called.
I'm not sure, but what are you trying to get at by row-wise splitting
`aa` by c('a', 'b', 'c', 'd', 'e') [ie. namaes(aa)]?
Thanks in advance for your help,
- Stuart Andrews
set.seed(1234)
aa = as.data.frame(matrix(rnorm(100)>0.3,nrow=20))
names(aa) = c('a','b','c','d','e')
head(aa)
a b c d e
1 FALSE FALSE FALSE TRUE TRUE
2 TRUE TRUE FALSE TRUE FALSE
3 TRUE TRUE FALSE TRUE TRUE
4 TRUE FALSE FALSE TRUE FALSE
5 TRUE FALSE FALSE TRUE FALSE
6 FALSE FALSE FALSE FALSE TRUE
ddply(aa, names(aa), colwise(sum))
a b c d e
1 0 0 0 0 0
2 0 0 0 0 2
3 0 0 0 4 0
4 0 0 0 1 1
5 0 0 1 0 0
6 0 0 2 0 2
7 0 0 1 1 0
8 0 2 0 0 0
9 0 1 0 0 1
10 1 0 0 0 0
11 2 0 0 0 2
12 1 0 0 1 0
13 1 0 0 1 1
apply(as.matrix(aa),2,sum)
a b c d e
5 3 4 8 9
colwise(sum)(aa)
a b c d e
1 5 3 4 8 9
... Isn't ddply() just doing something like this for each column??
colwise(sum)(aa[,1,drop=F])
a
1 5
That's what colwise is doing per each column of the data.frame it's
working on ... ddply does the split-by-row/apply/merge magic on the
data frame and is giving colwise smaller chunks of `aa` to work on at
a time...
So, to summarize, I think you just need to figure out the correct 2nd
arg to ddply for your specific problem.
-steve
--
Steve Lianoglou
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
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