On 31/01/2009 3:26 PM, Christian Brechbühler wrote:
On Sat, Jan 31, 2009 at 10:13 AM, Peter Dalgaard
<p.dalga...@biostat.ku.dk>wrote:
Duncan Murdoch wrote:
On 31/01/2009 7:31 AM, Andrew Piskorski wrote:
On Fri, Jan 30, 2009 at 11:51:00AM -0500, Simon Urbanek wrote:
Subject: Re: [Rd] (PR#13487) Segfault when mistakenly calling
[.data.frame
ever tried drop=FALSE ?
Simon, no, the drop=FALSE argument has nothing to do with what
Christian was talking about. The kind of thing he meant is PR# 8192,
"Subject: [ subscripting sometimes loses names":
http://bugs.r-project.org/cgi-bin/R/wishlist?id=8192
In that bug report you were asked to provide simple examples, and you
didn't.
...
I just tracked this one down, and can put together this simple example:
> (1:3)["no"]
[1] NA
where I think you would want the name "no" attached to the output.
No, it has nothing to do with indexing by name. It's about preserving
existing names when subsetting.
I think you misread my message.
And the other two cases where you list "BAD" behaviour? I didn't track them
down.
I did, and they boil down to variations of
data.frame(val=1:3,row.names=letters[1:3])[,1]
[1] 1 2 3
but it's not obvious that the result should be named using the row.names
and (in particular) whether or why it should differ from .....[[1]] and
....$val. Given that for most purposes, extracting the relevant names would
just be unnecessary red tape, I'd say that we can do without it.
Compare
data.frame(val=1:3,row.names=letters[1:3])[,1]
[1] 1 2 3
as.matrix(data.frame(val=1:3,row.names=letters[1:3]))[,1]
a b c
1 2 3
X[,1] preserves row names if X is a matrix, and loses them if X is a data
frame. To me, this is ugly and inconsistent.
One might argue that having names and dimnames at all is "red tape", and
wastes memory and computational efficiency -- after all, Fortran arrays had
no names. But R chose to drag along the names (sometimes), and it can be
very helpful to us humans. Now R should do it consistently.
In one case you're working with a matrix, and in the other, a dataframe.
So perfect consistency is impossible: matrices and dataframes are not
the same. So it's a matter of deciding how much consistency is worth
pursuing. Now, it seems nobody thinks this is worth pursuing: so it
won't get changed.
To get it changed, you should make the change, then investigate what
would break the change were adopted, and what would become slower, etc.
Or convince someone else to do that. But the fact that you think it's
ugly is probably not convincing.
Duncan Murdoch
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