David Winsemius wrote:
>
>
> On Jul 17, 2009, at 3:24 PM, Ulrike Grömping wrote:
>
>>
>> David,
>>
>> thanks. Your explanation does not quite fit, though, as it refers to
>> using
>> function data.frame, while I assigned the new column with $<-.
>> poly() does
>> return an object of classes poly and matrix, not model.matrix,
>
> But model.matrix is not a class as far as I can tell. It has no
> "is.<>" function, and examining a sample model matrix does not
> indicate that it carries a special class attribute.
>
It is a class all right, but is apparently not per default assigned to
objects generated with function model.matrix. Try
mm <- model.matrix(lm(swiss))
str(data.frame(swiss,mm))
class(mm) <- c("model.matrix","matrix")
str(data.frame(swiss,mm))
David Winsemius wrote:
>
>>...
>> It is just the assignment with "$" that does behave differently -
>> and not
>> only for poly objects but for any matrix object. After I eventually
>> remembered how to get to the documentation of extractors
>> (?"$<-.data.frame"), I found this behavior documented there in the
>> section
>> on Coercion. Nevertheless, this does seem to contradict the
>> understanding of
>> what a data frame is. I am aware that data frames are lists, but
>> they are of
>> course special lists, requiring that all list elements have the same
>> number
>> of rows. So far I thought that all list elements also have the same
>> number
>> of columns, namely just one. In fact, the documentation of function
>> data.frame states that
>>
>> "A data frame is a list of variables of the same length with unique
>> row
>> names, given class "data.frame".",
>>
>> which would imply such a rule.
>
> Except that the same page asserts:
>
> "Note that when the replacement value is an array (including a matrix)
> it is not treated as a series of columns (as data.frame and
> as.data.frame do) but inserted as a single column."
>
This is the piece on coercion in the extract documentation I was also
referring to.
David Winsemius wrote:
>
> ... which is more on point documentation than what I offered earlier.
> I also found that the <-I() construct within the data.frame() would
> replicate the behavior of df$x<-<mtx> (as was documented in
> data.frame's help:
> > dat2 <- data.frame(X1=1:10, X2=LETTERS[1:10], X1poly <- I(poly(dat
> $X1,3)) )
> > length(dat2)
> [1] 3
> > dat2[1,3]
> 1 2 3
> [1,] -0.4954337 0.522233 -0.4534252
> attr(,"class")
> [1] "poly" "matrix"
>> The possibility of a matrix with more than
>> one column being a column of the data frame contradicts this piece of
>> documentation, since the length of the matrix is not the same as the
>> length
>> of the other columns (e.g. length(poly(dat$X1,3) is 30, not 10 like
>> for the
>> other variables). Or would one consider the columns of the matrix
>> X1poly the
>> variables, but X1poly a column ? I'm not trying to be difficult, I
>> just find
>> this quite confusing and wonder about the consequences when using
>> such a
>> data frame in analyses.
>
> The could be unforeseen consequences, but I am not the right person to
> answer for all of those possibilities. I can see another instance
> where it would be desirable to have tuples included in data.frames as
> arrays and that is in the representation of complex numbers, but it
> appears that the internal representation of complex numbers is more
> completely hidden from casual view than is the capacity of data.frames
> to carry matrices. If you have a compelling argument to change the
> behavior of [<-.data.frame, you will need to take it up with the
> developers.
>
I have no idea which behavior is more useful; also, if this behavior has
been
around for a long time, changing it would presumably break some code. I
suppose I would just opt for clearer documentation of the data frame class.
The bugs interface is currently down, I may file a documentation wish or
documentation bug later.
Best regards, Ulrike
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