At 2:26 PM -0400 5/14/08, Gabor Grothendieck wrote:
The key difference is inheritance.
Objects consisting of data frames with attributes, including a class attribute
such as c("myclass", "data.frame), can inherit data frame methods but a list
with a data frame component will require entirely new methods to be
constructed
for everything.
Or always specify the data frame element of the list, instead of the
list, when writing expressions that need the dataframe. Which could
be a pain!
For the attributes approach, one will have to watch for actions that
remove unexpected attributes. For example, if you have two data
frames, each with your own added attribute, what will happen to the
attributes if you merge() them?
You might check the Hmisc package; as I recall there are some
features in it for adding attributes (e.g., "units", though I don't
remember for sure).
-Don
On Wed, May 14, 2008 at 2:15 PM, Bert Gunter <[EMAIL PROTECTED]> wrote:
R-Fellow Travellers:
Asked from the perspective of a software development amateur ...
Suppose one wishes to create data structures that have both data and
metadata -- e.g. a data.frame and details about where, when, and by whom the
data were gathered (specifics not important here).
1. Is there any inherent processing advantage in R in representing this as a
list that contains both the data and metadata as components vs as a
data.frame with the metadata as attributes?
2. Is there a compelling software architecture argument to favor one vs the
other?
I suspect the answer is no in both cases, but I thought I'd ask. This seems
to be mainly relevant for S3 programming, as in S4 one might stick the info
into different slots (if one wishes to dispatch on them).
Cheers to all,
Bert Gunter
Genentech
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---------------------------------
Don MacQueen
Lawrence Livermore National Laboratory
Livermore, CA, USA
925-423-1062
[EMAIL PROTECTED]
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