[Rd] Bridging R to OpenOffice
lmada at gmx.net
Wed Mar 28 20:29:18 CEST 2007
Many thanks for the many kind replies. It is very reassuring to have
support from a strong community.
Hin-Tak Leung wrote:
> Hmm, if all you are interested is reading/writing Excel spreadsheets
> from R, there are much lighter and easier ways of doing it, than
> hooking up with openoffice. The Perl people have had
> Spreadsheet::ParseExcel and Spreadsheet::WriteExcel for years (and
> they work quite well, personal experience). Those are tiny
> (a couple of Mb's?) compared to the size of openoffice.
I believe that this R-OOo bridge should pursue a different path. I
favour the idea to facilitate access to R for common spreadsheet users.
As these users are less likely to learn the full S language, the
implemented method should by largely offer a GUI-driven interface to
important statistical (R)-functions (at least in the beginning; adding
further functionality later on).
Having an R package to read/write .ods files seems reasonable, too, (and
I would definitely like it) however this will not benefit the larger
spreadsheet community. Again, it will ease the life of power users, but
the novice must still first learn R. The package odfWeave (see R News
vol 6/4, October 2006) offers already basic support for OOo Writer files
and, while it currently lacks spreadsheet functionality, I am looking
forward to see it implemented, too.
1. Teaching Role
There are some deeper reasons why I cling to the R-OOo bridging idea. I
have read in my life hundreds of biomedical articles (probably even more
than a thousand) and I have a very bitter taste about the quality of
most of these articles. The statistics have played an important role in
The fact is, that most researchers will use a spreadsheet program to
gather their data. And most will use this spreadsheet program to do
their analysis, too. If this spreadsheet program offers more advanced
statistical methods (and also a sensible help file on these methods),
then some users will try to use them. Some of these will take the next
step, too, and will dwell a little bit deeper into statistics, thus
raising the quality of the research.
In this way, this bridge would have also a teaching role, persuading
some users to take a deeper look at statistics (especially learning more
advanced and various newer methods). It will make R more popular, too.
2. Implementing Advanced Statistical Functions in OOo
I do not favour this idea, because:
- newer methods are not always trivial to implement
- spreadsheet programs are notorious for poor statistical algorithms
- more resources (programmers, testing frameworks) are needed, when free
(and much better) alternatives already do exist
- community would have to form first (e.g. help, FAQ), while R already
has a large community
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