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 my judgment. 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 (non-robust implementation) - 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 Many thanks, Leonard ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
