Thanks so much for the many responses on and off this email list!

I think it's helped me reach a resolution.  I'm going to use R on my current
small project for something relatively self-contained, such as some final
tests and graphics. I figure this will help me learn some basics about
interacting with R without getting too bogged down in setting up a new
database system -- which sounds like a job all on its own.  After I
understand a bit more about R's capabilities I'll ease into the database
part.

Cheers, Martin


On 8/19/07, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
>
> Regarding RODBC vs. DBI-based packages (RSQLite, RMySQL, etc.) its
> my perception, possibly mistaken, that apart from any consideration of
> the R packages themselves, ODBC (which originated in the Windows world)
> is more widely used on Windows than UNIX.  Also ODBC has the problem
> that one must configure it which puts an extra step into the
> process.  Clear
> documentation on how to do such ODBC configuration may be difficult to
> find.
>
> On the other hand the RODBC package itself seems to be maintained
> very well and is typically available for new versions of R before the
> DBI-based packages.
>
> On 8/19/07, Prof Brian Ripley <[EMAIL PROTECTED]> wrote:
> > Some additional comments on the DBMS front.
> >
> > (a) SPSS is not a DBMS, so it is not clear that you need this. But if
> you
> > do and are storing valuable data in a DBMS a lot of further questions
> come
> > into play, like how you are going to do backups.  I'd say PostgreSQL was
> > really only for professional-level administrators.  My sysadmins
> recommend
> > MySQL for most people.  We do also run PostgreSQL and they find it a lot
> > trickier to maintain.
> >
> > 'dozens of columns and thousands of rows' is not big.  A data frame with
> > 50 columns and 5000 rows would only take 2Mb to store, and R will easily
> > handle 100x with 4GB of RAM (and if you have less, get 4GB).  So storing
> > data in .rda (R's save() format) is most likely viable.  R's indexing
> etc
> > operations make it good at data manipulation, and using a DBMS will
> > involve learning SQL, a non-trivial cost.
> >
> > (b) You have a choice of interfaces to a DBMS, RODBC and the DBI+
> family,
> > e.g. DBI+RMySQL and DBI+RSQLite.  I'm biased, but I find RODBC more
> > intuitive, and many people have reported it to be faster.  If all you
> want
> > is non-permanent storage for manipulation of large data sets, consider
> > also SQLiteDF.
> >
> > On Sat, 18 Aug 2007, Duncan Murdoch wrote:
> >
> > > Martin Brown wrote:
> > >> [i sent this message earlier but apparently should have sent it plain
> > >> text, as follows..]
> > >>
> > >> Hi there,
> > >>
> > >> I would like some advice, not so much about how to use R, but about
> > >> software that I need to complement R.  I've rooted around in the
> FAQ's
> > >> and done a few searches on this mailing list but haven't quite found
> > >> the perspective I need.
> > >>
> > >> I am an experienced data analyst in my field (forest ecology and
> > >> ecological monitoring) but new to R. I am a long time user of SPSS
> and
> > >> have gotten pretty handy with it.  However, I am frustrated with SPSS
> > >> for several reasons:  There's the cost (I'm a freelancer; I pay for
> my
> > >> software myself);  the Windows dependence (I use Kubuntu as my usual
> > >> OS now, and switching back and forth is a pain); the horrible
> > >> inefficiency when I do certain types of file manipulations; and the
> > >> inability to do the kind of publication-quality graphs I want... I've
> > >> usually ended up using a commercial graphing program (another source
> > >> of expense and limitation).
> > >>
> > >> I'd like to switch to using R on Kubuntu, for all those reasons.  In
> > >> addition I think the mathematical formality that R encourages might
> be
> > >> good for me.
> > >>
> > >> However, reviewing the FAQ's on the R project web site makes me
> > >> realize that I've been using SPSS as three kinds of software really:
> > >> a DBMS; a statistical analysis package; and a graphing package.  It
> > >> looks like moving to R might involve learning three kinds of
> software,
> > >> not just one.  I wonder:
> > >>
> > >> 1) What open-source DBMS works most seamlessly with R?  I have seen
> > >> MySQL recommended but wonder if there are alternatives.  I sometimes
> > >> need to handle big data files.  In fact a lot of my work involves
> > >> exploratory and descriptive analyses of rather large and messy
> > >> databases from ecological monitoring, rather than statistical tests
> > >> per se.  In SPSS the data files I have been generating have dozens of
> > >> columns and thousands of rows, often with value and variable labels
> > >> helpful for documenting my work.
> >
> > See above.
> >
> > >
> > > I think you won't find much difference in the R interface between
> MySQL,
> > > PostgreSQL, or SQLite.  The choice should be made based on the
> qualities
> > > of the database (and I don't know enough about the differences to give
> a
> > > recommendaton.)
> > >> 2) For the purpose of creating publication-quality graphs, do R users
> > >> typically need to go outside of the R system? If so, what open-source
> > >> programs would you all recommend?
> > >>
> > > R is great for this, but you might need to go outside for some
> > > specialized stuff (e.g. medical imaging).
> > >
> > >> 3) Any other software I need to learn that would make my work in R
> > >> more productive? (for example, a code editor).
> > >
> > > A lot of people are happy with ESS mode in Emacs.
> > >
> > > Duncan Murdoch
> > >
> > > ______________________________________________
> > > R-help@stat.math.ethz.ch mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> > >
> >
> > --
> > Brian D. Ripley,                  [EMAIL PROTECTED]
> > Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> > University of Oxford,             Tel:  +44 1865 272861 (self)
> > 1 South Parks Road,                     +44 1865 272866 (PA)
> > Oxford OX1 3TG, UK                Fax:  +44 1865 272595
> >
> > ______________________________________________
> > R-help@stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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