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.
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?
3) Any other software I need to learn that would make my work in R more
productive? (for example, a code editor).

Thank you for your time,

Martin J. Brown
Portland, Oregon

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