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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