[R] recommended combo of apps for new user?
mjb2000 at gmail.com
Sat Aug 18 23:34:57 CEST 2007
[i sent this message earlier but apparently should have sent it plain
text, as follows..]
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
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