On Jun 14, 4:02 pm, "Talbot Katz" <[EMAIL PROTECTED]> wrote: > Greetings Pythoners! > > I hope you'll indulge an ignorant outsider. I work at a financial > software > firm, and the tool I currently use for my research is R, a software > environment for statistical computing and graphics. R is designed with > matrix manipulation in mind, and it's very easy to do regression and time > series modeling, and to plot the results and test hypotheses. The kinds > of > functionality we rely on the most are standard and robust versions of > regression and principal component / factor analysis, bayesian methods > such > as Gibbs sampling and shrinkage, and optimization by linear, quadratic, > newtonian / nonlinear, and genetic programming; frequently used graphics > include QQ plots and histograms. In R, these procedures are all available > as functions (some of them are in auxiliary libraries that don't come with > the standard distribution, but are easily downloaded from a central > repository). > > For a variety of reasons, the research group is considering adopting > Python. > Naturally, I am curious about the mathematical, statistical, and > graphical > functionality available in Python. Do any of you out there use Python in > financial research, or other intense mathematical/statistical computation? > Can you compare working in Python with working in a package like R or S- > Plus > or Matlab, etc.? Which of the procedures I mentioned above are available > in > Python? I appreciate any insight you can provide. Thanks! > > -- TMK -- > 212-460-5430 home > 917-656-5351 cell > > > -- > http://mail.python.org/mailman/listinfo/python-list
It is worth noting that there's a bridge available to allow python to integrate cleanly with R, the Rpy project: http://rpy.sourceforge.net/ Which should allow you to use python for whatever it is you need without abandoning R for your mathematical/statistical work. --------- John Krukoff [EMAIL PROTECTED] -- http://mail.python.org/mailman/listinfo/python-list
