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
