Questions about mathematical and statistical functionality in Python

[Talbot Katz]

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  --
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