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I'm actually working on a stats PhD (in the early stages) and I've made it my goal to build a lot of Python software as I go along. So if you have the inclinati
by wesm 16y ago
I'm actually working on a stats PhD (in the early stages) and I've made it my goal to build a lot of Python software as I go along. So if you have the inclination I'd recommend giving it a shot. When you consider the wealth of tools out there for both high level (NumPy-based) and lower-level computation (e.g. Cython, for speeding up algorithms), and software development (especially interactive debugging and testing), it's a fairly compelling proposition (for me, at least).
But long story short is that people are working on making Python more amenable to applied statistics work. And the more people working toward that goal, the faster we'll get there.
So I would recommend: join numpy-discussion and scipy-user mailing lists, explore projects out there-- last few SciPy conferences are a decent place to start.
- hyperbovine 16y agoYes, it's a tantalizing prospect because so much of the groundwork has already been laid. I have the sense that something is just needed to tie it all together into a nice, easy-to-use package with a consistent interface, easily-understood object model, etc. My masters is in math, and I have watched Sage create a small revolution in the past couple years by doing exactly this. Food for thought...
- wesm 16y agoI agree-- and doing so could make some pretty serious waves across both academia and industry. You should join the discussion on the mailing lists: in particular pystatsmodels and the numpy/scipy lists. Any input would be much appreciated.