Hi,
Has anyone run any R vs Python (numpy) tests?
I'd love to see what the differences performance-wise are, specially
handling large sparse matrices.
Since both rely on external C code, there might not be much of a
difference.
If you know and use both languages, what are the main differences and what
made you stick to one over another?
I also noticed that there are strong libraries for social networks on both.
python:
networkX: https://networkx.lanl.gov/wiki
pySNA: http://www.menslibera.com.tr/pysna/
R:
sna, network etc. see:
http://www.jstatsoft.org/v24
Has anyone run a bechmark of the two systems doing the same operation?
Which is the right environment for large social networks? Some packages
have bindings for both languages, and of course, there's a reliable way
to bind the two languages together, Rpy:
http://rpy.sourceforge.net/
So this may not be a big deal which one to pick.
Thanks,
-Jose
--
Jose Quesada, PhD.
Max Planck Institute, Human Development, Berlin
http://www.andrew.cmu.edu/~jquesada
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