David Cournapeau <david <at> ar.media.kyoto-u.ac.jp> writes: > You can use nanmean (from scipy.stats): >
I rejoiced when I saw this answer, because it looks like a function I can just drop in and it works. Unfortunately, nanmedian seems to be quite a bit slower than just using lists (ignoring nan values from my experiments) and a home-brew implementation of median. I was mostly using numpy for speed... I would like to try the masked array approach, but the Ubuntu packages for scipy and matplotlib depend on numpy. Does anybody know whether I can naively do "sudo python setup.py install" on a more modern numpy without disturbing scipy and matplotlib, or do I need to uninstall all three packages and install them manually from source? On my 64 bit machine, the Ubuntu numpy package is even more out of date: $ dpkg -l | grep numpy ii python-numpy 1:1.0.4-6ubuntu3 Does anybody know why this is? I might be willing to help bring the repository up to date, if anybody can give me pointers on how to do this. Peter _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
