How to use numpy with 'None' value in Python?

You are looking for masked arrays. Here's an example.

import numpy.ma as maa = ma.array([1, 2, None], mask = [0, 0, 1])print "average =", ma.average(a)

From the numpy docs linked above, "The numpy.ma module provides a nearly work-alike replacement for numpy that supports data arrays with masks."

python numpy mean

haven't used numpy, but in standard python you can filter out None using list comprehensions or the filter function

>>> [i for i in [1, 2, None] if i != None][1, 2]>>> filter(lambda x: x != None, [1, 2, None])[1, 2]

and then average the result to ignore the None

python numpy mean

You can use scipy for that:

import scipy.stats.stats as stm=st.nanmean(vec)

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