NumPy: calculate averages with NaNs removed

Question

How can I calculate matrix mean values along a matrix, but to remove nan values from calculation? (For R people, think na.rm = TRUE).

Here

Answer 1

This is built upon the solution suggested by JoshAdel.

Define the following function:

def nanmean(data, **args):
    return numpy.ma.filled(numpy.ma.masked_array(data,numpy.isnan(data)).mean(**args), fill_value=numpy.nan)

Example use:

data = [[0, 1, numpy.nan], [8, 5, 1]]
data = numpy.array(data)
print data
print nanmean(data)
print nanmean(data, axis=0)
print nanmean(data, axis=1)

Will print out:

[[  0.   1.  nan]
 [  8.   5.   1.]]

3.0

[ 4.  3.  1.]

[ 0.5         4.66666667]