Average of a numpy array returns NaN

try this:

>>> np.nanmean(ngma_heat_daily)

This function drops NaN values from your array before taking the mean.

Edit: the reason that average(ngma_heat_daily[ngma_heat_daily != nan]) doesn't work is because of this:

>>> np.nan == np.nan
False

according to the IEEE floating-point standard, NaN is not equal to itself! You could do this instead to implement the same idea:

>>> average(ngma_heat_daily[~np.isnan(ngma_heat_daily)])

np.isnan, np.isinf, and similar functions are very useful for this type of data masking.

Also, there is a function named nanmedian which ignores NaN values. Signature of that function is: numpy.nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=<no value>)