mean, nanmean and warning: Mean of empty slice

Question

Say I construct two numpy arrays:

a = np.array([np.NaN, np.NaN])
b = np.array([np.NaN, np.NaN, 3])

Now I find that np.mean ret

Answer 1

A NaN value is defined to not be equal to itself:

>>> float('nan') == float('nan')
False
>>> np.NaN == np.NaN
False

You can use a Python conditional and the property of a nan never being equal to itself to get this behavior:

>>> a = np.array([np.NaN, np.NaN])
>>> b = np.array([np.NaN, np.NaN, 3])
>>> np.NaN if np.all(a!=a) else np.nanmean(a)
nan
>>> np.NaN if np.all(b!=b) else np.nanmean(b)
3.0

You can also do:

import warnings
import numpy as np

a = np.array([np.NaN, np.NaN])
b = np.array([np.NaN, np.NaN, 3])

with warnings.catch_warnings():
    warnings.filterwarnings('error')
    try:
        x=np.nanmean(a)
    except RuntimeWarning:
        x=np.NaN    
print x