np.mean() vs np.average() in Python NumPy?

Question

I notice that

In [30]: np.mean([1, 2, 3])
Out[30]: 2.0

In [31]: np.average([1, 2, 3])
Out[31]: 2.0

However, there should be some differences, since after all they are two different functions.

What are the differences between them?

Answer 1

np.average takes an optional weight parameter. If it is not supplied they are equivalent. Take a look at the source code: Mean, Average

np.mean:

try:
    mean = a.mean
except AttributeError:
    return _wrapit(a, 'mean', axis, dtype, out)
return mean(axis, dtype, out)

np.average:

...
if weights is None :
    avg = a.mean(axis)
    scl = avg.dtype.type(a.size/avg.size)
else:
    #code that does weighted mean here

if returned: #returned is another optional argument
    scl = np.multiply(avg, 0) + scl
    return avg, scl
else:
    return avg
...