Question

Python question.

I have a list (A) of numpy object arrays (B). I’d like to get the mean of one of the object variables for all the objects in the B array. Right now, I’m just parsing through the B array, summing the variable and dividing it by the number of objects in B. Is there a better or more pythonic way to do this?

It would also be great, if I could get the mean of all objects in the A list (i.e. all objects)

Answer 1

If you have a numpy array, you can just call the mean method:

In [24]: import numpy as np

In [25]: b = np.arange(5)

In [26]: b
Out[26]: array([0, 1, 2, 3, 4])

In [27]: b.mean()
Out[27]: 2.0

If you have a list of numpy arrays, getting the mean of each numpy is just:

In [28]: A = [np.arange(i) for i in range(3, 6)]

In [29]: A
Out[29]: [array([0, 1, 2]), array([0, 1, 2, 3]), array([0, 1, 2, 3, 4])]

In [30]: for B in A: print B.mean()
1.0
1.5
2.0

Or, if you’re trying to get the mean of all the elements (over all elements of B in A), use the sum method:

In [31]: sum(B.sum() for B in A) / sum(len(B) for B in A)
Out[31]: 1.5833333333333333