python - Calculate mean across dimension in a 2D array

Question

I have an array a like this:

a = [[40, 10], [50, 11]]

I need to calculate the mean for each dimension separately, the result should be this:

[45, 10.5]

45 being the mean of a[*][0] and 10.5 the mean of a[*][1].

What is the most elegant way of solving this without using a loop?

Answer 1

a.mean() takes an axis argument:

In [1]: import numpy as np

In [2]: a = np.array([[40, 10], [50, 11]])

In [3]: a.mean(axis=1)     # to take the mean of each row
Out[3]: array([ 25. ,  30.5])

In [4]: a.mean(axis=0)     # to take the mean of each col
Out[4]: array([ 45. ,  10.5])

Or, as a standalone function:

In [5]: np.mean(a, axis=1)
Out[5]: array([ 25. ,  30.5])

The reason your slicing wasn't working is because this is the syntax for slicing:

In [6]: a[:,0].mean() # first column
Out[6]: 45.0

In [7]: a[:,1].mean() # second column
Out[7]: 10.5