title: Sum along axis in numpy array
body: <p>I want to understand how this ndarray.sum(axis=) works. I know that axis=0 is for columns and axis=1 is for rows.
  But in case of 3 dimensions(3 axes) its difficult to interpret below result.</p>
  
  <pre><code>arr = np.arange(0,30).reshape(2,3,5)
  
  arr
  Out[1]: 
  array([[[ 0,  1,  2,  3,  4],
          [ 5,  6,  7,  8,  9],
          [10, 11, 12, 13, 14]],
  
         [[15, 16, 17, 18, 19],
          [20, 21, 22, 23, 24],
          [25, 26, 27, 28, 29]]])
  
  arr.sum(axis=0)
  Out[2]: 
  array([[15, 17, 19, 21, 23],
         [25, 27, 29, 31, 33],
         [35, 37, 39, 41, 43]])
  
  
  arr.sum(axis=1)
  Out[8]: 
  array([[15, 18, 21, 24, 27],
         [60, 63, 66, 69, 72]])
  
  arr.sum(axis=2)
  Out[3]: 
  array([[ 10,  35,  60],
         [ 85, 110, 135]])
  </code></pre>
  
  <p>Here in this example of <strong>3 axes array</strong> of shape(2,3,5), there are 3 rows and 5 columns. But if i look at this array as whole, seems like only two rows (both with 3 array elements).</p>
  
  <p>Can anyone please explain how this sum works on array of 3 or more axes(dimensions).</p>