title: How to add names to a numpy array without changing its dimension?
body: <p>I have an existing two-column numpy array to which I need to add column names. Passing those in via <code>dtype</code> works in the toy example shown in <strong>Block 1</strong> below. With my actual array, though,  as shown in <strong>Block 2</strong>, the same approach is having an unexpected (to me!) side-effect of changing the array dimensions.</p>
  <p>How can I convert my actual array, the one named <code>Y</code> in the second block below, to an array having named columns, like I did for array <code>A</code> in the first block?</p>
  <p><strong>Block 1:</strong> (Columns of <code>A</code> named without reshaping dimension)</p>
  <pre><code>import numpy as np
  A = np.array(((1,2),(3,4),(50,100)))
  A
  # array([[  1,   2],
  #        [  3,   4],
  #        [ 50, 100]])
  dt = {'names':['ID', 'Ring'], 'formats':[np.int32, np.int32]}
  A.dtype=dt
  A
  # array([[(1, 2)],
  #        [(3, 4)],
  #        [(50, 100)]], 
  #       dtype=[('ID', '&lt;i4'), ('Ring', '&lt;i4')])
  </code></pre>
  <p><strong>Block 2:</strong> (Naming columns of my actual array, <code>Y</code>, reshapes its dimension)</p>
  <pre><code>import numpy as np
  ## Code to reproduce Y, the array I'm actually dealing with
  RING = [1,2,2,3,3,3]
  ID = [1,2,3,4,5,6]
  X = np.array([ID, RING])
  Y = X.T
  Y
  # array([[1, 3],
  #        [2, 2],
  #        [3, 2],
  #        [4, 1],
  #        [5, 1],
  #        [6, 1]])
  
  ## My unsuccessful attempt to add names to the array's columns    
  dt = {'names':['ID', 'Ring'], 'formats':[np.int32, np.int32]}
  Y.dtype=dt
  Y
  # array([[(1, 2), (3, 2)],
  #        [(3, 4), (2, 1)],
  #        [(5, 6), (1, 1)]], 
  #       dtype=[('ID', '&lt;i4'), ('Ring', '&lt;i4')])
  
  ## What I'd like instead of the results shown just above
  # array([[(1, 3)],
  #        [(2, 2)],
  #        [(3, 2)],
  #        [(4, 1)],
  #        [(5, 1)],
  #        [(6, 1)]],
  #       dtype=[('ID', '&lt;i4'), ('Ring', '&lt;i4')])
  </code></pre>