title: numpy.ndarray to dataframe conversion - dimension issues
body: <p>I am trying to convert an array into a <code>df</code>, with an index copied from <code>another_df</code>.</p>
  <pre><code>another_df:
          test1               test2               test3               test4               test5
  test1   0.0                 0.8                 0.6                 0.6                 0.2857142857142857
  test2   0.8                 0.0                 0.5                 1.0                 0.8571428571428571
  test3   0.6                 0.5                 0.0                 1.0                 0.7142857142857143
  test4   0.6                 1.0                 1.0                 0.0                 0.7142857142857143
  test5   0.2857142857142857  0.8571428571428571  0.7142857142857143  0.7142857142857143  0.0
  
  print (array)
  [[ 0.23052147  0.03058967]
   [-0.54449458 -0.08481665]
   [-0.21274323 -0.39635658]
   [ 0.13880332  0.58125618]
   [ 0.38791301 -0.13067262]]
  
  print (type(array))
  &lt;class 'numpy.ndarray'&gt;
  
  df = pd.DataFrame(array, 
                    index = another_df.index, 
                    columns = ['x','y'])
  </code></pre>
  <p>It does this fine - <code>df</code> is:</p>
  <pre><code>        x                   y
  test1   0.2305214680511617  0.03058967262464556
  test2   -0.544494575705709  -0.08481665342258861
  test3   -0.2127432294443813 -0.396356582859552
  test4   0.13880332309442767 0.5812561804072454
  test5   0.38791301400450073 -0.13067261674975036
  </code></pre>
  <p>However, I also get <code>ValueError: Shape of passed values is (5, 1), indices imply (5, 2)</code>.  This is very confusing, as</p>
  <p>(i) my function completes fine despite the error, which according to the stack trace happens before any return statements.</p>
  <p>(ii) my array looks 2d, so I'm not sure why it's getting read as 1d (which is what looks like is happening).</p>
  <p>Any ideas for the above, and can I ignore it as it seems to be returning OK?</p>
  <p><em>edit - variable typo</em></p>