title: Numpy concatenate 2D arrays with 1D array
body: <p>I am trying to concatenate 4 arrays, one 1D array of shape (78427,) and 3 2D array of shape (78427, 375/81/103). Basically this are 4 arrays with features for 78427 images, in which the 1D array only has 1 value for each image.</p>
  
  <p>I tried concatenating the arrays as follows:</p>
  
  <pre><code>&gt;&gt;&gt; print X_Cscores.shape
  (78427, 375)
  &gt;&gt;&gt; print X_Mscores.shape
  (78427, 81)
  &gt;&gt;&gt; print X_Tscores.shape
  (78427, 103)
  &gt;&gt;&gt; print X_Yscores.shape
  (78427,)
  &gt;&gt;&gt; np.concatenate((X_Cscores, X_Mscores, X_Tscores, X_Yscores), axis=1)
  </code></pre>
  
  <p>This results in the following error: </p>
  
  <blockquote>
    <p>Traceback (most recent call last):
      File "", line 1, in 
    ValueError: all the input arrays must have same number of dimensions</p>
  </blockquote>
  
  <p>The problem seems to be the 1D array, but I can't really see why (it also has 78427 values). I tried to transpose the 1D array before concatenating it, but that also didn't work. </p>
  
  <p>Any help on what's the right method to concatenate these arrays would be appreciated!</p>