title: Combine two numpy arrays and covert them into a dataframe
body: <p>I have two Dataframes (X &amp; y) sliced off the main dataframe <code>df</code> as below : </p>
  
  <pre><code> X = df.ix[:,df.columns!='Class']
   y = df.ix[:,df.columns=='Class']
  
   from imblearn.over_sampling  import SMOTE
   sm = SMOTE()
  
   X_resampled , y_resampled = sm.fit_sample(X,y.values.ravel())
  </code></pre>
  
  <p>The last line returns a <code>numpy</code> 2-d array for <code>X_resampled</code> and <code>y_resampled</code>.
  So I would want to know how to convert <code>X_resampled</code> and <code>y_resampled</code> back into a <code>dataframe</code>.</p>
  
  <p>Example Data : </p>
  
  <pre><code> X_resampled :Dimensions(2,30) : 2 rows,30 columns
  
      array([[ 0.        , -1.35980713, -0.07278117,  2.53634674,  1.37815522,
              -0.33832077,  0.46238778,  0.23959855,  0.0986979 ,  0.36378697,
               0.09079417, -0.55159953, -0.61780086, -0.99138985, -0.31116935,
               1.46817697, -0.47040053,  0.20797124,  0.02579058,  0.40399296,
               0.2514121 , -0.01830678,  0.27783758, -0.11047391,  0.06692807,
               0.12853936, -0.18911484,  0.13355838, -0.02105305,  0.24496426],
             [ 0.        ,  1.19185711,  0.26615071,  0.16648011,  0.44815408,
               0.06001765, -0.08236081, -0.07880298,  0.08510165, -0.25542513,
              -0.16697441,  1.61272666,  1.06523531,  0.48909502, -0.1437723 ,
               0.63555809,  0.46391704, -0.11480466, -0.18336127, -0.14578304,
              -0.06908314, -0.22577525, -0.63867195,  0.10128802, -0.33984648,
               0.1671704 ,  0.12589453, -0.0089831 ,  0.01472417, -0.34247454]])
  
  
          y_resampled :Dimensions (2,) - Coressponding to the two rows of X_resampled.
  
          array([0, 0], dtype=int64)
  </code></pre>