title: pandas dataframe how to do "elementwise" concatenation?
body: <p>I have two pandas dataframes <code>A,B</code> with identical shape, index and column. Each element of <code>A</code> is a <code>np.ndarray</code> with shape <code>(n,1)</code>, and each element of <code>B</code> is a float value. Now I want to <em>efficiently</em> append <code>B</code> elementwise to <code>A</code>. A minimal example:</p>
  
  <pre><code>index = ['fst', 'scd']
  
  column = ['a','b']
  
  A
  Out[23]: 
            a       b
  fst  [1, 2]  [1, 4]
  scd  [3, 4]  [3, 2]
  
  B
  Out[24]: 
              a         b
  fst  0.392414  0.641136
  scd  0.264117  1.644251
  
  resulting_df = pd.DataFrame([[np.append(A.loc[i,j], B.loc[i,j]) for i in index] for j in column], columns=column, index=index)
  
  resulting_df
  Out[27]: 
                                a                           b
  fst  [1.0, 2.0, 0.392414377685]  [3.0, 4.0, 0.264117463613]
  scd  [1.0, 4.0, 0.641136433253]   [3.0, 2.0, 1.64425062851]
  </code></pre>
  
  <p>Is there something similar to <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.applymap.html" rel="nofollow noreferrer"><code>pd.DataFrame.applymap</code></a> that can operate elementwise between two instead of just one pandas dataframe? </p>