title: keep both merging keys after pandas.merge_asof
body: <p>I have found this nice function  <code>pandas.merge_asof</code>.
  From the documentation</p>
  
  <pre><code>pandas.merge_asof(left, right, on=None, left_on=None, right_on=None)
  
  Parameters: 
  
  left : DataFrame
  right : DataFrame
  on : label
  
  Field name to join on. Must be found in both DataFrames.
  The data MUST be ordered. 
  Furthermore this must be a numeric column,such as datetimelike, integer, or float. 
  On or left_on/right_on must be given.
  </code></pre>
  
  <p>and it works as expected.</p>
  
  <p>However, my merged dataframe keeps as columns <code>on</code> only the one that originally was in <code>left</code>. I would need to keep them both, so to have </p>
  
  <pre><code>   mydf=pandas.merge_asof(left, right, on='Time')
  </code></pre>
  
  <p>and <code>mydf</code> to contain both <code>Time</code> from <code>left</code> and <code>right</code></p>
  
  <p>Example data:</p>
  
  <pre><code>a=pd.DataFrame(data=pd.date_range('20100201', periods=100, freq='6h3min'),columns=['Time'])
  b=pd.DataFrame(data=
                    pd.date_range('20100201', periods=24, freq='1h'),columns=['Time'])
  b['val']=range(b.shape[0])
  out=pd.merge_asof(a,b,on='Time',direction='forward',tolerance=pd.Timedelta('30min'))
  </code></pre>