title: Changing column datatype from Timestamp to datetime64
body: <p>I have a database I'm reading from excel as a pandas dataframe, and the dates come in Timestamp <code>dtype</code>, but I need them to be in <code>np.datetime64</code>, so that I can make calculations.</p>
  
  <p>I am aware that the function <code>pd.to_datetime()</code> and the <code>astype(np.datetime64[ns])</code> method do work. However, I am unable to update my dataframe to yield this datatype, for whatever reason, using the code mentioned above.</p>
  
  <p>I have also tried creating an acessory dataframe from the original one, with just the dates that I wish to update the typing, converting it to <code>np.datetime64</code> and plugging it back onto the original dataframe:</p>
  
  <pre><code>dfi = df['dates']
  dfi = pd.to_datetime(dfi)
  df['dates'] = dfi
  </code></pre>
  
  <p>But still it doesn't work. I have also tried updating values one by one:</p>
  
  <pre><code>arr_i = df.index
  for i in range(len(arr_i)):
      df.at[arri[l],'dates'].to_datetime64()
  </code></pre>
  
  <p><strong>Edit</strong>
  The root problem seems to be that the <code>dtype</code> of the column gets updated to <code>np.datetime64</code>, but somehow, when getting single values from within, they still have the <code>dtype = Timestamp</code></p>
  
  <p>Does anyone have a suggestion of a workaround that is fairly fast?</p>