title: pandas.Timedelta conversion to seconds in float is too slow
body: <p>I have a dataframe named <code>_df</code>, whose <code>len</code> is 3.7M, having two <code>pandas.Timestamp</code> columns <code>timestamp</code> and <code>lead_timestamp</code>. I want to add a new column <code>diff_timestamp</code> as differences of the two columns in seconds.</p>
  <p>The following snippet</p>
  <pre><code>_df[&quot;diff_timestamp&quot;] = _df.timestamp - _df.lead_timestamp
  </code></pre>
  <p>cost less than 0.1 second.</p>
  <p>But when I modify it as following:</p>
  <pre><code>_df[&quot;diff_timestamp&quot;] = (_df.timestamp - _df.lead_timestamp).map(lambda x: x.seconds)
  </code></pre>
  <p>It takes more than 25 seconds, about 300 times longer.</p>
  <p>Is there any more efficient way ?</p>