title: Difference between pandas Timestamp and datetime
body: <p>I was tinkering around with converting <code>pandas.Timestamp</code> to the built in python <code>datetime</code>. I tried the following:</p>
  <pre><code>pandas_time = pd.Timestamp(year=2020, day=4, month=2, hour=0, minute=0, second=1)
  pandas_ts = pandas_time.timestamp()
  datetime_time = datetime.datetime.fromtimestamp(pandas_ts)
  datetime_ts = datetime_time.timestamp()
  </code></pre>
  <p>Looking at the variables gives this:</p>
  <pre><code>pandas_time:   2020-02-04 00:00:01
  datetime_time: 2020-02-04 01:00:01
  pandas_ts:   1580774401.0
  datetime_ts: 1580774401.0
  </code></pre>
  <p>So they both have the same timestamp but the dates differ by one hour.
  When I tried it the other way around, I got this:</p>
  <pre><code>datetime_time = datetime.datetime(year=2020, day=4, month=2, hour=0, minute=0, second=1)
  datetime_ts = datetime_time.timestamp()
  pandas_time = pd.Timestamp(datetime_time)
  pandas_ts = pandas_time.timestamp()
  
  pandas_time:   2020-02-04 00:00:01
  datetime_time: 2020-02-04 00:00:01
  pandas_ts:   1580774401.0
  datetime_ts: 1580770801.0
  </code></pre>
  <p>Now the dates are the same but the timestamps differ by 3600 (1 hour).
  I do know that I could use pandas <code>to_pydatetime</code> for conversion from pandas Timestamp to python datetime but I'm wondering why this difference occurs. Are their starting points defined differently? And if so, why?</p>