title: Converting timezones from pandas Timestamps
body: <p>I have the following in a dataframe:</p>
  
  <pre><code>&gt; df['timestamps'].loc[0]
  Timestamp('2014-09-02 20:24:00')
  </code></pre>
  
  <p>I know the <strong>timezone</strong> (I think it is <strong>GMT</strong>) it uses and would like to convert the entire column to <strong>EST</strong>. How can I do that in Pandas?</p>
  
  <p>For reference, I found these other threads: </p>
  
  <ul>
  <li><a href="https://stackoverflow.com/questions/6706808/changing-a-unix-timestamp-to-a-different-timezone">Changing a unix timestamp to a different timezone</a></li>
  <li><a href="https://stackoverflow.com/questions/14371476/pandas-read-timestamp-from-csv-in-gmt-then-resample">Pandas: Read Timestamp from CSV in GMT then resample</a></li>
  </ul>
  
  <p>but they work with <code>datetime</code> timestamps. E.g.:</p>
  
  <pre><code>&gt; datetime.datetime.fromtimestamp(df['timestamps'].loc[0], tz=None)
  returns:
  
  TypeError                                 Traceback (most recent call last)
  ----&gt; 2 datetime.datetime.fromtimestamp(ts, tz=None)
  
  TypeError: an integer is required (got type Timestamp)
  </code></pre>