title: Pandas tz_localize: Infer dst when localizing timezone in data with duplicates
body: <p>I want to localize a datetime series with pandas tz_localize. The series crosses a DST date (e.g. 25Oct2015 for Germany CET). I usually do this with</p>
  
  <pre><code>import pandas as pd
  T = ['25/10/2015 02:59:00','25/10/2015 02:00:00','25/10/2015 02:01:00']
  pd.to_datetime(T).tz_localize('CET',ambiguous='infer')
  </code></pre>
  
  <p>But when the time series has duplicates - even if they are sorted in an unambiguous way - I get an error:</p>
  
  <pre><code>T = ['25/10/2015 02:59:00','25/10/2015 02:59:00','25/10/2015 02:00:00','25/10/2015 02:01:00']
  pd.to_datetime(T).tz_localize('CET',ambiguous='infer')
  
  AmbiguousTimeError: There are 2 dst switches when there should only be 1.
  </code></pre>
  
  <p>This seems like a unnecessary limitation since the infer should be pretty straight forward. Is there a workaround or solution, or do I need to code my own infer-method?</p>