set locale to data frame with ambiguous local time leads to 
I read CSV-files with ambiguous local time -- ambiguous due to daylight saving time. 

When I apply `tz_localize()` I run in the following error:

    AmbiguousTimeError: There are %i dst switches when there should only be 1.

Here is my code to reproduce the error. Note that from 2am to 3am every datetime is a duplicate due to daylight saving time.

    index = pd.DatetimeIndex(['2018-10-28 01:00:00', '2018-10-28 01:15:00',
                              '2018-10-28 01:30:00', '2018-10-28 01:45:00',
                              '2018-10-28 02:00:00', '2018-10-28 02:00:00',
                              '2018-10-28 02:15:00', '2018-10-28 02:15:00',
                              '2018-10-28 02:30:00', '2018-10-28 02:30:00',
                              '2018-10-28 02:45:00', '2018-10-28 02:45:00',
                              '2018-10-28 03:00:00', '2018-10-28 03:15:00',
                              '2018-10-28 03:30:00', '2018-10-28 03:45:00',
                              '2018-10-28 04:00:00'], freq='infer')
    
    data = list(range(len(index)))
    
    df = pd.DataFrame(data=data,index=index)
    df.index = df.index.tz_localize('Europe/Berlin', ambiguous='infer')

I don't quite understand why the error occurs even with parameter `ambiguous='infer'`. <br>
Does my dataframe have to be "sorted" in any way? I think data frames are ordered by default since there is  `DataFrame.iloc` <br>
Or is there a specific problem with `pd.read_csv()`? <br>
I wish to apply `ambiguous='infer'` with respect to the order of the CSV file. Precisly I mean: the order of the ambiguous time format helps to differ between summer and winter time.

I would be glad about help for a solution and about a broader explanation. I couldn't find out more about how order can play a role in data frames--does it sometimes?

If order is not the problem here, than I believe this is an issue.