pandas to_datetime parsing wrong year
<p>I'm coming across something that is almost certainly a stupid mistake on my part, but I can't seem to figure out what's going on. </p>

<p>Essentially, I have a series of dates as strings in the format <code>"%d-%b-%y"</code>, such as <code>26-Sep-05</code>. When I go to convert them to datetime, the year is sometimes correct, but sometimes it is not. </p>

<p>E.g.: </p>

<pre><code>dates = ['26-Sep-05', '26-Sep-05', '15-Jun-70', '5-Dec-94', '9-Jan-61', '8-Feb-55']

pd.to_datetime(dates, format="%d-%b-%y")
DatetimeIndex(['2005-09-26', '2005-09-26', '1970-06-15', '1994-12-05',
               '2061-01-09', '2055-02-08'],
              dtype='datetime64[ns]', freq=None)
</code></pre>

<p>The last two entries, which get returned as 2061 and 2055 for the years, are wrong. But this works fine for the <code>15-Jun-70</code> entry. What's going on here?</p>