Out of bounds nanosecond timestamp
<p>I have a variable ['date_hiring'] in Googlespeedsheet in format like</p>

<pre><code>16.01.2016
</code></pre>

<p>I import it in Python, the variable has an object type. I try to convert to datetime </p>

<pre><code>from datetime import datetime
data['date_hiring'] = pd.to_datetime(data['date_hiring'])
</code></pre>

<p>and i get</p>

<pre><code>OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 16-01-06 00:00:00
</code></pre>

<p>i know from this <a href="https://stackoverflow.com/questions/32888124/pandas-out-of-bounds-nanosecond-timestamp-after-offset-rollforward-plus-adding-a">pandas out of bounds nanosecond timestamp after offset rollforward plus adding a month offset</a> that </p>

<blockquote>
  <p>Since pandas represents timestamps in nanosecond resolution, the
  timespan that can be represented using a 64-bit integer is limited to
  approximately 584 years</p>
</blockquote>

<p>but in original data in the Googlespeedsheet i have no data like '16.01.06' </p>

<p>Just like '16.06.2006'</p>

<p>So the problem is in converting </p>

<p>How to improve it?</p>