title: Drop duplicates of one column based on value in another column, Python, Pandas
body: <p>I have a dataframe like this:</p>
  
  <pre><code>Date                PlumeO      Distance
  2014-08-13 13:48:00  754.447905 5.844577 
  2014-08-13 13:48:00  754.447905 6.888653
  2014-08-13 13:48:00  754.447905 6.938860
  2014-08-13 13:48:00  754.447905 6.977284
  2014-08-13 13:48:00  754.447905 6.946430 
  2014-08-13 13:48:00  754.447905 6.345506
  2014-08-13 13:48:00  754.447905 6.133567
  2014-08-13 13:48:00  754.447905 5.846046 
  2014-08-13 16:59:00  754.447905 6.345506 
  2014-08-13 16:59:00  754.447905 6.694847 
  2014-08-13 16:59:00  754.447905 5.846046 
  2014-08-13 16:59:00  754.447905 6.977284 
  2014-08-13 16:59:00  754.447905 6.938860 
  2014-08-13 16:59:00  754.447905 5.844577 
  2014-08-13 16:59:00  754.447905 6.888653 
  2014-08-13 16:59:00  754.447905 6.133567 
  2014-08-13 16:59:00  754.447905 6.946430
  </code></pre>
  
  <p>I'm trying to keep the date with the smallest distance, so drop the duplicates dates and keep the with the smallest distance. </p>
  
  <p>Is there a way to achieve this in pandas' <code>df.drop_duplicates</code> or am I stuck using if statements to find the smallest distance?</p>