title: Pandas: Remove rows whose date does not follow specified format
body: <p>In my dataset, I have a date column in which the data is of mixed format. </p>
  
  <ul>
  <li>Some rows only have <code>YYYY</code> (e.g. <code>2009</code>)</li>
  <li>Others have <code>MMM-YY</code> (e.g. <code>Jan-08</code>)</li>
  <li>Yet others have a full date <code>MM/DD/YYYY</code> (e.g. <code>01/15/2006</code>)</li>
  </ul>
  
  <p>How might I remove the entries that do not follow the format <code>MM/DD/YYYY</code>? I'm not quite sure where to start here.</p>
  
  <p>Below, I have provided the <code>.head()</code> of the data as a <code>dict</code>.</p>
  
  <pre><code>{'Collection Date': {0: '2001',
    1: '2002',
    2: '2006',
    3: '2/19/2006',
    4: '2/28/2006'},
   'Complete Genome': {0: 'No', 1: 'No', 2: 'No', 3: 'No', 4: 'No'},
   'Country': {0: 'Egypt', 1: 'Egypt', 2: 'Egypt', 3: 'Egypt', 4: 'Egypt'},
   'Flu Season': {0: '-N/A-', 1: '-N/A-', 2: '-N/A-', 3: '-N/A-', 4: '-N/A-'},
   'Host Species': {0: 'IRD:Human',
    1: 'IRD:Human',
    2: 'IRD:Bird/Avian',
    3: 'IRD:Chicken/Avian',
    4: 'IRD:Avian'},
   'Protein Name': {0: 'NA', 1: 'NA', 2: 'NA', 3: 'NA', 4: 'HA'},
   'Segment': {0: 6, 1: 6, 2: 6, 3: 6, 4: 4},
   'Segment Length': {0: 1428, 1: 1449, 2: 1441, 3: 1363, 4: 1707},
   'Sequence Accession': {0: 'AJ457944',
    1: 'AJ457943',
    2: 'GU050304',
    3: 'GQ184251',
    4: 'KF178948'},
   'State/Province': {0: '-N/A-',
    1: '-N/A-',
    2: '-N/A-',
    3: '-N/A-',
    4: '-N/A-'},
   'Strain Name': {0: '(A/Egypt/84/2001(H1N2))',
    1: '(A/Egypt/96/2002(H1N2))',
    2: 'A/avian/Egypt/920431/2006(H9N2)',
    3: 'A/chicken/Egypt/06207-NLQP/2006(H5N1)',
    4: 'A/chicken/Egypt/0626/2006'},
   'Subtype': {0: 'H1N2', 1: 'H1N2', 2: 'H9N2', 3: 'H5N1', 4: 'H5N1'}}
  </code></pre>