title: safest way to read missing dates with pandas read_csv--given blank space turns in today's date bug
body: <p>py2.7
  pandas version .13</p>
  
  <p>What is the safest way to read a csv and convert the column to dates.
  I noticed that in my case, a white space in the column of dates was converted to today's date.  Why?</p>
  
  <p>here's my csv data</p>
  
  <pre><code>fake_file = StringIO.StringIO("""case,opdate,
  7,10/18/2006,
  7,10/18/2008,
  621, ,""")
  </code></pre>
  
  <p>here's my code</p>
  
  <pre><code>df=pd.DataFrame(pd.read_csv('path.csv',parse_dates=['opdate']))
  </code></pre>
  
  <p>tragically fills in the white space with today's date!</p>
  
  <pre><code>df=pd.DataFrame(pd.read_csv('path.csv',parse_dates=['opdate'],na_values=' '))
  </code></pre>
  
  <p>works, but do i really have to know that it is always ' ', instead of say '' or 'null'.</p>
  
  <p>What is the safest way to convert dates and keep the nulls (especially when the null isn't a consistent value)?</p>