title: pandas df.corr() returns NaN despite data fed having populated data
body: <p>My data looks like the following:</p>
  
  <p><code>print data</code></p>
  
  <pre><code>                   A                B 
  2014-04-04        163.24         191.77
  2014-06-11        165.43         182.25
  2014-12-22        194.44         161.44
  2014-03-25        163.25         195.04
  2014-11-03        190.83         164.36
  2014-06-16        165.85         182.35
  2014-11-24        190.07         162.15
  2014-05-21        159.35         186.39
  2015-01-21        177.15         152.09
  2014-08-28        177.65         192.00
  2014-02-19        163.26         182.95
  2014-05-12        159.55         192.57
  2014-07-09        164.67         188.42
  2015-02-26        192.20         160.87
  2014-10-14        178.70         183.80
  2014-07-16        170.47         192.36
  2014-01-21        173.20         188.43
  2014-06-03        161.80         184.37
  2014-03-17        166.84         185.81
  2014-08-11        172.46         187.47
  2015-01-07        187.28         155.05
  2014-05-29        160.74         183.76
  2015-02-11        187.65         158.20
  2014-02-27        165.38         185.27
  2015-01-05        188.34         159.51
  2014-07-01        166.81         186.35
  2015-02-18        188.67         162.19
  2014-04-03        166.09         192.69
  2014-10-06        187.48         189.04
  2014-12-29        196.19         160.51
  </code></pre>
  
  <p>When I try to call <code>data.corr()</code> I receive back all <code>NaN</code>. I tested this in excel, and the correlation is indeed able to be calculated.</p>
  
  <p>Any idea why this might be the case?</p>
  
  <p>I am happy to post more but i am unsure what would help.</p>
  
  <pre><code>print data.info()
  
  &lt;class 'pandas.core.frame.DataFrame'&gt;
  Index: 298 entries, 2014-04-04 to 2014-01-29
  Data columns (total 2 columns):
  A     298 non-null float64
  B    298 non-null float64
  dtypes: float64(2)None
  
  
  
  print data.describe()
                A                B
      count    298.000000     298.000000
      mean     175.152886     178.596242
      std       11.490668      13.709316
      min      152.720000     151.410000
      25%      165.502500     162.655000
      50%      175.480000     184.330000
      75%      185.085000     189.692500
      max      196.890000     197.770000
  
  
  print pd.version
  0.14.1
  </code></pre>