title: numpy corrcoef - compute correlation matrix while ignoring missing data
body: <p>I am trying to compute a correlation matrix of several values.  These values include some 'nan' values.  I'm using numpy.corrcoef.  For element(i,j) of the output correlation matrix I'd like to have the correlation calculated using all values that exist for both variable i and variable j.</p>
  
  <p>This is what I have now:</p>
  
  <pre><code>In[20]: df_counties = pd.read_sql("SELECT Median_Age, Rpercent_2008, overall_LS, population_density FROM countyVotingSM2", db_eng)
  In[21]: np.corrcoef(df_counties, rowvar = False)
  Out[21]: 
  array([[ 1.        ,         nan,         nan, -0.10998411],
         [        nan,         nan,         nan,         nan],
         [        nan,         nan,         nan,         nan],
         [-0.10998411,         nan,         nan,  1.        ]])
  </code></pre>
  
  <p>Too many nan's :(</p>