title: Run a basic correlation between two columns of a dataframe
body: <p>I am trying to be able to produce a correlation matrix from a pandas dataframe using data from specified columns</p>
  
  <p>Here is my csv data:</p>
  
  <pre><code>col0,col1,col2,col3,col4
  122468.9071,1417464.203,3546600,151804924,10839476
  14691.1139,170036.0407,103847,19208604,2365065
  </code></pre>
  
  <p>Here are the two dataframes I created:</p>
  
  <pre><code>df1 = pd.read_csv('c:/temp/test_1.csv', usecols=[0])
  df2 = pd.read_csv('c:/temp/test_1.csv', usecols=[1])
  </code></pre>
  
  <p>I tried the corr and corrwith functions and get the following errors:</p>
  
  <pre><code>Corr Function:
  
  print df1.corr(df2)
  
  Result: 
  
  Error: Could not compare ['pearson'] with block values
  
  Corrwith:
  
  print df1.corrwith(df2)
  
  Result:    
  
  col0   NaN
  col1   NaN
  dtype: float64
  </code></pre>
  
  <p>As you can see, there are no null values in the data set and the float64 should be able to handle decimals.</p>
  
  <p>Any assistance on a solve would be greatly appreciated.</p>
  
  <p>Tiberius</p>