title: Pandas corr() vs corrwith()
body: <p>What is the reason of Pandas to provide two different correlation functions?</p>
  
  <blockquote>
    <p><strong>DataFrame.corrwith(other, axis=0, drop=False)</strong>: 
    Correlation between rows or columns of two DataFrame objectsCompute pairwise</p>
  </blockquote>
  
  <p>vs.</p>
  
  <blockquote>
    <p><strong>DataFrame.corr(method='pearson', min_periods=1)</strong>: Compute pairwise
    correlation of columns, excluding NA/null values</p>
  </blockquote>
  
  <p>(from pandas 0.20.3 documentation)</p>