title: Compute correlation between features and target variable
body: <p>What is the best solution to compute correlation between my features and target variable ?? My dataframe have 1000 rows and 40 000 columns... </p>
  
  <p>Exemple : </p>
  
  <pre><code>df = pd.DataFrame([[1, 2, 4 ,6], [1, 3, 4, 7], [4, 6, 8, 12], [5, 3, 2 ,10]], columns=['Feature1', 'Feature2','Feature3','Target'])
  </code></pre>
  
  <p>This code works fine but this is too long on my dataframe ... I need only the last column of correlation matrix : correlation with target (not pairwise feature corelation).</p>
  
  <pre><code>corr_matrix=df.corr()
  corr_matrix["Target"].sort_values(ascending=False)
  </code></pre>
  
  <p>The <strong>np.corcoeff()</strong> function works with array but can we exclude the pairwise feature correlation ?</p>