title: Factor Loadings using sklearn
body: <p>I want the correlations between individual variables and principal components in python.
  I am using PCA in sklearn. I don't understand how can I achieve the loading matrix after I have decomposed my data? My code is here.</p>
  
  <pre><code>iris = load_iris()
  data, y = iris.data, iris.target
  pca = PCA(n_components=2)
  transformed_data = pca.fit(data).transform(data)
  eigenValues = pca.explained_variance_ratio_
  </code></pre>
  
  <p><a href="http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html">http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html</a> doesn't mention how this can be achieved.</p>