title: converting scipy.sparse.csr.csr_matrix to a list of lists
body: <p>I am learning multi label classification and trying to implement the tfidf tutorial from scikit learning.
  I am dealing with a text corpus to calculate its tf-idf score.
  I am using the module sklearn.feature_extraction.text for the purpose.Using CountVectorizer and TfidfTransformer I have now my corpus vectorised and tfidf for each vocabulary.
  The problem is that I am having a sparse matrix now, like:</p>
  
  <pre><code>(0, 47) 0.104275891915
  (0, 383)    0.084129133023
  .
  .
  .
  .
  (4, 308)    0.0285015996586
  (4, 199)    0.0285015996586
  </code></pre>
  
  <p>I want to convert this sparse.csr.csr_matrix into a list of lists so that I can get rid of the document id from the above csr_matrix and get the tfidf and vocabularyId pair like</p>
  
  <pre><code>47:0.104275891915 383:0.084129133023
  .
  .
  .
  .
  308:0.0285015996586 
  199:0.0285015996586
  </code></pre>
  
  <p>Is there any  way to convert into a list of lists or any other way with which i can change the format to get tfidf-vocabularyId pair ?</p>