title: plot a document tfidf 2D graph
body: <p>I would like to plot a 2d graph with the x-axis as term and y-axis as TFIDF score (or document id) for my list of sentences. I used scikit learn's fit_transform() to get the scipy matrix but i do not know how to use that matrix to plot the graph. I am trying to get a plot to see how well my sentences can be classified using kmeans.</p>
  
  <p>Here is the output of <code>fit_transform(sentence_list)</code>:</p>
  
  <p><strong>(document id, term number) tfidf score</strong></p>
  
  <pre><code>(0, 1023)   0.209291711271
  (0, 924)    0.174405532933
  (0, 914)    0.174405532933
  (0, 821)    0.15579574484
  (0, 770)    0.174405532933
  (0, 763)    0.159719994016
  (0, 689)    0.135518787598
  </code></pre>
  
  <p>Here is my code:</p>
  
  <pre><code>sentence_list=["Hi how are you", "Good morning" ...]
  vectorizer=TfidfVectorizer(min_df=1, stop_words='english', decode_error='ignore')
  vectorized=vectorizer.fit_transform(sentence_list)
  num_samples, num_features=vectorized.shape
  print "num_samples:  %d, num_features: %d" %(num_samples,num_features)
  num_clusters=10
  km=KMeans(n_clusters=num_clusters, init='k-means++',n_init=10, verbose=1)
  km.fit(vectorized)
  PRINT km.labels_   # Returns a list of clusters ranging 0 to 10 
  </code></pre>
  
  <p>Thanks,</p>