title: How vectorizer fit_transform work in sklearn?
body: <p>I'm trying to understand the following code </p>
  
  <pre><code>from sklearn.feature_extraction.text import CountVectorizer 
  
  vectorizer = CountVectorizer() 
  
  corpus = ['This is the first document.','This is the second second document.','And the third one.','Is this the first document?'] 
  
  X = vectorizer.fit_transform(corpus)
  </code></pre>
  
  <p>When I try to print X to see what will be return, I got this result :</p>
  
  <pre><code>(0, 1)  1
  
  (0, 2)  1
  
  (0, 6)  1
  
  (0, 3)  1
  
  (0, 8)  1
  
  (1, 5)  2
  
  (1, 1)  1
  
  (1, 6)  1
  
  (1, 3)  1
  
  (1, 8)  1
  
  (2, 4)  1
  
  (2, 7)  1
  
  (2, 0)  1
  
  (2, 6)  1
  
  (3, 1)  1
  
  (3, 2)  1
  
  (3, 6)  1
  
  (3, 3)  1
  
  (3, 8)  1
  </code></pre>
  
  <p>However, I don't understand the meaning of this result ?</p>