title: Vectorize list of lists uisng countvectorizer() & tfidfvectorizer()
body: <p>So I have the following list of lists which is tokenized:</p>
  
  <pre><code>tokenized_list = [['ALL', 'MY', 'CATS', 'IN', 'A', 'ROW'], ['WHEN', 'MY', 
                     'CAT', 'SITS', 'DOWN', ',', 'SHE', 'LOOKS', 'LIKE', 'A', 
                     'FURBY', 'TOY', '!'], ['THE', CAT', 'FROM', 'OUTER', 
                     'SPACE'], ['SUNSHINE', 'LOVES', 'TO', 'SIT', 
                     'LIKE', 'THIS', 'FOR', 'SOME', 'REASON', '.']]
  </code></pre>
  
  <p>When i try to vectorize it using the CountVectorizer() or TfIdfVectorizer()</p>
  
  <pre><code> from sklearn.feature_extraction.text import CountVectorizer
   vectorizer = CountVectorizer()
   print(vectorizer.fit_transform(tokenized_list).todense()) 
   print(vectorizer.vocabulary_)
  </code></pre>
  
  <p>I am getting the following error: </p>
  
  <pre><code>AttributeError: 'list' object has no attribute 'lower'
  </code></pre>
  
  <p>And if I put a <strong>simple list</strong> inside the <strong>vectorizer.fit_transform()</strong> function it works properly.</p>
  
  <p>How do I remove this error?</p>