title: Extract text features from dataframe
body: <p>I have dataframe with two text fields and other features like this format : </p>
  
  <pre><code> message            feature_1      feature_2       score        text
   'This is the text'     4             7            10          extra text
   'This is more text'    3             2            8           and this is another text
  </code></pre>
  
  <p>Now my goal is to predict the score, when trying to transform this dataframe into a feature matrix to feed it into my machine learning model, here is what I have did :</p>
  
  <pre><code>    # Create vectorizer for function to use
      vectorizer = TfidfVectorizer()
      # combine the numerical features with the TFIDF generated matrix
      X = sp.sparse.hstack( (vectorizer.fit_transform(df.message),
                        df[['feature_1', 'feature_2']].values, vectorizer.fit_transform(df.text)),
                        format='csr')
  </code></pre>
  
  <p>Now when printing the shape of my X matrix I got 2x13, but when I check the X_columsn like this : </p>
  
  <pre><code>X_columns = vectorizer.get_feature_names() + df[['feature_1', 'feature_2']].columns.tolist()
  </code></pre>
  
  <p>I don't get all the words in the corpus, it bring me just the words existing in <code>df.text</code> and other features attribute without words in <code>df.message</code> .</p>
  
  <pre><code>['and', 'another', 'extra', 'is', 'text', 'this', 'feature_1', 'feature_2']
  </code></pre>
  
  <p>How can I make X contain all my dataframe features !!</p>