title: Python Scikit-learn CountVectorizer throwing ValueError: empty vocabulary
body: <p>I'm trying to extract features from a text document. Here is my code:</p>
  
  <p><code>import sklearn</code><br>
  <code>from sklearn.datasets import load_files</code><br>
  <code>from sklearn.feature_extraction.text import CountVectorizer</code><br>
  <code>files = sklearn.datasets.load_files('/home/niyas/Documents/project/container', shuffle = False)</code><br>
  <code>vectorizer = CountVectorizer(min_df=1)</code><br>
  <code>X = vectorizer.fit_transform(files.data[1])</code><br>
  <code>Y=vectorizer.get_feature_names()</code></p>
  
  <p>I'm getting an error "ValueError: empty vocabulary; perhaps the documents only contain stop words". The code works fine when I pass a string with the exact same content of the text doc. </p>
  
  <p>Help me. Thanks in advance.</p>