title: How to Select Top 1000 words using TF-IDF Vector?
body: <p>I have a Documents with 5000 reviews. I applied tf-idf on that document. Here <strong>sample_data</strong> contains 5000 reviews. I am applying tf-idf vectorizer on the sample_data with <strong>one gram range</strong>. Now I want to get the top 1000 words
  from the sample_data which have <strong>highest tf-idf values</strong>. Could anyone tell me how to get the top words?</p>
  
  <pre><code>from sklearn.feature_extraction.text import TfidfVectorizer
  tf_idf_vect = TfidfVectorizer(ngram_range=(1,1))
  tf_idf_vect.fit(sample_data)
  final_tf_idf = tf_idf_vect.transform(sample_data)
  </code></pre>