title: Run nltk sent_tokenize through Pandas dataframe
body: <p>I have a dataframe that consists of two columns: ID and TEXT. Pretend data is below:</p>
  
  <pre><code>ID      TEXT
  265     The farmer plants grain. The fisher catches tuna.
  456     The sky is blue.
  434     The sun is bright.
  921     I own a phone. I own a book.
  </code></pre>
  
  <p>I know all nltk functions do not work on dataframes. How could sent_tokenize be applied to the above dataframe?</p>
  
  <p>When I try:</p>
  
  <pre><code>df.TEXT.apply(nltk.sent_tokenize)  
  </code></pre>
  
  <p>The output is unchanged from  the original dataframe. My desired output is:</p>
  
  <pre><code>TEXT
  The farmer plants grain.
  The fisher catches tuna.
  The sky is blue.
  The sun is bright.
  I own a phone.
  I own a book.
  </code></pre>
  
  <p>In addition, I would like to tie back this new (desired) dataframe to the original <code>ID</code> numbers like this (following further text cleansing):</p>
  
  <pre><code>ID    TEXT
  265     'farmer', 'plants', 'grain'
  265     'fisher', 'catches', 'tuna'
  456     'sky', 'blue'
  434     'sun', 'bright'
  921     'I', 'own', 'phone'
  921     'I', 'own', 'book'
  </code></pre>
  
  <p>This question is related to another of my questions <a href="https://stackoverflow.com/questions/43917011/convert-dataframe-column-to-list-of-lists-and-convert-back-to-dataframe-while-m">here</a>. Please let me know if I can provide anything to help clarify my question! </p>