title: How to find most frequnet words in a corpus in Pandas dataframe (Python)
body: <p>I have Pandas dataframe that looks like following.I have tokenized my text files and used <code>NLTK</code> <code>Countvectorizer</code> to convert into <code>pandas</code> dataframe. In addition, I have already removed stopwords and punctuation from my coupus. I am trying to find most frequent words in my corpus in <code>pandas</code> dataframe. In below dataframe,words such as "aaron" and "abandon" aprreared >10 times, thus those words should be in new dataframe.</p>
  
  <p><em>Note: I am new to python, and I am  not sure how to implement this. Provide explanation with code.</em></p>
  
  <p><strong>Subset of the dataframe</strong></p>
  
  <p>I already already clean my corpus and my <code>dataframe</code> looks like following</p>
  
  <pre><code>{'aaaahhhs': {990: 0, 991: 0, 992: 0, 993: 0, 994: 0, 995: 0, 996: 0, 997: 0, 998: 0, 999: 0, 1000: 1}, 'aahs': {990: 0, 991: 0, 992: 0, 993: 0, 994: 0, 995: 0, 996: 0, 997: 0, 998: 0, 999: 0, 1000: 1}, 'aamir': {990: 0, 991: 0, 992: 0, 993: 0, 994: 0, 995: 0, 996: 0, 997: 0, 998: 0, 999: 0, 1000: 1}, 'aardman': {990: 0, 991: 0, 992: 0, 993: 0, 994: 0, 995: 0, 996: 0, 997: 0, 998: 0, 999: 0, 1000: 2}, 'aaron': {990: 0, 991: 0, 992: 0, 993: 0, 994: 0, 995: 0, 996: 4, 997: 0, 998: 0, 999: 0, 1000: 14}, 'abandon': {990: 0, 991: 0, 992: 0, 993: 0, 994: 0, 995: 0, 996: 0, 997: 0, 998: 0, 999: 0, 1000: 16}}
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/1W7lX.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/1W7lX.png" alt="enter image description here"></a></p>