title: Most Frequent words in each row
body: <p>I am trying to find the most frequent words, in each row of a tokenized Dataframe as follows:</p>
  
  <pre><code>print(df.tokenized_sents)
  
  ['apple', 'inc.', 'aapl', 'reported', 'fourth', 'consecutive', 'quarter', 'record', 'revenue', 'profit', 'combination', 'higher', 'iphone', 'prices', 'strong', 'app-store', 'sales', 'propelled', 'technology', 'giant', 'best', 'year', 'ever', 'revenue', 'three', 'months', 'ended', 'sept.']
  
  ['brussels', 'apple', 'inc.', 'aapl', '-.', 'chief', 'executive', 'tim', 'cook', 'issued', 'tech', 'giants', 'strongest', 'call', 'yet', 'u.s.-wide', 'data-protection', 'regulation', 'saying', 'individuals', 'personal', 'information', 'been', 'weaponized', 'mr.', 'cooks', 'call', 'came', 'sharply', 'worded', 'speech', 'before', 'p…']
  
  ...
  
  wrds = []
  for i in range(0, len(df) ):
  
      wrds.append( Counter(df["tokenized_sents"][i]).most_common(5) )
  </code></pre>
  
  <p>But it reports a list as:</p>
  
  <pre><code>print(wrds)
  
  [('revenue', 2), ('apple', 1), ('inc.', 1), ('aapl', 1), ('reported', 1)]
  ...
  </code></pre>
  
  <p>I would like to create the following dataframe instead;</p>
  
  <pre><code>print(final_df)
  
  KeyWords                                                                         
  revenue, apple, inc., aapl, reported
  ...
  </code></pre>
  
  <p>N.B. The rows of the final dataframe are not lists, but single text values, e.g. revenue, apple, inc., aapl, reported, <strong>NOT</strong>, [revenue, apple, inc., aapl, reported]</p>