title: Pandas dataframe groupby and combine multiple row values
body: <p>I apologize if the title isn't clear, but I had difficulty phrasing the question. It's probably best if I just show what I would like to do.</p>
  
  <p>Some context: I parsed a document for names and stored each name with the page number where it appears. I need to transform the DataFrame so that there is a single row for each name the page number column combines all the pages where the name appears. I figured that this would require GroupBy, but I'm not entirely sure.</p>
  
  <p>My data currently:</p>
  
  <pre><code>data = np.array([['John', 'Smith', 1], ['John', 'Smith', 7], ['Eric', 'Adams', 9], ['Jane', 'Doe', 14], ['Jane', 'Doe', 16], ['John', 'Smith', 19]])
  
  pd.DataFrame(data, columns=['FIRST_NM', 'LAST_NM', 'PAGE_NUM'])
  
    FIRST_NM LAST_NM PAGE_NUM
  0     John   Smith        1
  1     John   Smith        7
  2     Eric   Adams        9
  3     Jane     Doe       14
  4     Jane     Doe       16
  5     John   Smith       19
  </code></pre>
  
  <p>Desired dataframe:</p>
  
  <pre><code>  FIRST_NM LAST_NM PAGE_NUM
  0     John   Smith   1,7,19
  1     Eric   Adams        9
  2     Jane     Doe    14,16
  </code></pre>