title: Pandas get count with ancillary information
body: <p>I have the following data frame:</p>
  <pre><code>df = pd.DataFrame([{'file_name': 'my_movie.mov', 'status': 'final'}, {'file_name': 'his_movie.mov', 'status': 'source'}, {'file_name': 'her_movie.mov', 'status': 'source'}])
  
         file_name  status
  0   my_movie.mov   final
  1  his_movie.mov  source
  2  her_movie.mov  source
  </code></pre>
  <p>I would like to do something like:</p>
  <pre><code>df.groupby('status')[['status', 'file_name', 'count']]
  </code></pre>
  <p><code>file_name</code> can be any file_name value, and count would be the <code>count</code> of records. The answer would be something like:</p>
  <pre><code>status         file_name              count
  final          my_movie.mov           1
  source         his_movie.mov          2
  </code></pre>
  <p>In SQL (using mysql dialect) I would do:</p>
  <pre><code>SELECT status, file_name, COUNT(*) FROM df GROUP BY status
  </code></pre>
  <p>How would I do this in pandas?</p>
  <hr />
  <p>The closest I have gotten is this, but this isn't adding in the file_name, which I want:</p>
  <pre><code>&gt;&gt;&gt; df[['new__status', 'file_name']].groupby('new__status').count().sort_values('file_name', ascending=False)
  </code></pre>