title: Pandas sum across columns and divide each cell from that value
body: <p>I have read a csv file and pivoted it to get to following structure:</p>
  
  <pre><code>pivoted = df.pivot('user_id', 'group', 'value')
  lookup = df.drop_duplicates('user_id')[['user_id', 'group']]
  lookup.set_index(['user_id'], inplace=True)
  result = pivoted.join(lookup)
  result = result.fillna(0) 
  </code></pre>
  
  <p>Section of the result:</p>
  
  <pre><code>             0     1     2    3     4    5   6  7    8   9  10  11  12  13  group
  user_id                                                                      
  2        33653  2325   916  720   867  187  31  0    6   3  42  56  92  15    l-1
  4        18895   414  1116  570  1190   55  92  0  122  23  78   6   4   2    l-2 
  16        1383    70    27   17    17    1   0  0    0   0   1   0   0   0    l-2
  50         396    72    34    5    18    0   0  0    0   0   0   0   0   0    l-3
  51        3915  1170   402  832  2791  316  12  5  118  51  32   9  62  27    l-4
  </code></pre>
  
  <p>I want to sum across column 0 to column 13 by each row and divide each cell by the sum of that row. I am still getting used to pandas; if I understand correctly, we should try to avoid for loops when doing things like this? In other words, how can I do this in a  'pandas' way? </p>