title: Changing values in columns based on their previous marker
body: <p>I have the following dataframe:</p>
  <pre><code>df = {'id': [1,2,3,4],
      '1': ['Green', 'Green', 'Green', 'Green'],
    '2': ['34','67', 'Blue', '77'],
    '3': ['Blue', '45', '99', 'Blue'],
    '4': ['12', None, '101', '56'],
       '5': [None, None, None, '23']}
  
  df = pd.DataFrame(df)
  
  
      id  1       2     3     4       5
  0   1   Green   34    Blue  12      None
  1   2   Green   67    45    None    None
  2   3   Green   Blue  99    101     None
  3   4   Green   77    Blue  56      23
  </code></pre>
  <p>I would like to add the prefix G_ to all values which are in columns after GREEN but not after BLUE. The values after BLUE should result in a B_ prefix.</p>
  <p>Here is the output needed:</p>
  <pre><code>    id  1       2       3       4       5
  0   1   Green   G_34    Blue    B_12    None
  1   2   Green   G_67    G_45    None    None
  2   3   Green   Blue    B_99    B_101   None
  3   4   Green   G_77    Blue    B_56    B_23
  </code></pre>