title: How to create new columns in pandas dataframe using column values?
body: <p>I'm working in Python with a pandas DataFrame similar to:</p>
  <pre><code>REQUESET_ID | DESCR | TEST | TEST_DESC | RESULT |
           1  |     1 |   T1 | TEST_1    |  2.0   |           
           1  |     2 |   T2 | TEST_2    |  92.0  |                       
           2  |     1 |   T1 | TEST_1    |  8.0   |
           3  |     3 |   T3 | TEST_3    |  12.0  |
           3  |     4 |   T4 | TEST_4    |  45.0  |
  </code></pre>
  <p>What I want is a final dataframe like this:</p>
  <pre><code> REQUESET_ID | DESCR_1 | TEST_1 | TEST_DESC_1 | RESULT_1 | DESCR_2 | TEST_2 | TEST_DESC_2 | RESULT_2 |
            1  |       1 |     T1 |   TEST_1    |  2.0     |       2 |   T2   |   TEST_2    |  92.0    | 
            2  |       1 |     T1 |   TEST_1    |  8.0     |   NaN   |  NaN   |     NaN     | Nan      |  
            3  |       3 |     T3 |    TEST_3   |  12.0    |       4 |   T4   |   TEST_4    |  45.0    |
  </code></pre>
  <p>How I should implement that as a method working with DataFrames. I understand that if I try to do it with a merge instead of having 4x2 columns added beacuse the value_counts method of the REQUEST_ID will return 2, will add the 4 columns for each entry in the request column.</p>