title: Combine multiple rows with the same timestamp and put values into new columns
body: <p>Assuming I'm having an input df which looks as follows:</p>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>Timestamp</th>
  <th>name</th>
  <th>value</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>14:00:00</td>
  <td>A</td>
  <td>25</td>
  </tr>
  <tr>
  <td>14:00:00</td>
  <td>B</td>
  <td>24</td>
  </tr>
  <tr>
  <td>15:00:00</td>
  <td>A</td>
  <td>20</td>
  </tr>
  <tr>
  <td>15:00:00</td>
  <td>C</td>
  <td>21</td>
  </tr>
  <tr>
  <td>16:00:00</td>
  <td>A</td>
  <td>20</td>
  </tr>
  <tr>
  <td>16:00:00</td>
  <td>B</td>
  <td>22</td>
  </tr>
  <tr>
  <td>16:00:00</td>
  <td>C</td>
  <td>23</td>
  </tr>
  <tr>
  <td>16:00:00</td>
  <td>D</td>
  <td>24</td>
  </tr>
  </tbody>
  </table>
  </div>
  <p>What I'd like to do now is to merge the rows dependend on the Timestamps but when merging putting the names with the corresponding value into new columns to achieve the following:</p>
  <div class="s-table-container">
  <table class="s-table">
  <thead>
  <tr>
  <th>Timestamp</th>
  <th>A</th>
  <th>B</th>
  <th>C</th>
  <th>D</th>
  </tr>
  </thead>
  <tbody>
  <tr>
  <td>14:00:00</td>
  <td>25</td>
  <td>24</td>
  <td>nan</td>
  <td>nan</td>
  </tr>
  <tr>
  <td>15:00:00</td>
  <td>20</td>
  <td>nan</td>
  <td>21</td>
  <td>nan</td>
  </tr>
  <tr>
  <td>16:00:00</td>
  <td>20</td>
  <td>22</td>
  <td>23</td>
  <td>24</td>
  </tr>
  </tbody>
  </table>
  </div>
  <p>Are there some build in functions for Pyspark that I could use to achieve this? It would be great if the approach is as generic as possible.</p>