title: In Pandas Dataframe, how to get the indexes of another column base on a known values in a column?
body: <p>I have a pandas dataframe with several columns. The data type of 2 columns (including <em>'report_end_d'</em> and <em>'report_start_d'</em>) is date. I want to basically get the difference between that two columns and find the maximum length. (That I can do) Also, I want to find the values for that maximum value. I mean dates for report_end_d, report_start_d columns.
  If anyone can give a suggestion that would be a great help!
  Thanks in advance!</p>
  <pre><code># here are my dataframe
      report_sales  report_end_d             report_start_d   
  0      342        2021-09-04 00:00:00      2021-06-13 00:00:0
  1      231        2021-08-29 00:00:00     2021-05-23 00:00:00
  2      124        2021-09-04 00:00:00     2021-07-11 00:00:00
  3      56         2021-09-04 00:00:00     2021-07-25 00:00:00
  4      76         2021-08-28 00:00:00     2021-05-22 00:00:00
      
  
  dss['length'] = (dss['report_end_d'] - dss['report_start_d'])
      report_sales  report_end_d        report_start_d        length
  0        342        2021-09-04 00:00:00   2021-06-13 00:00:00   83 days
  1        231        2021-08-29 00:00:00   2021-05-23 00:00:00   98 days
  2        124        2021-09-04 00:00:00   2021-07-11 00:00:00   55 days
  3         56        2021-09-04 00:00:00   2021-07-25 00:00:00   41 days
  4         76        2021-08-28 00:00:00   2021-05-22 00:00:00   98 days
  
  So I basically need either index 1 values (report_end_d as - 2021-08-29 00:00:00      report_start_d as- 2021-05-23 00:00:00) or index 4 values (report_end_d as -2021-08-28 00:00:00     report_start_d as- 2021-05-22 00:00:00)
  </code></pre>
  <p>Thanks in advance!</p>