In Pandas Dataframe, how to get the indexes of another column base on a known values in a column?-CodePudding

I have a pandas dataframe with several columns. The data type of 2 columns (including 'report_end_d' and 'report_start_d') 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!

# 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)

Thanks in advance!

CodePudding user response：

largest = dss['length'].max()
dss[['report_end_d','report_start_d']] [dss['length'] == largest]