filter dataframe values based on another column using pandas

Question

Have df with values.


name     last_date                     submission_date

mike  2020-04-10 02:22:22.222   2020-04-01 02:22:22.222
mike  2020-04-10 02:22:22.222   2020-04-08 02:22:22.222
mike  2020-04-10 02:22:22.222   2020-04-16 02:22:22.222

ross  2020-04-16 02:22:22.222   2020-04-18 02:22:22.222
ross  2020-04-16 02:22:22.222   2020-04-19 02:22:22.222
ross  2020-04-16 02:22:22.222   2020-04-20 02:22:22.222
ross  2020-04-16 02:22:22.222   2020-04-15 02:22:22.222

carter 2020-04-22 02:22:22.222   2020-04-28 02:22:22.222
carter 2020-04-22 02:22:22.222   2020-04-15 02:22:22.222
carter 2020-04-22 02:22:22.222   2020-04-19 02:22:22.222
carter 2020-04-22 02:22:22.222   2020-04-21 02:22:22.222

filter values based on last_date. exclude values of submission_date if it is greater than last_date

expected output:

name     last_date                     submission_date

mike  2020-04-10 02:22:22.222   2020-04-01 02:22:22.222
mike  2020-04-10 02:22:22.222   2020-04-08 02:22:22.222

ross  2020-04-16 02:22:22.222   2020-04-15 02:22:22.222

carter 2020-04-22 02:22:22.222   2020-04-15 02:22:22.222
carter 2020-04-22 02:22:22.222   2020-04-19 02:22:22.222
carter 2020-04-22 02:22:22.222   2020-04-21 02:22:22.222

you can just query: df.query("last_date>=submission_date") ? — anky
– anky, Commented Apr 18, 2020 at 13:29

anky · Accepted Answer · 2020-04-18 13:37:42Z

1

You can query the dataframe where submission_date is less than or equal to last_date , this returns the rows where the condition is met an filters out the rest:

df.query("last_date>=submission_date")

    name                 last_date         submission_date
0   mike   2020-04-10 02:22:22.222 2020-04-01 02:22:22.222
1   mike   2020-04-10 02:22:22.222 2020-04-08 02:22:22.222
2   ross   2020-04-16 02:22:22.222 2020-04-15 02:22:22.222
3  carter  2020-04-22 02:22:22.222 2020-04-15 02:22:22.222
4  carter  2020-04-22 02:22:22.222 2020-04-19 02:22:22.222
5  carter  2020-04-22 02:22:22.222 2020-04-21 02:22:22.222

answered Apr 18, 2020 at 13:37

anky

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