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- +-------+---------------------+--------+---------------------------------------------------+------+-------+----------------+-----+---------+------+
- | Row | Date | Sender | Message | Year | Month | day_month_year | Day | WeekDay | Hour |
- +-------+---------------------+--------+---------------------------------------------------+------+-------+----------------+-----+---------+------+
- | 33624 | 2019-05-21 14:50:00 | Bob | ['15/09/16 12:22 pm - User1 | 2019 | May | 2019-05-21 | 21 | Tue | 14 |
- | 33625 | 2019-05-21 14:50:00 | Bob | ['15/09/16 12:22 pm - User1 | 2019 | May | 2019-05-21 | 21 | Tue | 14 |
- | 33626 | 2019-05-21 14:50:00 | Bob | this will split into | 2019 | May | 2019-05-21 | 21 | Tue | 14 |
- | 33627 | 2019-05-21 14:51:00 | Bob | DATE | TIME | USERNAME | MESSAGE | 2019 | May | 2019-05-21 | 21 | Tue | 14 |
- | 33628 | 2019-05-21 14:51:00 | Bob | those next "Hi" and "Some More Text" gets fill... | 2019 | May | 2019-05-21 | 21 | Tue | 14 |
- | 33629 | 2019-05-21 14:51:00 | Pat | Got it. | 2019 | May | 2019-05-21 | 21 | Tue | 14 |
- +-------+---------------------+--------+---------------------------------------------------+------+-------+----------------+-----+---------+------+
- data2 = data.groupby(['day_month_year','Sender']).count()["Message"].unstack()
- +----------------+-------+-------+-------+-------+
- | Sender | Bob | Pat | User1 | User2 |
- +----------------+-------+-------+-------+-------+
- | day_month_year | | | | |
- | 2016-09-15 | NaN | NaN | 1.0 | 2.0 |
- | 2018-11-09 | 68.0 | 86.0 | NaN | NaN |
- | 2018-11-10 | 40.0 | 56.0 | NaN | NaN |
- | 2018-11-11 | 34.0 | 25.0 | NaN | NaN |
- | 2018-11-12 | 214.0 | 229.0 | NaN | NaN |
- +----------------+-------+-------+-------+-------+
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