I have a potentially big dataframe containing datetimes sourced from a date range query as such:
0 2022-11-20 00:02:22.630968 00:00
1 2022-11-23 00:03:02.134938 00:00
2 2022-11-23 00:03:50.589251 00:00
3 2022-11-26 00:05:17.568843 00:00
4 2022-11-26 00:05:22.653905 00:00
5 2022-11-26 00:05:22.653905 00:00
6 2022-11-26 00:05:22.653905 00:00
I need to reshape it into a list of date with number of date occurrences in the second row, no date occurrence must be zero filled as such:
2022-11-20 1
2022-11-21 0
2022-11-22 0
2022-11-23 2
2022-11-24 0
2022-11-25 0
2022-11-26 4
What is the most efficient way to achieve that with Pandas ?
If that's useful.. the end goal is to feed that data to
Intermediates :
2022-11-20 1
2022-11-21 0
2022-11-22 0
2022-11-23 2
2022-11-24 0
2022-11-25 0
2022-11-26 4
Freq: D, Name: Datetime, dtype: int64 <class 'pandas.core.series.Series'>