I have time series data with other fields. Now I want create more columns like
valueonsamehour1daybefore,valueonsamehour2daybefore,
valueonsamehour3daybefore,valueonsamehour1weekbefore,
valueonsamehour1monthbefore
If values are not present at the hour then value should be set as zero dataframe can be loaded from here
url = 'https://drive.google.com/file/d/1BXvJqKGLwG4hqWJvh9gPAHqCbCcCKkUT/view?usp=sharing'
path = 'https://drive.google.com/uc? export=download&id='+url.split('/')[-2]
df = pd.read_csv(path,index_col=0,delimiter=",")
The DataFrame looks like the following:
| time | StartCity | District | Id | stype | EndCity | Count
2021-09-15 09:00:00 1 104 2713 21 9 2
2021-05-16 11:00:00 1 107 1044 11 6 1
2021-05-16 12:00:00 1 107 1044 11 6 0
2021-05-16 13:00:00 1 107 1044 11 6 0
2021-05-16 14:00:00 1 107 1044 11 6 0
2021-05-16 15:00:00 1 107 1044 11 6 0
2021-05-16 16:00:00 1 107 1044 11 6 0
2021-05-16 17:00:00 1 107 1044 11 6 0
2021-05-16 18:00:00 1 107 1044 11 6 0
2021-05-16 19:00:00 1 107 1044 11 6 0
2021-05-16 20:00:00 1 107 1044 11 6 0
2021-05-16 21:00:00 1 107 1044 11 6 0
2021-05-16 22:00:00 1 107 1044 11 6 0
2021-05-16 23:00:00 1 107 1044 11 6 0
2021-05-17 00:00:00 1 107 1044 11 6 0
2021-05-17 01:00:00 1 107 1044 11 6 0
2021-05-17 02:00:00 1 107 1044 11 6 0
2021-05-17 03:00:00 1 107 1044 11 6 0
2021-05-17 04:00:00 1 107 1044 11 6 0
2021-05-17 05:00:00 1 107 1044 11 6 0
2021-05-17 06:00:00 1 107 1044 11 6 0
2021-05-17 07:00:00 1 107 1044 11 6 0
2021-05-17 08:00:00 1 107 1044 11 6 0
2021-05-17 09:00:00 1 107 1044 11 6 0
2021-05-17 10:00:00 1 107 1044 11 6 0
2021-05-17 11:00:00 1 107 1044 11 6 0