Pandas 中的日期时间

Question

I have a data frame similar to the following:

--------------------------------------------------------------------------------------
| Start_Date       |  End_Date         | Jan-16 | Feb-16 | Mar-16 | Apr-16 | May-16   |
| 2016-02-20 17:40 |  2019-11-20 16:31 |  0     | 1      | 1      | 1      | 1        |
| 2016-03-11 15:12 |  2020-11-01 12:12 |  0     | 0      | 1      | 1      | 1        |
---------------------------------------------------------------------------------------

If the start and end date fall in between January 2016 to December 2020, I need to put a 1 or else a 0 using PANDAS in the respective month column. For example, in the first row, the date is Feb 20, 2020. Therefore, there is a 0 in the Jan-16 column and 1 in Feb-16, Mar-16, Apr-16 and so on. Date is in Year, Month and Day format.

How do you achieve this?

Answer 1

If you are trying to count how many months occur between the start and end date,

import datetime
start_date = datetime.datetime.strptime('2016-02-20 17:40', '%Y-%m-%d %H:%M')
end_date = datetime.datetime.strptime('2019-11-20 16:31', '%Y-%m-%d %H:%M')
num_months = (end_date.year - start_date.year) * 12 + (end_date.month - start_date.month)

num_months print(num_months)