How do I convert a dataframe with time-periods into a particular format?

Question

My initial dataframe looks as follows:

User	License	Status	Start-Date	End-Date
A	xy	access	10.01.2022	13.01.2022
B	xy	access	11.01.2022	14.01.2022
C	xy	access	11.01.2022	14.01.2022
A	xy	access	12.01.2022	15.01.2022
A	xy	access	14.01.2022	17.01.2022
B	xy	access	21.01.2022	24.01.2022
A	xy	access	21.01.2022	24.01.2022

There are three users (a, b, c) who request a license on different days. In principle, the end date is always three days later than the start date due to the fact that a license is locked for a period of 3 days.

For example, if user A accesses again within these three days, the period is extended again by three days.

My (ultimate) goal is to get a graph like the following:

So i can see how many licenses were blocked.

But this is just my goal in a later step. I thought the best way to achieve an output like this would be the following table (dataframe) in a next step and just plotting Sum over Date:

Date	A	B	C	Sum
10.01.2022	1	0	0	1
11.01.2022	1	1	1	3
12.01.2022	1	1	1	3
13.01.2022	1	1	1	3
14.01.2022	1	1	1	3
15.01.2022	1	0	0	1
16.01.2022	1	0	0	1
17.01.2022	1	0	0	1
18.01.2022	0	0	0	0
19.01.2022	0	0	0	0
20.01.2022	0	0	0	0
21.01.2022	1	1	0	2
22.01.2022	1	1	0	2
23.01.2022	1	1	0	2
24.01.2022	1	1	0	2

(But I am not sure if this is the best way to achieve it.)

Would that be possible with pandas? If yes, how? Tbh I have no clue. I hope I didn't explain the question too complicated.

So I'm only concerned with the second dataframe, how I get it, not the graph itself.