I figured out why it wasn’t letting me subtract dates before! It was because one value was a date (year, month, day) and the other value was a date AND time (including hours, mins, seconds). The difference was really between using .datetime and .date. So I just made them both be .datetime and it worked!
When converting dates to datetime format, you can change whether it interprets the first number as day vs month (European vs American) with the “dayfirst=True” addition. For example…
pd.to_datetime(data_name.Timestamp, infer_datetime_format=True, dayfirst=True)
I practiced a lot with formatting with .strftime. I found this cool website which lists a bunch of the variables (?) that one can use (for example %-m for number of month).
Also I read on Stackexchange that generally having back to back brackets  is a sign of inefficient code. So if I find myself doing that I’ll try to find a way to do it better.
I am still confused on:
Using Kernal>Restart and Run All Code does not actually run all the code as I previously thought, which means every time I open Jupyter notebook I still have to go in and manually run the code to import Pandas and assign variable values… there’s got to be a simple way around this.
I’m having trouble converting a custom dataset into usable Pandas data. In particular I’m getting an error when formatting for a month with the %-m command. It says to not use “-” even though in the documentation for .strftime I need to use -m. Je suis confuse.
These shall be problems for the tomorrow Isaac. For now I shall continue with my day.