There are several date/time related classes like datetime.date
, datetime.datetime
, pandas.Timestamp
, numpy.datetime64
. Are there some general guidelines when to use one over the other in a project?
What are the advantages of each?
Should I avoid using python native datetime
objects if I use pandas
most of the time?
My use case:
I have a project which uses daily financial price data, I use pandas in most functions, but I have also some functions which just use a list
of datetime.date
. I feel like it would be good to unify my data types for the whole project.