5 ms·
>pendulum is probably your best bet It is best until you work with Pandas DataFrame (https://stackoverflow.com/questions/47849342/making-pandas-work-with-pendu
by nooorofe 3y ago
>pendulum is probably your best bet
It is best until you work with Pandas DataFrame (https://stackoverflow.com/questions/47849342/making-pandas-work-with-pendulum https://stackoverflow.com/questions/47849342/making-pandas-w...)
- BiteCode_dev 3y agoNumpy and pandas are their own little island. It's not just dates and time, it's everything. If you use numpy and pandas, you should also not use Python datetime, generators, most stdlib mathematical functions, the itertools module, random, etc. It's the first thing you learn if you read any good pandas book, and the first thing I teach in my numpy/pandas trainings. It has pretty much nothing to do with pendulum. Basically, half the Python ecosystem is "well, except with numpy/pandas of course".
- nooorofe 3y agofrom zoneinfo import ZoneInfo import pendulum import datetime def pendulum_to_datetime(pendulum_dt: pendulum.DateTime) -> datetime.datetime: return datetime.datetime.fromtimestamp(pendulum_dt.timestamp(), ZoneInfo(pendulum_dt.timezone_name)) # test df = pd.DataFrame([[1, 2], [1, 2]], columns=['a', 'b']) df["time_column"] = pendulum_to_datetime(pendulum.now()) print(df) output a b time_column 0 1 2 2023-11-19 18:14:16.027777-05:00 1 1 2 2023-11-19 18:14:16.027777-05:00 >> df.dtypes a int64 b int64 time_column datetime64[ns, America/New_York] dtype: object