18.06.2019 · timedelta objects contain the delta between two dates - 2 years, 2 milliseconds, etc.. You're trying to coerce this timedelta into a string representation of a date / time; a moment in time, which isn't possible. now - self.start_time isn't a date or time, it's the amount of time elapsed between then and now. Express it as, say, seconds instead:
24.11.2021 · Solution 2. The timestamp method was added in Python 3.3. So if you’re using Python 2.0, or even 2.7, you don’t have it. There are backports of current datetime to older Python versions on PyPI, but none of them seems to be official, or up-to-date; you might want to try searching for yourself. There are also a number of third-party ...
timestamp = dt.replace (tzinfo=timezone.utc).timestamp () … or: timestamp = (dt - datetime (1970, 1, 1)) / timedelta (seconds=1) Since you don't have aware datetimes, that last one is all you need. If your Python is old enough, timedelta may not have a __div__ method. In that case (if you haven't found a backport), you have to do division ...
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from datetime import datetime >>> datetime >>> datetime.datetime(2001,5,1) # You shouldn't expect this to work # as you imported the type, not the module ...
I have checked that this issue has not already been reported. I have confirmed this bug exists on the latest version of pandas. I have confirmed this bug exists on the master branch of pandas. Reproducible Example import backports.zonein...
19.10.2021 · Hello - the code works but it seems to be raising a pandas error: import pendulum from datetime import time from business_duration import businessDuration biz_hours = { "AMER": (time(8,0,...
30.10.2017 · Problem description. The documentation for pd.Series.dt.total_seconds() is a bit confusing. Reading it, one would expect that this method should work on any Series with the dt accessor. This is incorrect; looking at the API reference for datetimeline properties, it's made clear that this attribute is only available on timedelta Series.. It might be helpful to make it more …
I have a dataframe that looks like this df [output]: date time 2020-02-28 00:30:45 2020-02-28 00:30:45 2020-03-09 00:21:06 2020-03-09 00:21:06 2020-03-09 00:21:06 with df.time.dtype [