Closed cancan101 closed 1 year ago
Timestamp no longer accepts the offset keyword (deprecated and removed). Closing.
@mroeschke I think this is still an issue with the freq
keyword:
>>> pd.Timestamp('now', freq='D')
Timestamp('2018-07-07 08:17:00.395067', freq='D')
>>> pd.to_datetime(pd.Timestamp('now', freq='D'))
Timestamp('2018-07-07 08:17:08.939068', freq='D')
>>> pd.to_datetime([pd.Timestamp('now', freq='D')])
DatetimeIndex(['2018-07-07 08:17:14.227013'], dtype='datetime64[ns]', freq=None)
Oh I see. I had also rationalized closing this in light of #15146, but I see you mentioned that removing freq from Timestamp is non-trivial. Do you believe that's still the case?
Do you believe that's still the case?
Backwards-compat would be annoying, not sure if anyone would really complain though.
Getting rid of it would break a behavior that is nice for testing that (dti + other == [x + other for x in dti]).all()
. Probably not a good enough reason to keep the Timestamp.freq attribute if it isn't otherwise needed.
But as long as the attribute does exist, I think to_datetime
should preserve it.
Sounds good. Reopening.
@mroeschke didn't this get solved recently?
This now works for the scalar case but still not the array case. But should the DatetimeIndex
have a freq in this case with just 1 element?
In [5]: pd.__version__
Out[5]: '0.24.0.dev0+1010.ge413c491e'
In [6]: pd.to_datetime(pd.Timestamp("2014-1-1", freq="M"))
Out[6]: Timestamp('2014-01-01 00:00:00', freq='M')
In [7]: pd.to_datetime([pd.Timestamp("2014-1-1", freq="M")])
Out[7]: DatetimeIndex(['2014-01-01'], dtype='datetime64[ns]', freq=None)
This was once closed and then reopened due to Timestamp.freq
but can now be closed again since freq
has been deprecated and removed. closing
It would be cool if the offset were kept. Perhaps even an error should be raised if not all of the
Timestamp
s have the sameoffset
:See #6560