to_datetime loses freq on DatetimeIndex with offset

[cancan101]

It would be cool if the offset were kept. Perhaps even an error should be raised if not all of the Timestamps have the same offset:

In [36]:
dti = pd.to_datetime([pd.Timestamp("2014-1-1", offset="M"),])
dti

Out[36]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2014-01-01]
Length: 1, Freq: None, Timezone: None

See #6560

[mroeschke]

Timestamp no longer accepts the offset keyword (deprecated and removed). Closing.

[jbrockmendel]

@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)

[mroeschke]

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?

[jbrockmendel]

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.

[mroeschke]

Sounds good. Reopening.