Thanks @JeremyVriens for the report

Since Pandas 1.4.0 a warning is raised: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)

deprecation added in #42870

cc @jbrockmendel

IIUC in a future version this will return with object dtype, which seems More Correct to me. So might want to catch this warning and then re-issue with something more specific?

moving to 1.4.2

IIUC in a future version this will return with object dtype, which seems More Correct to me. So might want to catch this warning and then re-issue with something more specific?

Why will this return an object dtype in a future version? No warning is raised when there're non-NA values in the datetime64[ns] series ([pd.NaT, "2022-02-18"]). Maybe I'm misunderstanding why this is happening only when there're only NA values in the datetime64[ns] series. Could you maybe elaborate a bit more why you think this seems more correct?

Why will this return an object dtype in a future version?

Because object-dtype is what we get in every other case with strftime. float64 doesn't make sense as a strftime result.

ser = pd.Series([pd.Timestamp.now(), pd.NaT])

>>> ser.dt.strftime("%Y-%m-%d").dtype
dtype('O')

>>> ser[1:].dt.strftime("%Y-%m-%d").dtype
dtype('float64')

moving to 1.4.3

moving to 1.4.4

Agreed that this returning float64 dtype for all-NaN is a bug. The result dtype shouldn't depend on the values.

I think the root bug is that DatetimeIndex.strftime returns a Float64Index for all NaT

In [32]: pd.DatetimeIndex([pd.NaT]).strftime("%Y")
/home/taugspurger/miniconda3/envs/pandas=1.4.2/lib/python3.10/site-packages/pandas/core/indexes/extension.py:101: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)
  return Index(result, name=self.name)
Out[32]: Float64Index([nan], dtype='float64')

If that were fixed I think the series case will automatically be fixed too.

The underlying strftime from DatetimeArray actually properly ensures to return object dtype:

In [2]: pd.DatetimeIndex([pd.NaT])._data.strftime("%Y")
Out[2]: array([nan], dtype=object)

but indeed then passing this to Index(..) will try to infer such object dtype array as float at the moment (which is what is deprecated). Since we know here that we always have object dtype, passing that to the Index constructor should be sufficient I think.

hey there, thanks for this! so pandas>=1.4.0 is a dependency in my software package (pysyd) and I've had people reach out to me due to this error. is there a quick hack that I can do from my end or will I/they have to wait until the full v1.4.4 release?

I am receiving this warning performing a pivot of a table (it will include some date/time data)
"FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)"

Will the warning become an error in the future? Is there anything that users need to do as a work-around or will this issue be resolved in an upcoming release? (I have upgraded to 1.5.2 and still receive the warning).

Many thanks