BUG: Error concatenating timezone-aware datetime column and object column containing only None

[getuem]

Pandas version checks

• 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 main branch of pandas.

Reproducible Example

import pandas as pd
import pytz
from datetime import datetime

df1 = pd.DataFrame([{'date': datetime(2022, 12, 1, 12, 0, 0, 0, pytz.UTC)}])
df2 = pd.DataFrame([{'date': None}])
pd.concat([df1, df2])

Traceback

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Input In [55], in <cell line: 3>()
      1 df1 = pd.DataFrame([{'date': datetime(2022, 12, 1, 12, 0, 0, 0, pytz.UTC)}])
      2 df2 = pd.DataFrame([{'date': None}])
----> 3 pd.concat([df1, df2])

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/util/_decorators.py:331, in deprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper(*args, **kwargs)
    325 if len(args) > num_allow_args:
    326     warnings.warn(
    327         msg.format(arguments=_format_argument_list(allow_args)),
    328         FutureWarning,
    329         stacklevel=find_stack_level(),
    330     )
--> 331 return func(*args, **kwargs)

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/core/reshape/concat.py:381, in concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)
    159 """
    160 Concatenate pandas objects along a particular axis.
    161 
   (...)
    366 1   3   4
    367 """
    368 op = _Concatenator(
    369     objs,
    370     axis=axis,
   (...)
    378     sort=sort,
    379 )
--> 381 return op.get_result()

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/core/reshape/concat.py:616, in _Concatenator.get_result(self)
    612             indexers[ax] = obj_labels.get_indexer(new_labels)
    614     mgrs_indexers.append((obj._mgr, indexers))
--> 616 new_data = concatenate_managers(
    617     mgrs_indexers, self.new_axes, concat_axis=self.bm_axis, copy=self.copy
    618 )
    619 if not self.copy:
    620     new_data._consolidate_inplace()

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/core/internals/concat.py:233, in concatenate_managers(mgrs_indexers, axes, concat_axis, copy)
    231     fastpath = blk.values.dtype == values.dtype
    232 else:
--> 233     values = _concatenate_join_units(join_units, concat_axis, copy=copy)
    234     fastpath = False
    236 if fastpath:

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/core/internals/concat.py:542, in _concatenate_join_units(join_units, concat_axis, copy)
    539 has_none_blocks = any(unit.block.dtype.kind == "V" for unit in join_units)
    540 upcasted_na = _dtype_to_na_value(empty_dtype, has_none_blocks)
--> 542 to_concat = [
    543     ju.get_reindexed_values(empty_dtype=empty_dtype, upcasted_na=upcasted_na)
    544     for ju in join_units
    545 ]
    547 if len(to_concat) == 1:
    548     # Only one block, nothing to concatenate.
    549     concat_values = to_concat[0]

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/core/internals/concat.py:543, in <listcomp>(.0)
    539 has_none_blocks = any(unit.block.dtype.kind == "V" for unit in join_units)
    540 upcasted_na = _dtype_to_na_value(empty_dtype, has_none_blocks)
    542 to_concat = [
--> 543     ju.get_reindexed_values(empty_dtype=empty_dtype, upcasted_na=upcasted_na)
    544     for ju in join_units
    545 ]
    547 if len(to_concat) == 1:
    548     # Only one block, nothing to concatenate.
    549     concat_values = to_concat[0]

File ~/software/mambaforge/envs/dev/lib/python3.10/site-packages/pandas/core/internals/concat.py:468, in JoinUnit.get_reindexed_values(self, empty_dtype, upcasted_na)
    464         fill_value = None
    466 if isinstance(empty_dtype, DatetimeTZDtype):
    467     # NB: exclude e.g. pyarrow[dt64tz] dtypes
--> 468     i8values = np.full(self.shape, fill_value.value)
    469     return DatetimeArray(i8values, dtype=empty_dtype)
    471 elif is_1d_only_ea_dtype(empty_dtype):

AttributeError: 'NoneType' object has no attribute 'value'

Issue Description

Concatenating DataFrames fails with an AttributeError if attempting to concatenate a column with a timezone-aware datetime dtype and a column with the object dtype containing only None as values.

Expected Behavior

The expected behavior is for this to work as it does with timezone-naive datetimes:

df1 = pd.DataFrame([{'date': datetime(2022, 12, 9, 12, 0, 0, 0)}])
df2 = pd.DataFrame([{'date': None}])
pd.concat([df1, df2])

                 date
0 2022-12-09 12:00:00
0                 NaT

Installed Versions

INSTALLED VERSIONS

commit : 8dab54d
python : 3.10.6.final.0
python-bits : 64
OS : Linux
OS-release : 4.4.0-19041-Microsoft
Version : #1237-Microsoft Sat Sep 11 14:32:00 PST 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.2
numpy : 1.23.2
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.8.0
html5lib : None
pymysql : None
psycopg2 : 2.9.3
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.3
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.3
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
zstandard : None
tzdata : 2022.5

[mroeschke]

Looks like this works correctly on main now so closing

In [20]: import pandas as pd
    ...: import pytz
    ...: from datetime import datetime
    ...: 
    ...: df1 = pd.DataFrame([{'date': datetime(2022, 12, 1, 12, 0, 0, 0, pytz.UTC)}])
    ...: df2 = pd.DataFrame([{'date': None}])
    ...: pd.concat([df1, df2])
Out[20]: 
                        date
0  2022-12-01 12:00:00+00:00
0                       None