BUG: `NaT` does not propagate in row-wise `max` for `datetime64` rows
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
pdf = pd.DataFrame()
pdf['a'] = pd.Series(['2020-01-01 08:00:00', '1920-02-01 09:00:00'], dtype='datetime64[ns]')
pdf['b'] = pd.Series(['2020-02-01 08:00:00', pd.NaT], dtype='datetime64[ns]')
pdf.max(axis=1, skipna=False)
```

#### Problem description
Current output is 
```
0   2020-02-01 08:00:00
1   1920-02-01 09:00:00
dtype: datetime64[ns]
```
In general, missing values involved in reduction should propagate.

#### Expected Output
```
0   2020-02-01 08:00:00
1   NaT
dtype: datetime64[ns]
```

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.7.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-48-generic
Version          : #52~18.04.1-Ubuntu SMP Thu Sep 10 12:50:22 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8

pandas           : 1.1.2
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 49.6.0.post20200917
Cython           : 0.29.21
pytest           : 6.1.1
hypothesis       : 5.28.0
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.3.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.3
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.0rc1
</details>
