DataFrame.min/max with axis=1, datetime64[ns, tz] types and NaT values returns NaNs
#### Code Sample, a copy-pastable example if possible

```python
s1 = pd.Series([pd.Timestamp('2017-01-01T10', tz='UTC'), pd.Timestamp('2017-01-01T11', tz='UTC')])
s2 = pd.Series([pd.Timestamp('2017-01-01T12', tz='UTC'), pd.NaT])

df = pd.DataFrame(dict(s1=s1, s2=s2))
df.min(axis=1)
```

produces:

```
0  NaN
1  NaN
dtype: float64
```
#### Problem description

For tz-aware timestamp columns, as soon as `pd.NaT` value is present in any row in any of the columns, than the column-wise `min()/max()` operations returns all `NaN`s. 

If columns are non-tz-aware, then `min()/max()` work as expected, i.e. the result is similar to the one pasted below (except for the timezone part). 

#### Expected Output

```
0   2017-01-01 10:00:00+00:00
1   2017-01-01 11:00:00+00:00
dtype: datetime64[ns, UTC]
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.1
numpy            : 1.17.2
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 18.0
setuptools       : 41.2.0
Cython           : 0.27.3
pytest           : 4.4.0
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.2.6
html5lib         : None
pymysql          : None
psycopg2         : 2.7.3.2 (dt dec pq3 ext lo64)
jinja2           : 2.10.1
IPython          : 7.7.0
pandas_datareader: None
bs4              : 4.6.3
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.2.6
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : 0.11.0
pyarrow          : 0.13.0
pytables         : None
s3fs             : None
scipy            : 1.0.0
sqlalchemy       : 1.3.8
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
