NaT values cannot be compared with tz-aware datetime objects
#### Code Sample, a copy-pastable example if possible

```python
import pandas
import datetime
a = pandas.DataFrame({'b': [pandas.NaT]})
a.b > datetime.datetime.now(datetime.timezone.utc)
```

Output:

```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../pandas/core/ops/__init__.py", line 1179, in wrapper
    res_values = dispatch_to_index_op(op, self, other, pd.DatetimeIndex)
  File ".../pandas/core/ops/__init__.py", line 630, in dispatch_to_index_op
    result = op(left_idx, right)
  File ".../pandas/core/indexes/datetimelike.py", line 132, in wrapper
    result = op(self._data, maybe_unwrap_index(other))
  File ".../pandas/core/arrays/datetimes.py", line 168, in wrapper
    self._assert_tzawareness_compat(other)
  File ".../pandas/core/arrays/datetimes.py", line 789, in _assert_tzawareness_compat
    "Cannot compare tz-naive and tz-aware " "datetime-like objects."
TypeError: Cannot compare tz-naive and tz-aware datetime-like objects.
```

#### Problem description

When parsing timestamps, I return `pandas.NaT` if value is not parsed correctly. Otherwise I return timezone-aware timestamps. I also want then to compare those values with a timezone-aware timestamp. But if there is any `pandas.NaT` value present comparison fails.

#### Expected Output

```
0    False
Name: b, dtype: bool
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.0.0-37-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.2
numpy            : 1.17.3
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.0.3
setuptools       : 40.4.3
Cython           : 0.29.10
pytest           : 4.4.1
hypothesis       : None
sphinx           : 1.8.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.2.5
html5lib         : 0.9999999
pymysql          : None
psycopg2         : 2.8.3 (dt dec pq3 ext lo64)
jinja2           : 2.10
IPython          : None
pandas_datareader: None
bs4              : 4.7.1
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.2.5
matplotlib       : 3.0.0
numexpr          : 2.6.9
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.15.1
pytables         : None
s3fs             : None
scipy            : 1.3.1
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
