Pandas any() returning false with true values present
#### Code Sample

```python
In [1]: from io import StringIO

In [2]: import pandas as pd

In [3]: data = StringIO("""issue_date,issue_date_dt
   ...: ,
   ...: ,
   ...: 19600215.0,1960-02-15
   ...: ,
   ...: ,""")

In [4]: df = pd.read_csv(data, parse_dates=[1])

In [5]: df
Out[5]:
   issue_date issue_date_dt
0         NaN           NaT
1         NaN           NaT
2  19600215.0    1960-02-15
3         NaN           NaT
4         NaN           NaT

In [6]: df.any(axis=0)
Out[6]:
issue_date       True
issue_date_dt    True
dtype: bool

In [7]: df.any(axis=1)
Out[7]:
0    False
1    False
2    False
3    False
4    False
dtype: bool
```
#### Problem description

`df.any(axis=0)` behaves as expected. It returns True for both the columns, but `df.any(axis=1)` returns False for all the rows.
**Note**: A question with similar issue can be found [here](https://stackoverflow.com/questions/52732364/pandas-any-returning-false-with-true-values-present)

**Note**:  If you use `notnull` then we are getting the required output
```python
In [9]: df.notnull().any(1)
Out[9]:
0    False
1    False
2     True
3    False
4    False
dtype: bool
```
#### Expected Output
`df.any(axis=1)` should return True for those rows with True values.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.23.4
pytest: None
pip: 10.0.1
setuptools: 39.2.0
Cython: None
numpy: 1.15.0
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.5.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
