Slicing an index with DateTime throws AttributeError: 'int' object has no attribute 'stop'
#### Code Sample, a copy-pastable example if possible

```python

idx = pd.IndexSlice

dt_index = pd.date_range(start="1jan2019 00:15:33",periods=100,freq="h")  #this will fail
#dt_index = pd.date_range(start="1jan2019",periods=100,freq="d")    #this works

zf = pd.DataFrame(index=dt_index)
zf['foo']=10
zf['bar']="squat"
zf['zaa']=range(len(dt_index))
zf.index.name="date"
zf = zf.reset_index().set_index(["date", "bar", "zaa"])


zf.loc[idx['2019-1-1':'2019-1-3',"squat",:],:]     # This works ok
zf.loc[idx['2019-1-1':,"squat",:],:]     # This fails  AttributeError: 'int' object has no attribute 'stop'
zf.loc[idx['2019-1-1':None,'squat',:],:]           # AttributeError: 'int' object has no attribute 'stop'
```
#### Problem description

The same slice of a multindex fails if the index is DateTimes but works if the index is Dates-only.
This occurs in pandas 0.24.2

A [related-sounding ticket ](https://github.com/pandas-dev/pandas/issues/10331)said if I have a reproducible example, post a new ticket.

#### Expected Output

same output as if I'd sliced a dates-only index (provided in the example above)

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: 4.3.1
pip: 19.0.3
setuptools: 40.8.0
Cython: 0.29.6
numpy: 1.16.2
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.4.0
sphinx: 1.8.5
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: 1.2.1
tables: 3.5.1
numexpr: 2.6.9
feather: None
matplotlib: 3.0.3
openpyxl: 2.6.1
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.5
lxml.etree: 4.3.2
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: 1.3.1
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>
