Numpy 'inf' values cause pandas.cut to fail
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
foo = pd.Series([1, 2, 3,])
bar = pd.Series([1, 2, 0])
baz = foo / bar
cut = pd.cut(baz, 8, duplicates='drop')

*** ValueError: missing values must be missing in the same location both left and right sides

```
#### Problem description

Having an 'inf' value in a Series seems to cause pandas.cut to fail with this error:
*** ValueError: missing values must be missing in the same location both left and right sides

I saw bug #19768 already, but that was fixed by PR 19833 in Feb, and I'm using 0.23.4 which was released on August 3, 2018. Also there's #5483, which was fixed a long time ago.

#### Expected Output

'inf' should probably be similar to the current NA-handling behavior: it should at least not raise an exception, and just drop that as a usable value.

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

<details>

pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.0.final.0
python-bits: 64
OS: Darwin
OS-release: 18.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: 3.10.0
pip: 18.1
setuptools: 40.2.0
Cython: 0.29.2
numpy: 1.15.1
scipy: 1.1.0
pyarrow: 0.11.0
xarray: None
IPython: 6.5.0
sphinx: 1.8.2
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.3
openpyxl: 2.5.10
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: 4.2.4
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.11
pymysql: None
psycopg2: 2.7.5 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
