crosstab in 0.23.4 does not respect categorical variables
#### Code Sample, a copy-pastable example if possible

```python
a = np.array(["foo", "foo", "foo", "foo", "bar", "bar", "bar", "bar", "foo", "foo", "foo"], dtype=object)
b = np.array(["one", "one", "one", "two", "one", "one", "one", "two", "two", "two", "one"], dtype=object)
c = np.array(["dull", "dull", "shiny", "dull", "dull", "shiny", "shiny", "dull", "shiny", "shiny", "shiny"], dtype=object)
foo = pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])
bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])
crosstab(foo, bar)
```

col_0  d  e
row_0      
a      1  0
b      0  1
#### Problem description

https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.crosstab.html

The example in the docs DOES NOT work

#### Expected Output

col_0  d  e  f
row_0
a      1  0  0
b      0  1  0
c      0  0  0

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


<details>



INSTALLED VERSIONS
------------------
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: en_US.UTF-8
pandas: 0.23.4
pytest: None
pip: 10.0.1
setuptools: 40.0.0
Cython: None
numpy: 1.15.0
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: 0.5.0
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: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: 0.6.0
pandas_datareader: None
</details>
