add dropna=False to crosstab example
```
>>> foo = pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])
>>> bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])
>>> crosstab(foo, bar)  # 'c' and 'f' are not represented in the data,
    ...                     # but they still will be counted in the output
col_0  d  e  f
row_0
a      1  0  0
b      0  1  0
c      0  0  0
```

The above example code does not produce the output shown because dropna=True is default. Changing crosstab(foo, bar) to crosstab(foo, bar, dropna=False) fixes that and produces the shown output (which is also the expected and correct output).

- [ ] closes #xxxx
- [x] tests added / passed
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
