passing string value to pandas.DataFrame.fillna()   &   pandas.PivotTable(fill_value) 'breaks' pandas.DataFrame.style.highlight_* inside jupyter notebook
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np
df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
                          "bar", "bar", "bar", "bar"],
                    "B": ["one", "one", "one", "two", "two",
                          "one", "one", "two", "two"],
                    "C": ["small", "large", "large", "small",
                          "small", "large", "small", "small",
                          "large"],
                    "D": [1, 2, 2, 3, 3, 4, None, 6, 7],
                    "E": [2, 4, 5, 5, 6, 6, 8, 9, 9]})
table = pd.pivot_table(df, values='D', index=['A','B'], columns=['C'], aggfunc=np.sum, fill_value='-')

df.fillna('-').style.highlight_max()
table.style.hightlight_max()


```
![Screenshot from 2019-09-09 11-07-48](https://user-images.githubusercontent.com/8972166/64513898-36833d80-d2f2-11e9-88a2-cac3da386d08.png)

![Screenshot from 2019-09-09 11-07-23](https://user-images.githubusercontent.com/8972166/64513905-3aaf5b00-d2f2-11e9-8abf-6465e4a41878.png)


#### Problem description
`pandas.DataFrame.style.highlight_*` does not work on column where `nan` has been replaced by string using `pandas.DataFrame.fillna()`  or `pandas.PivotTable(fill_value=)`


#### Expected Output

Expected that highlight will still work on column when `fillna` or `fill_value` get strings. 


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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.0.0-27-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.1
numpy            : 1.17.1
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.2.3
setuptools       : 41.2.0
Cython           : None
pytest           : 5.1.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.4.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.10.1
IPython          : 7.7.0
pandas_datareader: None
bs4              : 4.8.0
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.4.1
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : 2.6.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.3.1
sqlalchemy       : 1.3.7
tables           : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : None

</details>
