Pivot Table Margins aren't correctly showing NaN values despite dummy variables
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

fig = plt.figure()

data = [['Auto', 'A', 10], ['Auto', 'A', 2], ['Telco', 'B', 15], ['Manf', 'C'],
        ['Retail', 'A', ], ['Retail', 'B', ]] 
df = pd.DataFrame(data, columns = ['INDUSTRY', 'PRODUCT', 'COST'])

table_byindustry = pd.pivot_table(df, index=['INDUSTRY'], columns=['PRODUCT'], values='COST',
                                  fill_value=0, margins=True, margins_name='Total', aggfunc='count')
ax = sns.heatmap(table_byindustry, cmap='RdYlGn', linewidths=.1, annot=True, vmin=0, vmax=100, fmt="g", xticklabels=True)
ax.set_ylabel("Industry", fontsize=12)
ax.set_xlabel("Product", fontsize=12, labelpad=1)
ax.xaxis.tick_bottom()
ax.set_ylim(bottom=5,top=0)
```

#### Problem description

Pivot Table Margins ("Total") isn't showing 0 values for rows, yet will do so for columns (e.g., Product C).  As a result, the heatmap is empty for the "Total" column related to the rows ('Manf' and 'Retail') in my example.  It is treating those rows as NaN for Margin, and setting fill_value at 0 doesn't fix it.  See attached image.  Thank you for your efforts to fix this issue.

#### Expected Output
Based on the color map, there should be a color for every cell in the pivot table, including the Margins.  In addition, if the value is 0, it should be shown when the margins=True.  It seems as if the treatment is inconsistent (i.e., view the total for Product C vs. the totals for 'Manf' and 'Retail' in Industry).


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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.88-1-MANJARO
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.3
numpy            : 1.17.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 42.0.2.post20191203
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : 0.4.0
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.10.2
pandas_datareader: None
bs4              : 4.8.1
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : 3.0.2
pandas_gbq       : None
pyarrow          : 0.13.0
pytables         : None
s3fs             : None
scipy            : 1.3.2
seaborn       : 0.9.0
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : None

</details>
![bug_image_19Dec2019](https://user-images.githubusercontent.com/56904329/71194005-0816e600-2283-11ea-90b8-7fc69a79e28d.png)
