DOC: Clarifiy fill_value behavior in arithmetic ops
When adding two DataFrames using `df1.add(df2)` one can use the `fill_value` parameter to fill in any NaNs that might come up. This parameter seems pretty broken:

```python
a = pd.DataFrame(np.ones((3, 2)))
b = pd.DataFrame(np.ones((4, 3)))
print(a + b)  # all good:
#      0    1   2
# 0  2.0  2.0 NaN
# 1  2.0  2.0 NaN
# 2  2.0  2.0 NaN
# 3  NaN  NaN NaN

print(a.add(b))  # all good
print(a.add(b, fill_value=0))  # broken
#      0    1    2
# 0  2.0  2.0  1.0
# 1  2.0  2.0  1.0
# 2  2.0  2.0  1.0
# 3  1.0  1.0  1.0
```
As you see, it filled the NaNs with `1.0`. Changing `fill_value=1` will fill everything with `2.0`. However, changing some of the values inside `b` leads to more peculiar results, and I couldn't really connect the dots and find some pattern.

This was observed on Python 3.6 on both Linux and Windows.

Thanks.

<details>
```
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-514.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
pandas: 0.22.0
pytest: None
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.14.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.7
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
```
</details>