BUG: fillna(method="ffill") and ffill() on DataFrameGroupBy gives different results
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
# Your code here

import numpy as np
import pandas as pd
df = pd.DataFrame({'a':[1, 1, np.NaN, np.NaN], 'b':[10, np.NaN, 40, np.NaN]})
```
```
df
     a     b
0  1.0  10.0
1  1.0   NaN
2  NaN  40.0
3  NaN   NaN
```

```
# Case 1 - Forward fill using fillna
df.groupby(["a"]).fillna(method="ffill")

df
      b
0  10.0
1  10.0
2   NaN
3   NaN
```

```
# Case 2 - Forward fill using ffill
df.groupby(["a"]).ffill()

df
      b
0  10.0
1  10.0
2  40.0
3  40.0
```

#### Problem description
`df.groupby(["a"]).ffill()` is not ignoring the NaN group while performing forward fill. 

#### Expected Output
`df.groupby(["a"]).ffill()` should give the same output as `df.groupby(["a"]).fillna(method="ffill")` since NaN groups are ignored as per https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html#na-values-in-groupby.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 16.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8
pandas           : 1.0.4
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 44.0.0.post20200106
Cython           : None
pytest           : 5.4.3
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.17.0
pytables         : None
pytest           : 5.4.3
pyxlsb           : None
s3fs             : 0.4.2
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : 0.8.6
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
