BUG: groupby.shift return keys filled with `fill_value` when `fill_value` is specified
- [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
In [2]: df = pd.DataFrame({'a': [2, 1, 2, 1], 'b': ['x', 'x', 'y', 'y']})

In [3]: df.groupby('a').shift(1)
Out[3]: 
     b
0  NaN
1  NaN
2    x
3    x

In [4]: df.groupby('a').shift(1, fill_value='fill')
Out[4]: 
      a     b
0  fill  fill
1  fill  fill
2     2     x
3     1     x
```

#### Problem description
When specifying `fill_value` in `groupby.shift`, the returned result includes the key column with keys filled with `fill_value`. When `fill_value` is unspecified (None), the key column is not included.

#### Expected Output
It seems pretty strange that keys are to be filled with `fill_value`. This makes more sense to me:
```python
In [4]: df.groupby('a').shift(1, fill_value='fill')
Out[4]: 
      b
0  fill
1  fill
2    x
3    x
```


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

<details>


INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.7.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-76-generic
Version          : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8

pandas           : 1.2.4
numpy            : 1.20.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.1
setuptools       : 52.0.0.post20210125
Cython           : 0.29.23
pytest           : 6.2.4
hypothesis       : 6.12.0
sphinx           : 3.5.4
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.23.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 2021.04.0
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.53.1
</details>
