BUG: Sampling over selected groupbys does not reflect the selection
- [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.

---

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

```python
>>> import pandas as pd
>>> df1 = pd.DataFrame({'a': [3, 5, 2, 7, 1, 2, 4, 6, 2, 4],
                       'b': [8, 3, 4, 1, 8, 2, 2, 2, 2, 3],
                       'c': [1, 8, 8, 5, 3, 5, 0, 0, 5, 4],
                       'd': [9, 7, 6, 3, 6, 3, 2, 1, 5, 8]}, index=list(range(10, 20)))
>>> # selecting one single column works
>>> df1.groupby('c').b.sample(1)
7    2
0    8
4    8
9    3
3    1
2    4
Name: b, dtype: int64
>>> # selecting multiple columns does not work
>>> df1.groupby('c')[['a', 'd']].sample(1)
   a  b  c  d
7  6  2  0  1
0  3  8  1  9
4  1  8  3  6
9  4  3  4  8
8  2  2  5  5
2  2  4  8  6
```

#### Problem description

When ``['a', 'd']`` is selected, the result should only contain column ``a`` and ``d``. However, this selection has no effect on the result produced by `groupby-sample`.

#### Expected Output

```python
>>> df1.groupby('c')[['a', 'd']].sample(1)
   a  d
7  6  1
0  3  9
4  1  6
9  4  8
8  2  5
2  2  6
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : 7d32926db8f7541c356066dcadabf854487738de
python           : 3.8.5.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Tue Jan 12 22:13:05 PST 2021; root:xnu-6153.141.16~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : zh_CN.UTF-8
pandas           : 1.2.2
numpy            : 1.19.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 49.6.0.post20200814
Cython           : 0.29.21
pytest           : 6.0.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.17.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : 0.4.2
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.6.0
sqlalchemy       : 1.3.18
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.2

</details>
