BUG: Groupby column and min aggregation over period column yields NaT for all rows
- [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:
```python
d = {
  'user_id': {
    0: 4628132781164409,
    1: 7075307556966343,
    2: 8013098674514720,
    3: 7690164883842520,
    4: 4985766983843363,
    5: 3038805367505476,
    6: 2541787162631756,
    7: 4985766983843363,
    8: 2541787162631756,
    9: 3558493739463398},
  'date': {
    0: '2020-02-12',
    1: '2020-02-12',
    2: '2020-02-12',
    3: '2020-02-12',
    4: '2020-02-12',
    5: '2020-02-12',
    6: '2020-02-12',
    7: '2020-02-12',
    8: '2020-02-12',
    9: '2020-02-12'
 }
}

df = pd.DataFrame(d).astype({'date': 'datetime64'})
df['week'] = df['date'].dt.to_period('W')
df['cohort'] = df.groupby('user_id')['week'].min()
```

#### Problem description

The above code returns NaT values for the `cohort` column, but it was expected to return the minimum values for `week`, which in this case would be `2020-02-10/2020-02-16` for all rows.

#### Expected Output
If we change the last line to:
```
df['cohort'] = df.groupby('user_id')['week'].transform('min')
```

We get the expected value for the cohort column, i.e., `2020-02-10/2020-02-16`.


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

<details>

INSTALLED VERSIONS
------------------
commit           : 67a3d4241ab84419856b84fc3ebc9abcbe66c6b3
python           : 3.7.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-1029-aws
Version          : #30~18.04.1-Ubuntu SMP Tue Oct 20 11:09:25 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.4
numpy            : 1.19.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0
Cython           : 0.29.15
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.20
tables           : None
tabulate         : 0.8.7
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.52.0

</details>
