Description
Code Sample, a copy-pastable example if possible
import pandas as pd
periods = pd.period_range(start="2019-01", periods=4, freq="M")
groups = [1, 1, 2, 2]
df = pd.DataFrame({"periods": periods, "groups": groups})
result = df.groupby("groups")["periods"].min()
Problem description
The last line of the example throws a TypeError: data type not understood.
Expected Output
The result
DataFrame should contain the earliest period (in this case 2019-01) for each grouping slice.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.8.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United Kingdom.1252
pandas : 1.0.0
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.1.0.post20200127
Cython : None
pytest : None
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 : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None