Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
print(pd.__version__)
test_df = pd.DataFrame({
'Name':['L', 'L', 'L',
'M', 'M', 'M', 'M', 'M', 'M'],
'ID': ['L1', 'L2', 'L3',
'M1', 'M2', 'M3', 'M4', 'M5', 'M6'],
'Date': [
'2005-01-01', '2006-01-01', '2013-01-01',
'2005-01-01', '2006-01-01', '2006-01-01', '2017-01-01', '2006-02-01', '2006-03-01'],
'indicator': [0, 1, 0,
0, 1, 0, 0, 1, 0],
'rolling_sum':[0, 0, 1,
0, 0, 0, 0, 1, 2]})
test_df['Date'] = pd.to_datetime(test_df['Date'], errors='coerce')
test_df.groupby('Name').rolling('731D', on='Date')['indicator'].sum().reset_index()Issue Description
Grouping by a column and then rolling over the grouped dataframe results in [ValueError: Date must be monotonic](). Ultimately, the operation should be able to produce the rolling_sum column in the example.
Expected Behavior
This is not an issue in pandas 1.3.5 but is an issue in 1.4 and higher. I expect this function to create a grouped dataframe and to then perform the rolling summation on the provided column using the date window provided.
Installed Versions
INSTALLED VERSIONS
commit : 06d2301
python : 3.8.12.final.0
python-bits : 64
OS : Darwin
OS-release : 21.1.0
Version : Darwin Kernel Version 21.1.0: Wed Oct 13 17:33:24 PDT 2021; root:xnu-8019.41.5~1/RELEASE_ARM64_T8101
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.4.1
numpy : 1.22.2
pytz : 2021.3
dateutil : 2.8.2
pip : 22.0.3
setuptools : 60.6.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.0.1
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 6.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None