BUG: Inconsistency between behavior of cumsum when applied directly, and when applied within groupby. #44009
Description
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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 master branch of pandas.
Reproducible Example
import pandas as pd df = pd.DataFrame({"A": [2, 1, 2, 2], "B": [3, 3, 4, 4], "E": [['10'], ['20'], ['30'], ['40']]}) df["A"].cumsum() df["E"].cumsum() df.groupby("B")["A"].cumsum() df.groupby("B")["E"].cumsum()Issue Description
Inconsistency between behavior of cumsum() when applied directly, and when applied within groupby().
When used directly on a column of a dataframe that contains lists, cumsum() progressively concatenates the lists.
When used as part of groupby() on the same dataframe cumsum() throws "NotImplementedError: function is not implemented for this dtype: [how->cumsum,dtype->object]"
Expected Behavior
I'd expect cumsum() to progressively concatenate the lists of all rows within each group defined by groupby(), in a way similar to what it does with numeric values.
Installed Versions
INSTALLED VERSIONS
commit : 73c6825
python : 3.8.2.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-147-generic
Version : #151-Ubuntu SMP Fri Jun 18 19:21:19 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 46.1.3
Cython : 0.29.21
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.16.0
pyxlsb : None
s3fs : None
scipy : 1.5.0
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : 0.53.1