BUG: DatetimeIndexResamplerGroupby as_index interaction with .agg()

[1112114641]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

# works
pd.DataFrame(
    {"a":np.repeat([0,1,2,3,4], 10),"b":range(50,100)}, 
    index=pd.date_range(start=pd.Timestamp.now(),freq="1min",periods=50)
).groupby("a",as_index=False).resample("2min").min()

# works
pd.DataFrame(
    {"a":np.repeat([0,1,2,3,4], 10),"b":range(50,100)}, 
    index=pd.date_range(start=pd.Timestamp.now(),freq="1min",periods=50)
).groupby("a",as_index=False).resample("2min").agg(min)

# works
pd.DataFrame(
    {"a":np.repeat([0,1,2,3,4], 10),"b":range(50,100)}, 
    index=pd.date_range(start=pd.Timestamp.now(),freq="1min",periods=50)
).groupby("a",as_index=True).resample("2min").agg({"b":"min"})

# does not work
pd.DataFrame(
    {"a":np.repeat([0,1,2,3,4], 10),"b":range(50,100)}, 
    index=pd.date_range(start=pd.Timestamp.now(),freq="1min",periods=50)
).groupby("a",as_index=False).resample("2min").agg({"b":"min"})

Issue Description

Using pandas 2.0.0 / python 3.9.13 running the above code yields different behaviour based on whether the as_index=False flag is set in the .groupby() method or not.

The resulting error message ValueError: Length of values (5) does not match length of index (30) is misleading, uninformative, and does not explain the difference in behaviour between .agg({"b":"min"}), and .agg(min). The same holds true for other standard .groupby aggregations (max, first, ...).

Could you please look into this?

Expected Behavior

.agg({"b":"min"}) and .agg(min) should yield the same result, irrespective of as_index=True/False.

Installed Versions

INSTALLED VERSIONS

commit : 478d340
python : 3.9.13.final.0
python-bits : 64
OS : Darwin
OS-release : 22.4.0
Version : Darwin Kernel Version 22.4.0: Mon Mar 6 20:59:28 PST 2023; root:xnu-8796.101.5~3/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

pandas : 2.0.0
numpy : 1.23.5
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 63.3.0
pip : 23.0.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.9.0
pandas_datareader: None
bs4 : 4.11.2
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.3
numba : 0.56.4
numexpr : None
odfpy : None
openpyxl : 3.1.1
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.0
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[szczekulskij]

Can I pick this up and get two weeks to dig into the codebase? Thanks

[luke396]

@szczekulskij Just wanted to kindly remind you that commenting on 'take' will automatically assign you to this issue. No pressure though!

[1112114641]

as an interesting aside, I discovered a new method of defining aggregations, and this code works also:

pd.DataFrame(
    {"a":np.repeat([0,1,2,3,4], 10),"b":range(50,100)}, 
    index=pd.date_range(start=pd.Timestamp.now(),freq="1min",periods=50)
).groupby("a",as_index=False).resample("2min").agg(b=("b","min"))

[szczekulskij]

take

[szczekulskij]

To keep this thread updated - I've identified the problem is in pandas/core/groupby/generic.py.
Line 421: if not self.as_index and not_indexed_same: - if this line doesn't result in True, everything works as expected

I'll now work on solving this

[szczekulskij]

Hey, could I ask for review on the attached PR ?
It definitely solves the issue, but I'm open for feedback - I'm still learning more about the repo