FutureWarning: DataFrameGroupBy.apply does not have a clear solution.

[hunterhogan]

IDK how pandas will classify this issue.

df = df.sort_values(by=['oeisID', 'n', 'boundary'], ascending=[True, True, False])
def addColumnsGrowing(groupBy: pandas.DataFrame) -> pandas.DataFrame:
    groupBy['bucketsGrowing'] = groupBy['buckets'].diff().gt(0).fillna(True)
    groupBy['arcCodesGrowing'] = groupBy['arcCodes'].diff().gt(0).fillna(True)
    return groupBy
df = df.groupby(['oeisID', 'n'], group_keys=False).apply(addColumnsGrowing)

C:\Users\hunte\AppData\Local\Temp\ipykernel_25960\1489258679.py:6: FutureWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass include_groups=False to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.
df = df.groupby(['oeisID', 'n'], group_keys=False).apply(addColumnsGrowing)

"... pass include_groups=False" to what method?

"... or explicitly select the grouping columns." Is that a method, a parameter, or a topic in the documentation?

df = df.sort_values(by=['oeisID', 'n', 'boundary'], ascending=[True, True, False])
def addColumnsGrowing(groupBy: pandas.DataFrame) -> pandas.DataFrame:
    groupBy['bucketsGrowing'] = groupBy['buckets'].diff().gt(0).fillna(True)
    groupBy['arcCodesGrowing'] = groupBy['arcCodes'].diff().gt(0).fillna(True)
    return groupBy
df = df.groupby(['oeisID', 'n'], group_keys=False, include_groups=False).apply(addColumnsGrowing)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[6], line 6
      4     groupBy['arcCodesGrowing'] = groupBy['arcCodes'].diff().gt(0).fillna(True)
      5     return groupBy
----> 6 df = df.groupby(['oeisID', 'n'], group_keys=False, include_groups=False).apply(addColumnsGrowing)

TypeError: DataFrame.groupby() got an unexpected keyword argument 'include_groups'

Not groupby.

df = df.sort_values(by=['oeisID', 'n', 'boundary'], ascending=[True, True, False])
def addColumnsGrowing(groupBy: pandas.DataFrame) -> pandas.DataFrame:
    groupBy['bucketsGrowing'] = groupBy['buckets'].diff().gt(0).fillna(True)
    groupBy['arcCodesGrowing'] = groupBy['arcCodes'].diff().gt(0).fillna(True)
    return groupBy
df = df.groupby(['oeisID', 'n'], group_keys=False).apply(addColumnsGrowing, include_groups=False)

apply can't be right because I am getting diagnostic errors.

[{
	"resource": "/c:/apps/mapFolding/mapFolding/reference/matrixMeandersAnalysis/buckets.ipynb",
	"owner": "pylance12",
	"code": {
		"value": "reportCallIssue",
		"target": {
			"$mid": 1,
			"path": "/microsoft/pylance-release/blob/main/docs/diagnostics/reportCallIssue.md",
			"scheme": "https",
			"authority": "github.com"
		}
	},
	"severity": 8,
	"message": "No parameter named \"include_groups\"",
	"source": "Pylance",
	"startLineNumber": 6,
	"startColumn": 77,
	"endLineNumber": 6,
	"endColumn": 91,
	"origin": "extHost1"
}]

But if I run the cell, it seems to work, and I don't get a FutureWarning.

Partial solution

As I have tried to express many times to the Python community: the original linter was called a "spell checker." The same CI/CD concepts and tools can easily be applied to the words-that-are-not-code, which would have many benefits, including fewer "Issues" from confused users.

[hunterhogan]

But if I run the cell, it seems to work, and I don't get a FutureWarning.

No, I was wrong. ['oeisID', 'n'] are missing from the returned dataframe.

I scored 53%-tile on the GRE Comp Sci subject exam, but I guess I am too stupid to use pandas.

[rhshadrach]

Thanks for the report!

apply can't be right because I am getting diagnostic errors.

Using the argument in apply is correct, see the documentation: https://pandas.pydata.org/docs/reference/api/pandas.core.groupby.DataFrameGroupBy.apply.html

As to why Pylance is flagging this, I would guess the version of pandas Pylance is using and the version of pandas you have is out of sync. But I don't believe there is enough information to provide further assistance.

[pruthviraj-chavan]

You tried to add include_groups=False to .groupby(), but that parameter actually belongs to .apply(), not .groupby().

[rhshadrach]

I don't believe there is anything for pandas to do here. Closing.

[hunterhogan]

2 minutes ago:

I don't believe there is anything for pandas to do here. Closing.

😢

I just spent the last hour preparing information to address your comment:

As to why Pylance is flagging this, I would guess the version of pandas Pylance is using and the version of pandas you have is out of sync. But I don't believe there is enough information to provide further assistance.

[rhshadrach]

Issues can be reopened, if there is something actionable here will be happy to reopen!

[hunterhogan]

• Actionable for pandas: clarify the FutureWarning.
• Actionable for pandas: put documentation in the docstrings.

I don't understand why the diagnostic error is happening. I have identified some unexpected behavior, but I don't know how to interpret it.

Context

Development

Version: 1.105.0-insider (user setup)
Commit: 6e60e679fc6b6a512edbed9a750d7c5811595861
Date: 2025-10-01T05:02:28.879Z
Electron: 37.5.1
ElectronBuildId: 12409799
Chromium: 138.0.7204.251
Node.js: 22.19.0
V8: 13.8.258.32-electron.0
OS: Windows_NT x64 10.0.26100

ms-python.vscode-pylance
Version
2025.8.3
Last Updated
1 day ago

(.vanalysis) C:\apps\mapFolding>ver & py -VV & pip list

Microsoft Windows [Version 10.0.26100.6725]
Python 3.13.7 (tags/v3.13.7:bcee1c3, Aug 14 2025, 14:15:11) [MSC v.1944 64 bit (AMD64)]
Package                 Version     Editable project location
----------------------- ----------- -------------------------
asttokens               3.0.0
astToolkit              0.8.0
autoflake               2.3.1
charset-normalizer      3.4.3
colorama                0.4.6
comm                    0.2.3
contourpy               1.3.3
cycler                  0.12.1
debugpy                 1.8.17
decorator               5.2.1
docutils                0.22.2
et_xmlfile              2.0.0
executing               2.2.1
fonttools               4.60.1
hunterMakesPy           0.2.4
ipykernel               6.30.1
ipython                 9.6.0
ipython_pygments_lexers 1.1.1
isort                   6.0.1
jedi                    0.19.2
joblib                  1.5.2
jupyter_client          8.6.3
jupyter_core            5.8.1
kiwisolver              1.4.9
mapFolding              0.16.2      C:\apps\mapFolding
matplotlib              3.10.6
matplotlib-inline       0.1.7
more-itertools          10.8.0
mpmath                  1.3.0
nest-asyncio            1.6.0
numpy                   2.3.3
openpyxl                3.1.5
packaging               25.0
pandas                  2.3.3
parso                   0.8.5
patsy                   1.0.1
pillow                  11.3.0
pip                     25.2
platformdirs            4.4.0
prompt_toolkit          3.0.52
psutil                  7.1.0
pure_eval               0.2.3
pyarrow                 21.0.0
pyflakes                3.4.0
Pygments                2.19.2
pyparsing               3.2.5
python-dateutil         2.9.0.post0
pytz                    2025.2
pywin32                 311
pyzmq                   27.1.0
scikit-learn            1.7.2
scipy                   1.16.2
seaborn                 0.13.2
six                     1.17.0
stack-data              0.6.3
statistics              1.0.3.5
statsmodels             0.14.5
sympy                   1.14.0
threadpoolctl           3.6.0
tornado                 6.5.2
traitlets               5.14.3
typing_extensions       4.15.0
tzdata                  2025.2
wcwidth                 0.2.14

(.vanalysis) C:\apps\mapFolding>pip list --outdated

(.vanalysis) C:\apps\mapFolding>

1. pandas 2.3.3
2. pandas-stubs not installed
3. Main repo
4. Stubs repo

The locus of the diagnostic error

The notebook, but it does not include include_groups=False at the moment because I want the groups included.

The following diagnostic links to generic.pyi(201, 9).

No overloads for "apply" match the provided argumentsPylance(reportCallIssue)
generic.pyi(201, 9): Overload 2 is the closest match
(method)
def apply(
    func: DFCallable1[P@apply],
    /,
    ...
) -> Series[Any]: ...

def apply(
    func: DFCallable2[P@apply],
    /,
    ...
) -> DataFrame: ...

def apply(
    func: DFCallable3[P@apply],
    /,
    ...
) -> DataFrame: ...

Those overload definitions don't have include_groups, obviously, but that doesn't mean Pylance linked to the correct 'attr'. (IDK the proper way to describe it.) When I select .apply and choose F12 "Go to Definition," I see this:

That is the correct directory for the stub files, which I think is good. But that is __getattr__, not apply, so I hit F12 again, and I am taken here:

I don't understand why:

• Pylance went to the pandas installation in the venv (".vanalysis") instead of the stub file
• "groupby.py" has the parameter, but the stub file doesn't
• Pylance took me to a signature with the parameter, but tells me that the signature doesn't have the parameter

[rhshadrach]

Actionable for pandas: clarify the FutureWarning.

No objection to a PR adding "to the apply method", but I do not think it is a necessity either.

Actionable for pandas: put documentation in the docstrings.

What documentation would you like to see?

For the Pylance issue, I believe this is because the argument is missing in pandas-stubs. I've opened pandas-dev/pandas-stubs#1407.