BUG: No kwargs in df.apply(raw=True)

[erezinman]

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

import pandas as pd

def func(a, b):
    return a + b

df = pd.DataFrame([[1, 2], [3, 4]])
df.apply(func, b=1) # OK
df.apply(func, raw=True, b=1) # TypeError: func() missing 1 required positional argument: 'b'

Issue Description

df.apply(raw=True) should act similarly to df.apply(Raw=False). It worked below v2.1.

Installed Versions

INSTALLED VERSIONS

commit : a60ad39
python : 3.9.18.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-75-generic
Version : #82~20.04.1-Ubuntu SMP Wed Jun 7 19:37:37 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.2
numpy : 1.25.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 67.4.0
pip : 23.0.1
Cython : 3.0.4
pytest : 7.4.3
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
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : 2.8.7
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[hvsesha]

hi @erezinman

in updated pandas version i am not getting error

import pandas as pd
def func(a, b):
return a + b

df = pd.DataFrame([[1, 2], [3, 4]])
a=df.apply(func, b=2) # OK
print(a)
0 1
0 3 4
1 5 6
df.apply(func, raw=True, b=1)
0 1
0 2 3
1 4 5
pd.version
'2.2.0.dev0+360.g4556f11c46.dirty'

[Dhayanidhi-M]

Hi ,

In existing version , we have the below code which does not have the argument of Kwargs.

result = np.apply_along_axis(
wrap_function(self.func),
self.axis,
self.values
)

I think , the upcoming pandas release has the fix for this issue by adding the kwargs as an argument.

result = np.apply_along_axis(
wrap_function(self.func),
self.axis,
self.values,
*self.args,
**self.kwargs,
)

[lithomas1]

Tentatively marking this as a regression.

If someone wants to try and backport a fix for 2.1.x, I'm happy to merge that.

[dannyi96]

take

[dannyi96]

looks like this issue has been fixed in upcoming release as part of #55089 ( earlier reported issue - #55009 )

If someone wants to try and backport a fix for 2.1.x, I'm happy to merge that.

Can raise a PR for this if still allowed.