BUG: pd.DataFrame.mul has not support fill_value?

[TungPhaSanh]

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
df = pd.DataFrame(np.arange(12).reshape(3,4))
s = [1,pd.NA,3]
df.mul(s, axis="columns", fill_value=0)

Issue Description

It raise error: fill_value=0 is not supported

Expected Behavior

It should return the result with filled NA value of 0

Installed Versions

2.3.0

[sanggon6107]

Hi @TungPhaSanh ,

It seems the example code doesn't work because s only has 3 elements - I think it needs 4.

I have tried this on the main branch, but mul seems to work fine when fill_value=0.

>>> import pandas as pd
>>> import numpy as np

>>> df = pd.DataFrame(np.arange(12).reshape(3,4))
>>> df
   0  1   2   3
0  0  1   2   3
1  4  5   6   7
2  8  9  10  11
>>> s = [1,pd.NA,3, 4]
>>> s
[1, <NA>, 3, 4]
>>> df.mul(s, axis="columns", fill_value=0)
   0  1   2   3
0  0  0   6  12
1  4  0  18  28
2  8  0  30  44

[TungPhaSanh]

Thanks @sanggon6107

My bad. Sorry with my example, the true one is:

import pandas as pd
df = pd.DataFrame(np.arange(12).reshape(3,4))
s = [1,pd.NA,3]
df.mul(s, axis="index", fill_value=0) # index instead of columns

I have try it, it is okay, but sometimes in my project it raise error fill_value=0 is not supported. I have to fillna first before doing multiplication.

[asishm]

Thanks for the report. Your example doesn't reproduce for me on latest release (2.3.0) with axis='index'.

Can you confirm your example provided currently fails for you and if so, please provide the full traceback. If not, please update your post with a reproducible example. Thanks!

>>> df
   0  1   2   3
0  0  1   2   3
1  4  5   6   7
2  8  9  10  11
>>> s = [1,pd.NA,3]
>>> df.mul(s, axis="index", fill_value=0)
    0   1   2   3
0   0   1   2   3
1   0   0   0   0
2  24  27  30  33
>>> pd.__version__
'2.3.0'