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'

[TungPhaSanh]

Hi @asishm ,

I have face this error in my project, when I try it. Here is my code:

adjusted_data[["Open", "High", "Low", "Close"]] = adjusted_data[
    ["Open", "High", "Low", "Close"]
].mul(adjusted_data["Multiplier"], axis=0, fill_value=1)

---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_9980\1777838207.py in ?()
      2     listed_data, adjustment_multiplier, left_on="Ticker", right_index=True, how="left"
      3 )
      4 adjusted_data[["Open", "High", "Low", "Close"]] = adjusted_data[
      5     ["Open", "High", "Low", "Close"]
----> 6 ].mul(adjusted_data["Multiplier"], axis=0, fill_value=1)
      7 adjusted_data

~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\LocalCache\local-packages\Python313\site-packages\pandas\core\frame.py in ?(self, other, axis, level, fill_value)
   8386     @Appender(ops.make_flex_doc("mul", "dataframe"))
   8387     def mul(
   8388         self, other, axis: Axis = "columns", level=None, fill_value=None
   8389     ) -> DataFrame:
-> 8390         return self._flex_arith_method(
   8391             other, operator.mul, level=level, fill_value=fill_value, axis=axis
   8392         )

~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\LocalCache\local-packages\Python313\site-packages\pandas\core\frame.py in ?(self, other, op, axis, level, fill_value)
   8264 
   8265         if isinstance(other, Series) and fill_value is not None:
   8266             # TODO: We could allow this in cases where we end up going
   8267             #  through the DataFrame path
-> 8268             raise NotImplementedError(f"fill_value {fill_value} not supported.")
   8269 
   8270         other = ops.maybe_prepare_scalar_for_op(other, self.shape)
   8271         self, other = self._align_for_op(other, axis, flex=True, level=level)

NotImplementedError: fill_value 1 not supported.

For more information: adjusted_data is a DataFrame of 9 columns * 4,000,000 rows.

But when I try the following:

adjusted_data[["Open", "High", "Low", "Close"]] = adjusted_data[
    ["Open", "High", "Low", "Close"]
].mul(adjusted_data["Multiplier"].fillna(1), axis=0)

it is okay.