In Python Pandas DataFrame.apply() method lambda expression is taking apply() method's argument

Question

I have following code

display(ch2m_cpaf.groupby('PROVIDING_COMPANY_CODE').apply(lambda df: df, axis=0))

If I will run it with axis=0 argument, it raises

TypeError: () got an unexpected keyword argument 'axis'

But why axis=0 argument is not part of lambda expression?

I tried putting it in parenthesis, it should just return Pandas' Series object

always put full error message because there are other useful information. — furas
– furas, Commented Feb 28 at 1:42
better show minimal working code which we could simpy copy and run for tests. — furas
– furas, Commented Feb 28 at 1:43
I found that apply() for groupby() don't use axis=0 - you have to remove it. df.groupby().apply() works in different way than df.apply() - and it gets different parameters. — furas
– furas, Commented Feb 28 at 1:47
axis works only if I use df.groupby(...).apply(lambda data:data.apply(..., axis=0)) — furas
– furas, Commented Feb 28 at 1:53

Temunel · Accepted Answer · 2025-02-27 22:30:48Z

1

Unlike the .apply() method of a DataFrame, which can take an axis argument, groupby().apply() applies fuctions group-wise and doesn't require an axis argument.

To fix the issue, simply remove axis=0;

display(ch2m_cpaf.groupby('PROVIDING_COMPANY_CODE').apply(lambda df: df))

If you want to perform operations on rows or columns, you should do it inside the lambda function;

display(ch2m_cpaf.groupby('PROVIDING_COMPANY_CODE').apply(lambda df: df.sum(axis=0)))  # Sum across columns

answered Feb 27 at 22:30

Temunel

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