Python, Pandas: Access multiple columns in lambda-function

Question

Good day,

I would like to ask if it's possible to access more than one column in a lambda-function inside a pandas-dataframe or if there's an alternative!?

For example my dataframe is looking something like this:

value_a  |  value_b  |  value_c
1        |  17       |  8
2        |  253      |  9
3        |  89       |  8
...

I also got a function that is calculating with some of the data:

def some_function(a, b):
    ...do something:
    return c

Now I want to use lambda-function to calculate together with the function but include the data from two columns. Something like this...

df['value_d'] = df['value_b'].apply(lambda x: some_function(x, df['value_c']))

Is it possible to access more than one column inside such a function or is there a better solution?

Hoping my question is understandable.

Thanks to all of you and have a great day!

Raghava Dhanya · Accepted Answer · 2021-03-16 10:37:17Z

4

use apply over whole df

df['value_d'] = df.apply(lambda row: some_function(row['value_b'],row['value_c']), axis=1)

answered Mar 16, 2021 at 10:37

Raghava Dhanya

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