How to use max in a lambda function applied to a pandas DataFrame

Question

I'm trying to apply a lambda function to a pandas Dataframe that return the difference between each row and the max of that column.

It can be easily achieved by using a separate variable and setting that to the max of the column, but I'm curious how it can be done in a single line of code.

import pandas as pd

df = pd.DataFrame({
    'measure': [i for i in range(0,10)]
})

col_max = df.measure.max()
df['diff_from_max'] = df.apply(lambda x: col_max - x['measure'], axis=1)

df['diff_from_max'] = df['measure'].max() - df['measure'] you dont need apply for this — anky
– anky, Commented Apr 12, 2020 at 16:31
Thanks, @anky, I need to use apply as it's a simplified version of the question I'm trying to solve. I have to call other functions as part of my lambda function and use apply to use value from other columns including max of the column. — Mehdi Zare
– Mehdi Zare, Commented Apr 12, 2020 at 16:41

BENY · Accepted Answer · 2020-04-12 16:31:05Z

2

We usually do

max_df=df.max()-df

df=df.join(max_df.add_prefix('diff_max_')

To fix your code since the apply is not need here

col_max = df.measure.max()
df['diff_from_max'] = col_max-df['measure']

edited Apr 12, 2020 at 16:31

answered Apr 12, 2020 at 16:29

BENY

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4 Comments

Mehdi Zare Over a year ago

Thanks, but it's still two line! :)

Mehdi Zare Over a year ago

output is exactly what I have in df. I'm only looking for a single line solution with apply, if it's possible.

BENY Over a year ago

@MehdiZare df.apply(lambda x: df.measure.max() - x['measure'], axis=1)?

Mehdi Zare Over a year ago

Thanks! Now I see what I missed, I used x instead of df to get the max in lambda.

Anshul Vyas · Accepted Answer · 2020-04-12 16:40:27Z

1

I think apply() is not required here. You can simply use following line :

df['diff_from_max'] = df['measure'].max() - df['measure']

answered Apr 12, 2020 at 16:40

Anshul Vyas

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