(Pandas) Set values for multiple columns at once using apply

Question

I am using an apply method to determine the values for the three columns I am trying to create. The function that is responsible for calculating is calculate. It gives back the three values that are needed. The problem is how do I assign those three values to the columns. I tried doing something like this

def calculate(row):
    return 'column1_value', 'column2_value', 'column3_value'

df[['column1', 'column2', 'column3']] = df.apply(lambda row: calculate(row), axis=1)

That did not work, but is there a way that would allow assigning multiple values to multiple columns at once?

I am not sure if you are calculating the new column values based on your existing df values — chatax
– chatax, Commented Aug 12, 2021 at 19:56
I am, I didn't show the process of doing that in the question in order to simplify it — tedzz
– tedzz, Commented Aug 12, 2021 at 19:58

chatax · Accepted Answer · 2021-08-12 20:06:17Z

1

You could make a second DataFrame of your apply and concat the two column wise. This will create the new columns to your original dataframe

def calculate(row):
    return 'column1_value', 'column2_value', 'column3_value'

df2 = pd.DataFrame(list(df.apply(calculate, axis=1)), columns=['column1', 'column2', 'column3'])
df = pd.concat([df, df2], axis=1)

answered Aug 12, 2021 at 20:06

chatax

9984 silver badges17 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

(Pandas) Set values for multiple columns at once using apply

1 Answer 1

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related