this post was submitted on 11 Dec 2023
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Python

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how to optimize this kind of process (lemmy.eco.br)
submitted 11 months ago by driving_crooner@lemmy.eco.br to c/python@programming.dev
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Hi, When im working with some big dataframes and I need to create some columns based on functions. So i have some code like this

Def function(row): function

And then I run the function on the df as

df['new column'] = df.apply(function, axis=1)

But I do this with 10 or more columns/functions at time. I don't think this is efficient because each time a column is created it had to parce the entire data frame. There's a way to create all the columns at the same time while parsing the rows only once?

Thanks for any help.

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[โ€“] snakedrake@lemmy.world 6 points 11 months ago

Then change your function to operate across the dataframe and return a different dataframe?

You can add multiple columns at the same time or do a merge statement of some kind