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how to optimize this kind of process
(self.python)
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.
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