CODEWITHSUNDEEP
pythonpandasdataframeaggregation
Amir
Amir

Reputation: 1087

Apply transform of your own function in Pandas dataframe

I have pandas dataframe on which I need to some data manipulation, the following code provide me the average of column "Variable" group by "Key":

df.groupby('key').Variable.transform("mean")

The advantage of using "transform" is that it return back the result with the same index which is pretty useful.

Now, I want to have my customize function and use it within "transform" instead of "mean" more over my function need two or more column something like:

lambda (Variable, Variable1, Variable2): (Variable + Variable1)/Variable2

(actual function of mine is more complicated than this example) and each row of my dataframe has Variable,Variable1 and Variable2.

I am wondering if I can define and use such a customized function within "transform" to be able to rerun the result back with same index?

Thanks, Amir

Upvotes: 2

Views: 2444

Answers (2)

Soroosh Shafiee
Soroosh Shafiee

Reputation: 46

Why didn't you use simple

df.Variable + df.Variable1 / df.Variable2

There is no need to groupby. In case for example you want to divide by df.groupby('key').Variable2.transform("mean") you can still do it with transform as following:

df.Variable + df.Variable1 / df.groupby('key').Variable2.transform("mean")

Upvotes: 0

Zeugma
Zeugma

Reputation: 32105

Don't call transform against Variable, call it on the grouper and then call your variables against the dataframe the function receives as argument:

df.groupby('key').transform(lambda x: (x.Variable + x.Variable1)/x.Variable2)

Upvotes: 2

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