Pandas difference between apply() and aggregate() functions

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is there any difference in the (type) of the return value between the DataFrame.aggregate() and the DataFrame.apply() function if I just pass a function like

func=lambda x: x**2

because the return values seems to be pretty the same. And the documentation only tells:

apply() --> applied : Series or DataFrame

aggregate() --> aggregated : DataFrame

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