modin/core/dataframe/algebra/default2pandas/groupby.py
def fn(
            df,
            by,
            groupby_args,
            agg_args,
            axis=0,
            is_multi_by=None,
            drop=False,
            **kwargs
        ):
            """Group DataFrame and apply aggregation function to each group."""
            by = cls.validate_by(by)

            grp = df.groupby(by, axis=axis, **groupby_args)
            agg_func = cls.get_func(grp, key, **kwargs)
            result = (
                grp.agg(agg_func, **agg_args)
                if isinstance(agg_func, dict)
                else agg_func(grp, **agg_args)
            )

            return result
Group DataFrame and apply aggregation function to each group.
Group DataFrame and apply aggregation function to each group.
Group DataFrame and apply aggregation function to each group .
def fn(
            df,
            by,
            groupby_args,
            agg_args,
            axis=0,
            is_multi_by=None,
            drop=False,
            **kwargs
        ):
            by = cls.validate_by(by)
            grp = df.groupby(by, axis=axis, **groupby_args)
            agg_func = cls.get_func(grp, key, **kwargs)
            result = (
                grp.agg(agg_func, **agg_args)
                if isinstance(agg_func, dict)
                else agg_func(grp, **agg_args)
            )
            return result
def fn ( df , by , groupby_args , agg_args , axis = 0 , is_multi_by = None , drop = False , ** kwargs ) : by = cls . validate_by ( by ) grp = df . groupby ( by , axis = axis , ** groupby_args ) agg_func = cls . get_func ( grp , key , ** kwargs ) result = ( grp . agg ( agg_func , ** agg_args ) if isinstance ( agg_func , dict ) else agg_func ( grp , ** agg_args ) ) return result
Group DataFrame and apply aggregation function to each group.
Group DataFrame and apply aggregation function to each group .
"""Group DataFrame and apply aggregation function to each group."""
df
by
groupby_args
agg_args
axis
is_multi_by
drop