def map(
        self,
        func: Callable[..., Dataset],
        args: tuple[Any, ...] = (),
        shortcut: bool | None = None,
        **kwargs: Any,
    ) -> Dataset:
        """Apply a function to each Dataset in the group and concatenate them
        together into a new Dataset.

        `func` is called like `func(ds, *args, **kwargs)` for each dataset `ds`
        in this group.

        Apply uses heuristics (like `pandas.GroupBy.apply`) to figure out how
        to stack together the datasets. The rule is:

        1. If the dimension along which the group coordinate is defined is
           still in the first grouped item after applying `func`, then stack
           over this dimension.
        2. Otherwise, stack over the new dimension given by name of this
           grouping (the argument to the `groupby` function).

        Parameters
        ----------
        func : callable
            Callable to apply to each sub-dataset.
        args : tuple, optional
            Positional arguments to pass to `func`.
        **kwargs
            Used to call `func(ds, **kwargs)` for each sub-dataset `ar`.

        Returns
        -------
        applied : Dataset
            The result of splitting, applying and combining this dataset.
        """
        # ignore shortcut if set (for now)
        applied = (func(ds, *args, **kwargs) for ds in self._iter_grouped())
        return self._combine(applied)
Apply a function to each Dataset in the group and concatenate them
        together into a new Dataset.

        `func` is called like `func(ds, *args, **kwargs)` for each dataset `ds`
        in this group.

        Apply uses heuristics (like `pandas.GroupBy.apply`) to figure out how
        to stack together the datasets. The rule is:

        1. If the dimension along which the group coordinate is defined is
           still in the first grouped item after applying `func`, then stack
           over this dimension.
        2. Otherwise, stack over the new dimension given by name of this
           grouping (the argument to the `groupby` function).

        Parameters
        ----------
        func : callable
            Callable to apply to each sub-dataset.
        args : tuple, optional
            Positional arguments to pass to `func`.
        **kwargs
            Used to call `func(ds, **kwargs)` for each sub-dataset `ar`.

        Returns
        -------
        applied : Dataset
            The result of splitting, applying and combining this dataset.
        
xarray/core/groupby.py