Method stack

xarray/core/dataset.py:5280–5328

Stack any number of existing dimensions into a single new dimension. New dimensions will be added at the end, and by default the corresponding coordinate variables will be combined into a MultiIndex. Parameters ---------- dim : mapping of hashable t

(
        self,
        dim: Mapping[Any, Sequence[Hashable | EllipsisType]] | None = None,
        create_index: bool | None = True,
        index_cls: type[Index] = PandasMultiIndex,
        **dim_kwargs: Sequence[Hashable | EllipsisType],
    )

    @partial(deprecate_dims, old_name="dimensions")
    def stack(
        self,
        dim: Mapping[Any, Sequence[Hashable | EllipsisType]] | None = None,
        create_index: bool | None = True,
        index_cls: type[Index] = PandasMultiIndex,
        **dim_kwargs: Sequence[Hashable | EllipsisType],
    ) -> Self:
        """
        Stack any number of existing dimensions into a single new dimension.

        New dimensions will be added at the end, and by default the corresponding
        coordinate variables will be combined into a MultiIndex.

        Parameters
        ----------
        dim : mapping of hashable to sequence of hashable
            Mapping of the form `new_name=(dim1, dim2, ...)`. Names of new
            dimensions, and the existing dimensions that they replace. An
            ellipsis (`...`) will be replaced by all unlisted dimensions.
            Passing a list containing an ellipsis (`stacked_dim=[...]`) will stack over
            all dimensions.
        create_index : bool or None, default: True

            - True: create a multi-index for each of the stacked dimensions.
            - False: don't create any index.
            - None. create a multi-index only if exactly one single (1-d) coordinate
              index is found for every dimension to stack.

        index_cls: Index-class, default: PandasMultiIndex
            Can be used to pass a custom multi-index type (must be an Xarray index that
            implements `.stack()`). By default, a pandas multi-index wrapper is used.
        **dim_kwargs
            The keyword arguments form of ``dim``.
            One of dim or dim_kwargs must be provided.

        Returns
        -------
        stacked : Dataset
            Dataset with stacked data.

        See Also
        --------
        Dataset.unstack
        """
        dim = either_dict_or_kwargs(dim, dim_kwargs, "stack")
        result = self
        for new_dim, dims in dim.items():
            result = result._stack_once(dims, new_dim, index_cls, create_index)
        return result

    def to_stacked_array(
        self,