Method groupby

xarray/core/dataset.py:10113–10223

Returns a DatasetGroupBy object for performing grouped operations. Parameters ---------- group : str or DataArray or IndexVariable or sequence of hashable or mapping of hashable to Grouper Array whose unique values should be used to group this array. If a

(
        self,
        group: GroupInput = None,
        *,
        squeeze: Literal[False] = False,
        restore_coord_dims: bool = False,
        eagerly_compute_group: Literal[False] | None = None,
        **groupers: Grouper,
    )

    @_deprecate_positional_args("v2024.07.0")
    def groupby(
        self,
        group: GroupInput = None,
        *,
        squeeze: Literal[False] = False,
        restore_coord_dims: bool = False,
        eagerly_compute_group: Literal[False] | None = None,
        **groupers: Grouper,
    ) -> DatasetGroupBy:
        """Returns a DatasetGroupBy object for performing grouped operations.

        Parameters
        ----------
        group : str or DataArray or IndexVariable or sequence of hashable or mapping of hashable to Grouper
            Array whose unique values should be used to group this array. If a
            Hashable, must be the name of a coordinate contained in this dataarray. If a dictionary,
            must map an existing variable name to a :py:class:`Grouper` instance.
        squeeze : False
            This argument is deprecated.
        restore_coord_dims : bool, default: False
            If True, also restore the dimension order of multi-dimensional
            coordinates.
        eagerly_compute_group: False, optional
            This argument is deprecated.
        **groupers : Mapping of str to Grouper or Resampler
            Mapping of variable name to group by to :py:class:`Grouper` or :py:class:`Resampler` object.
            One of ``group`` or ``groupers`` must be provided.
            Only a single ``grouper`` is allowed at present.

        Returns
        -------
        grouped : DatasetGroupBy
            A `DatasetGroupBy` object patterned after `pandas.GroupBy` that can be
            iterated over in the form of `(unique_value, grouped_array)` pairs.

        Examples
        --------
        >>> ds = xr.Dataset(
        ...     {"foo": (("x", "y"), np.arange(12).reshape((4, 3)))},
        ...     coords={"x": [10, 20, 30, 40], "letters": ("x", list("abba"))},
        ... )

        Grouping by a single variable is easy

        >>> ds.groupby("letters")
        <DatasetGroupBy, grouped over 1 grouper(s), 2 groups in total:
            'letters': UniqueGrouper('letters'), 2/2 groups with labels 'a', 'b'>

        Execute a reduction

        >>> ds.groupby("letters").sum()
        <xarray.Dataset> Size: 64B
        Dimensions:  (letters: 2, y: 3)
        Coordinates:
          * letters  (letters) object 16B 'a' 'b'
        Dimensions without coordinates: y
        Data variables:
            foo      (letters, y) int64 48B 9 11 13 9 11 13