def thin(
        self,
        indexers: Mapping[Any, int] | int | None = None,
        **indexers_kwargs: Any,
    ) -> Self:
        """Return a new DataArray whose data is given by each `n` value
        along the specified dimension(s).

        Examples
        --------
        >>> x_arr = np.arange(0, 26)
        >>> x_arr
        array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
               17, 18, 19, 20, 21, 22, 23, 24, 25])
        >>> x = xr.DataArray(
        ...     np.reshape(x_arr, (2, 13)),
        ...     dims=("x", "y"),
        ...     coords={"x": [0, 1], "y": np.arange(0, 13)},
        ... )
        >>> x
        <xarray.DataArray (x: 2, y: 13)> Size: 208B
        array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12],
               [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]])
        Coordinates:
          * x        (x) int64 16B 0 1
          * y        (y) int64 104B 0 1 2 3 4 5 6 7 8 9 10 11 12

        >>>
        >>> x.thin(3)
        <xarray.DataArray (x: 1, y: 5)> Size: 40B
        array([[ 0,  3,  6,  9, 12]])
        Coordinates:
          * x        (x) int64 8B 0
          * y        (y) int64 40B 0 3 6 9 12
        >>> x.thin({"x": 2, "y": 5})
        <xarray.DataArray (x: 1, y: 3)> Size: 24B
        array([[ 0,  5, 10]])
        Coordinates:
          * x        (x) int64 8B 0
          * y        (y) int64 24B 0 5 10

        See Also
        --------
        Dataset.thin
        DataArray.head
        DataArray.tail
        """
        ds = self._to_temp_dataset().thin(indexers, **indexers_kwargs)
        return self._from_temp_dataset(ds)
Return a new DataArray whose data is given by each `n` value
        along the specified dimension(s).

        Examples
        --------
        >>> x_arr = np.arange(0, 26)
        >>> x_arr
        array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
               17, 18, 19, 20, 21, 22, 23, 24, 25])
        >>> x = xr.DataArray(
        ...     np.reshape(x_arr, (2, 13)),
        ...     dims=("x", "y"),
        ...     coords={"x": [0, 1], "y": np.arange(0, 13)},
        ... )
        >>> x
        <xarray.DataArray (x: 2, y: 13)> Size: 208B
        array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12],
               [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]])
        Coordinates:
          * x        (x) int64 16B 0 1
          * y        (y) int64 104B 0 1 2 3 4 5 6 7 8 9 10 11 12

        >>>
        >>> x.thin(3)
        <xarray.DataArray (x: 1, y: 5)> Size: 40B
        array([[ 0,  3,  6,  9, 12]])
        Coordinates:
          * x        (x) int64 8B 0
          * y        (y) int64 40B 0 3 6 9 12
        >>> x.thin({"x": 2, "y": 5})
        <xarray.DataArray (x: 1, y: 3)> Size: 24B
        array([[ 0,  5, 10]])
        Coordinates:
          * x        (x) int64 8B 0
          * y        (y) int64 24B 0 5 10

        See Also
        --------
        Dataset.thin
        DataArray.head
        DataArray.tail
        
xarray/core/dataarray.py