Closes #4658

- Use get_index(dim) in drop_sel
- Add drop_isel

doc/groupby.rst

@@ -226,4 +226,4 @@ applying your function, and then unstacking the result:
 .. ipython:: python
 
     stacked = da.stack(gridcell=["ny", "nx"])
-    stacked.groupby("gridcell").sum(...).unstack("gridcell")
+    stacked.groupby("gridcell").sum(...).unstack("gridcell")

doc/internals.rst

@@ -230,4 +230,4 @@ re-open it directly with Zarr:
 
     zgroup = zarr.open("rasm.zarr")
     print(zgroup.tree())
-    dict(zgroup["Tair"].attrs)
+    dict(zgroup["Tair"].attrs)

doc/interpolation.rst

@@ -317,4 +317,4 @@ The remapping can be done as follows
     dsi = ds.interp(lon=lon, lat=lat)
     dsi.air.plot(ax=axes[1])
     @savefig interpolation_sample4.png width=8in
-    axes[1].set_title("Remapped data")
+    axes[1].set_title("Remapped data")

doc/plotting.rst

@@ -955,4 +955,4 @@ One can also make line plots with multidimensional coordinates. In this case, ``
     f, ax = plt.subplots(2, 1)
     da.plot.line(x="lon", hue="y", ax=ax[0])
     @savefig plotting_example_2d_hue_xy.png
-    da.plot.line(x="lon", hue="x", ax=ax[1])
+    da.plot.line(x="lon", hue="x", ax=ax[1])

doc/reshaping.rst

@@ -288,4 +288,4 @@ As a shortcut, you can refer to existing coordinates by name:
 
     ds.sortby("x")
     ds.sortby(["y", "x"])
-    ds.sortby(["y", "x"], ascending=False)
+    ds.sortby(["y", "x"], ascending=False)

xarray/core/dataset.py

@@ -4053,13 +4053,68 @@ def drop_sel(self, labels=None, *, errors="raise", **labels_kwargs):
                 labels_for_dim = [labels_for_dim]
             labels_for_dim = np.asarray(labels_for_dim)
             try:
-                index = self.indexes[dim]
+                index = self.get_index(dim)
             except KeyError:
                 raise ValueError("dimension %r does not have coordinate labels" % dim)
             new_index = index.drop(labels_for_dim, errors=errors)
             ds = ds.loc[{dim: new_index}]
         return ds
 
+    def drop_isel(self, indexers=None, **indexers_kwargs):
+        """Drop index positions from this dataset.
+
+        Parameters
+        ----------
+        indexers : mapping of hashable to Any
+            Index locations to drop
+        **indexers_kwargs : {dim: position, ...}, optional
+            The keyword arguments form of ``dim`` and ``positions``
+
+        Returns
+        -------
+        dropped : Dataset
+
+        Raises
+        ------
+        IndexError
+
+        Examples
+        --------
+        >>> data = np.random.randn(2, 3)
+        >>> labels = ["a", "b", "c"]
+        >>> ds = xr.Dataset({"A": (["x", "y"], data), "y": labels})
+        >>> ds.drop_isel(y=[0, 2])
+        <xarray.Dataset>
+        Dimensions:  (x: 2, y: 1)
+        Coordinates:
+          * y        (y) <U1 'b'
+        Dimensions without coordinates: x
+        Data variables:
+            A        (x, y) float64 0.4002 1.868
+        >>> ds.drop_sel(y=1)
+        <xarray.Dataset>
+        Dimensions:  (x: 2, y: 2)
+        Coordinates:
+          * y        (y) <U1 'a' 'c'
+        Dimensions without coordinates: x
+        Data variables:
+            A        (x, y) float64 1.764 0.9787 2.241 -0.9773
+        """
+
+        indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "drop")
+
+        ds = self
+        for dim, pos_for_dim in indexers.items():
+            # Don't cast to set, as it would harm performance when labels
+            # is a large numpy array
+            if utils.is_scalar(pos_for_dim):
+                pos_for_dim = [pos_for_dim]
+            pos_for_dim = np.asarray(pos_for_dim).tolist()
+            index = self.get_index(dim)
+            new_index = index.delete(pos_for_dim)
+            ds = ds.loc[{dim: new_index}]
+        return ds
+
     def drop_dims(
         self, drop_dims: Union[Hashable, Iterable[Hashable]], *, errors: str = "raise"
     ) -> "Dataset":

xarray/tests/test_dataset.py

@@ -2371,8 +2371,12 @@ def test_drop_index_labels(self):
             data.drop(DataArray(["a", "b", "c"]), dim="x", errors="ignore")
         assert_identical(expected, actual)
 
-        with raises_regex(ValueError, "does not have coordinate labels"):
-            data.drop_sel(y=1)
+        actual = data.drop_sel(y=[1])
+        expected = data.isel(y=[0, 2])
+        assert_identical(expected, actual)
+
+        with raises_regex(KeyError, "not found in axis"):
+            data.drop_sel(x=0)
 
     def test_drop_labels_by_keyword(self):
         data = Dataset(
@@ -2410,6 +2414,30 @@ def test_drop_labels_by_keyword(self):
         with pytest.raises(ValueError):
             data.drop(dim="x", x="a")
 
+    def test_drop_labels_by_position(self):
+        data = Dataset(
+            {"A": (["x", "y"], np.random.randn(2, 6)), "x": ["a", "b"], "y": range(6)}
+        )
+        # Basic functionality.
+        assert len(data.coords["x"]) == 2
+
+        ds2 = data.drop_isel(x=0)
+        ds3 = data.drop_isel(x=[0])
+        ds4 = data.drop_isel(x=[0, 1])
+        ds5 = data.drop_isel(x=[0, 1], y=range(0, 6, 2))
+
+        assert_array_equal(ds2.coords["x"], ["b"])
+        assert_array_equal(ds3.coords["x"], ["b"])
+        assert ds4.coords["x"].size == 0
+        assert ds5.coords["x"].size == 0
+        assert_array_equal(ds5.coords["y"], [1, 3, 5])
+
+        with pytest.raises(KeyError):
+            data.drop_isel(z=1)
+
+        with pytest.raises(IndexError):
+            data.drop_isel(x=5)
+
     def test_drop_dims(self):
         data = xr.Dataset(
             {