Fix CI: .table→["table"], sync points after group filtering

- test_render_labels: use sdata["table"] instead of deprecated .table
- _render_points: filter the materialized `points` DataFrame when
  groups + na_color=None so matplotlib scatter gets matching lengths

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: timtreis

src/spatialdata_plot/pl/render.py

@@ -853,8 +853,9 @@ def _render_points(
             if not hasattr(color_vector, "reset_index")
             else (color_vector[keep].reset_index(drop=True))
         )
-        # re-register filtered points in sdata_filt
-        points_dd = dask.dataframe.from_pandas(points[keep].reset_index(drop=True), npartitions=1)
+        # filter the materialized points and re-register in sdata_filt
+        points = points[keep].reset_index(drop=True)
+        points_dd = dask.dataframe.from_pandas(points, npartitions=1)
         sdata_filt.points[element] = PointsModel.parse(points_dd, coordinates={"x": "x", "y": "y"})
         set_transformation(
             element=sdata_filt.points[element],

tests/pl/test_render_labels.py

@@ -373,7 +373,7 @@ def test_plot_respects_custom_colors_from_uns_with_groups_and_palette(
         ).pl.show()
 
     def test_plot_can_annotate_labels_with_nan_in_table_obs_categorical(self, sdata_blobs: SpatialData):
-        sdata_blobs.table.obs["cat_color"] = pd.Categorical(["a", "b", "b", "a", "b"] * 5 + [np.nan])
+        sdata_blobs["table"].obs["cat_color"] = pd.Categorical(["a", "b", "b", "a", "b"] * 5 + [np.nan])
         sdata_blobs.pl.render_labels("blobs_labels", color="cat_color").pl.show()
 
     def test_plot_can_annotate_labels_with_nan_in_table_obs_continuous(self, sdata_blobs: SpatialData):