diff --git a/src/spatialdata_plot/pl/render.py b/src/spatialdata_plot/pl/render.py
index 014c3cc5..02934fbc 100644
--- a/src/spatialdata_plot/pl/render.py
+++ b/src/spatialdata_plot/pl/render.py
@@ -358,8 +358,7 @@ def _render_shapes(
 
         color_key = (
             [_hex_no_alpha(x) for x in color_vector.categories.values]
-            if (type(color_vector) is pd.core.arrays.categorical.Categorical)
-            and (len(color_vector.categories.values) > 1)
+            if isinstance(color_vector.dtype, pd.CategoricalDtype) and (len(color_vector.categories.values) > 1)
             else None
         )
 
@@ -854,8 +853,7 @@ def _render_points(
 
         color_key: list[str] | None = (
             list(color_vector.categories.values)
-            if (type(color_vector) is pd.core.arrays.categorical.Categorical)
-            and (len(color_vector.categories.values) > 1)
+            if isinstance(color_vector.dtype, pd.CategoricalDtype) and (len(color_vector.categories.values) > 1)
             else None
         )
 
diff --git a/src/spatialdata_plot/pl/utils.py b/src/spatialdata_plot/pl/utils.py
index 9d3b2954..ae55a9c8 100644
--- a/src/spatialdata_plot/pl/utils.py
+++ b/src/spatialdata_plot/pl/utils.py
@@ -1120,7 +1120,10 @@ def _set_color_source_vec(
             raise ValueError("Unable to create color palette.")
 
         # do not rename categories, as colors need not be unique
-        color_vector = color_source_vector.map(color_mapping)
+        # pd.Categorical.map() demotes to object dtype when mapped values aren't unique
+        # (e.g. two categories share a color). Wrapping back in pd.Categorical ensures
+        # downstream consumers always receive a Categorical for categorical data.
+        color_vector = pd.Categorical(color_source_vector.map(color_mapping, na_action="ignore"))
 
         return color_source_vector, color_vector, True
 
@@ -1146,7 +1149,7 @@ def _map_color_seg(
 ) -> ArrayLike:
     cell_id = np.array(cell_id)
 
-    if pd.api.types.is_categorical_dtype(color_vector.dtype):
+    if isinstance(color_vector.dtype, pd.CategoricalDtype):
         # Case A: users wants to plot a categorical column
         if np.any(color_source_vector.isna()):
             cell_id[color_source_vector.isna()] = 0