diff --git a/doc/_docstrings/catplot.ipynb b/doc/_docstrings/catplot.ipynb
index 6e3ee7d06b..fcfff16beb 100644
--- a/doc/_docstrings/catplot.ipynb
+++ b/doc/_docstrings/catplot.ipynb
@@ -87,7 +87,7 @@
    "source": [
     "sns.catplot(\n",
     "    data=df, x=\"age\", y=\"class\", hue=\"sex\",\n",
-    "    kind=\"violin\", bw=.25, cut=0, split=True,\n",
+    "    kind=\"violin\", bw_adjust=.5, cut=0, split=True,\n",
     ")"
    ]
   },
diff --git a/seaborn/_core/groupby.py b/seaborn/_core/groupby.py
index cc41566cde..cb63c670d2 100644
--- a/seaborn/_core/groupby.py
+++ b/seaborn/_core/groupby.py
@@ -93,7 +93,7 @@ def agg(self, data: DataFrame, *args, **kwargs) -> DataFrame:
 
         res = (
             data
-            .groupby(grouper, sort=False, observed=True)
+            .groupby(grouper, sort=False, observed=False)
             .agg(*args, **kwargs)
             .reindex(groups)
             .reset_index()
@@ -113,7 +113,7 @@ def apply(
             return self._reorder_columns(func(data, *args, **kwargs), data)
 
         parts = {}
-        for key, part_df in data.groupby(grouper, sort=False):
+        for key, part_df in data.groupby(grouper, sort=False, observed=False):
             parts[key] = func(part_df, *args, **kwargs)
         stack = []
         for key in groups:
diff --git a/seaborn/axisgrid.py b/seaborn/axisgrid.py
index 2e35304940..17d333bc89 100644
--- a/seaborn/axisgrid.py
+++ b/seaborn/axisgrid.py
@@ -1522,7 +1522,7 @@ def _map_diag_iter_hue(self, func, **kwargs):
         fixed_color = kwargs.pop("color", None)
 
         for var, ax in zip(self.diag_vars, self.diag_axes):
-            hue_grouped = self.data[var].groupby(self.hue_vals)
+            hue_grouped = self.data[var].groupby(self.hue_vals, observed=True)
 
             plot_kwargs = kwargs.copy()
             if str(func.__module__).startswith("seaborn"):
@@ -1629,7 +1629,7 @@ def _plot_bivariate_iter_hue(self, x_var, y_var, ax, func, **kwargs):
         else:
             axes_vars = [x_var, y_var]
 
-        hue_grouped = self.data.groupby(self.hue_vals)
+        hue_grouped = self.data.groupby(self.hue_vals, observed=True)
         for k, label_k in enumerate(self._hue_order):
 
             kws = kwargs.copy()