diff --git a/optuna/visualization/matplotlib/_contour.py b/optuna/visualization/matplotlib/_contour.py
index 359c56b9cba..6a4737d9db6 100644
--- a/optuna/visualization/matplotlib/_contour.py
+++ b/optuna/visualization/matplotlib/_contour.py
@@ -190,19 +190,7 @@ def _calculate_axis_data(
     return ci, cat_param_labels, cat_param_pos, list(returned_values)
 
 
-def _calculate_griddata(
-    info: _SubContourInfo,
-) -> tuple[
-    np.ndarray,
-    np.ndarray,
-    np.ndarray,
-    list[int],
-    list[str],
-    list[int],
-    list[str],
-    _PlotValues,
-    _PlotValues,
-]:
+def _calculate_griddata(info: _SubContourInfo) -> tuple[np.ndarray, _PlotValues, _PlotValues]:
     xaxis = info.xaxis
     yaxis = info.yaxis
     z_values_dict = info.z_values
@@ -220,17 +208,7 @@ def _calculate_griddata(
 
     # Return empty values when x or y has no value.
     if len(x_values) == 0 or len(y_values) == 0:
-        return (
-            np.array([]),
-            np.array([]),
-            np.array([]),
-            [],
-            [],
-            [],
-            [],
-            _PlotValues([], []),
-            _PlotValues([], []),
-        )
+        return np.array([]), _PlotValues([], []), _PlotValues([], [])
 
     xi, cat_param_labels_x, cat_param_pos_x, transformed_x_values = _calculate_axis_data(
         xaxis,
@@ -261,90 +239,64 @@ def _calculate_griddata(
             infeasible.x.append(x_value)
             infeasible.y.append(y_value)
 
-    return (
-        xi,
-        yi,
-        zi,
-        cat_param_pos_x,
-        cat_param_labels_x,
-        cat_param_pos_y,
-        cat_param_labels_y,
-        feasible,
-        infeasible,
-    )
+    return zi, feasible, infeasible
 
 
 def _generate_contour_subplot(
     info: _SubContourInfo, ax: "Axes", cmap: "Colormap"
 ) -> "ContourSet" | None:
+    ax.label_outer()
+
     if len(info.xaxis.indices) < 2 or len(info.yaxis.indices) < 2:
-        ax.label_outer()
         return None
 
     ax.set(xlabel=info.xaxis.name, ylabel=info.yaxis.name)
     ax.set_xlim(info.xaxis.range[0], info.xaxis.range[1])
     ax.set_ylim(info.yaxis.range[0], info.yaxis.range[1])
     x_values, y_values = _filter_missing_values(info.xaxis, info.yaxis)
+    xi, x_cat_param_label, x_cat_param_pos, _ = _calculate_axis_data(info.xaxis, x_values)
+    yi, y_cat_param_label, y_cat_param_pos, _ = _calculate_axis_data(info.yaxis, y_values)
     if info.xaxis.is_cat:
-        _, x_cat_param_label, x_cat_param_pos, _ = _calculate_axis_data(info.xaxis, x_values)
         ax.set_xticks(x_cat_param_pos)
         ax.set_xticklabels(x_cat_param_label)
     else:
         ax.set_xscale("log" if info.xaxis.is_log else "linear")
     if info.yaxis.is_cat:
-        _, y_cat_param_label, y_cat_param_pos, _ = _calculate_axis_data(info.yaxis, y_values)
         ax.set_yticks(y_cat_param_pos)
         ax.set_yticklabels(y_cat_param_label)
     else:
         ax.set_yscale("log" if info.yaxis.is_log else "linear")
 
     if info.xaxis.name == info.yaxis.name:
-        ax.label_outer()
         return None
 
-    (
-        xi,
-        yi,
-        zi,
-        x_cat_param_pos,
-        x_cat_param_label,
-        y_cat_param_pos,
-        y_cat_param_label,
-        feasible_plot_values,
-        infeasible_plot_values,
-    ) = _calculate_griddata(info)
+    zi, feasible_plot_values, infeasible_plot_values = _calculate_griddata(info)
     cs = None
     if len(zi) > 0:
-        if info.xaxis.is_log:
-            ax.set_xscale("log")
-        if info.yaxis.is_log:
-            ax.set_yscale("log")
-        if info.xaxis.name != info.yaxis.name:
-            # Contour the gridded data.
-            ax.contour(xi, yi, zi, 15, linewidths=0.5, colors="k")
-            cs = ax.contourf(xi, yi, zi, 15, cmap=cmap.reversed())
-            assert isinstance(cs, ContourSet)
-            # Plot data points.
-            ax.scatter(
-                feasible_plot_values.x,
-                feasible_plot_values.y,
-                marker="o",
-                c="black",
-                s=20,
-                edgecolors="grey",
-                linewidth=2.0,
-            )
-            ax.scatter(
-                infeasible_plot_values.x,
-                infeasible_plot_values.y,
-                marker="o",
-                c="#cccccc",
-                s=20,
-                edgecolors="grey",
-                linewidth=2.0,
-            )
+        # Contour the gridded data.
+        ax.contour(xi, yi, zi, 15, linewidths=0.5, colors="k")
+        cs = ax.contourf(xi, yi, zi, 15, cmap=cmap.reversed())
+        assert isinstance(cs, ContourSet)
+        # Plot data points.
+        ax.scatter(
+            feasible_plot_values.x,
+            feasible_plot_values.y,
+            marker="o",
+            c="black",
+            s=20,
+            edgecolors="grey",
+            linewidth=2.0,
+        )
+        ax.scatter(
+            infeasible_plot_values.x,
+            infeasible_plot_values.y,
+            marker="o",
+            c="#cccccc",
+            s=20,
+            edgecolors="grey",
+            linewidth=2.0,
+        )
 
-    ax.label_outer()
     return cs