update feature importance explaination

Author: guillaume-vignal

shapash/webapp/utils/callbacks.py

@@ -857,11 +857,7 @@ def adjust_figure_layout(figure: Figure) -> None:
     MyGraph.adjust_graph_static(figure, x_ax="Mean absolute Contribution")
     figure.layout.clickmode = "event+select"
 
-    try:
-        y_values = figure.data[0].y
-        # Convert all y labels to strings before measuring their lengths
-        nb_car = max(len(str(y)) for y in y_values if y is not None)
-        figure.update_layout(yaxis=dict(tickfont={"size": min(round(500 / nb_car), 12)}))
-    except Exception as e:
-        # Optional: log or print an error message for debugging
-        print(f"Warning: Could not adjust figure layout properly: {e}")
+    y_values = figure.data[0].y
+    # Convert all y labels to strings before measuring their lengths
+    nb_car = max(len(str(y)) for y in y_values if y is not None)
+    figure.update_layout(yaxis=dict(tickfont={"size": min(round(500 / nb_car), 12)}))

shapash/webapp/utils/explanations.py

@@ -63,9 +63,12 @@ def __init__(self):
                                 *individual contributions*,
                                 computed on the complete dataset.
                                 You can click on each feature to update
-                                the detailed contribution plot below. \n
-                                In case of grouped the variables (based on the "features_groups"
-                                parameter),
+                                the detailed contribution plot below.\n
+                                When displaying the **Global Feature Importance** chart in full-screen mode,
+                                the visualization also includes the **Local Feature Importance** view,
+                                allowing you to explore both global and local contributions interactively.\n
+
+                                In case of grouped variables (based on the *"features_groups"* parameter),
                                 the group detail is available by clicking on the grouped variable
                                 (displayed in dark orange).
                                 """