Upload app.py

app.py

@@ -193,15 +193,15 @@ def y1_interpret_xgb(*args):
     df = pd.DataFrame([args], columns=x1.columns)
     df = df.astype({col: "category" for col in categorical_columns1})
     shap_values = y1_explainer_xgb.shap_values(xgb.DMatrix(df, enable_categorical=True))
-    fig_y1 = shap.bar_plot(shap_values[0], max_display = 10, show = False, feature_names = f_names)
+    shap.bar_plot(shap_values[0], max_display = 10, show = False, feature_names = f_names)
     fig_y1 = plt.gcf()
     fig_y1.set_figheight(6)
-    fig_y1.set_figwidth(6)
+    fig_y1.set_figwidth(8)
     ax_y1 = plt.gca()
+    plt.tight_layout()
     plt.xlabel("SHAP value (impact on model output)", fontsize =12, fontweight = 'heavy', labelpad = 8)
     plt.tick_params(axis="y",direction="out", labelsize = 12)
     plt.tick_params(axis="x",direction="out", labelsize = 12)
-    plt.tight_layout()
     wrap_labels(ax_y1, 30)
     ax_y1.figure
     return fig_y1