feat: updated app.py

app.py

@@ -303,9 +303,17 @@ elif page == "Customer Analysis":
                     
                     # Prepare data for prediction
                     X_predict = customer_data[features]
+
+                    # Convert categorical features to 'category' dtype
+                    categorical_features = ['mes', 'marca_id_encoded', 'cluster_id']
+                    for feature in categorical_features:
+                        X_predict[feature] = X_predict[feature].astype('category')
+                    
                     st.write("### Features for Prediction:")
                     st.write(X_predict.head())
                     st.write(f"Shape: {X_predict.shape}")
+                    st.write("Data types:")
+                    st.write(X_predict.dtypes)
                     
                     # Make Prediction for the selected customer
                     y_pred = gbm.predict(X_predict, num_iteration=gbm.best_iteration)