Update app.py

app.py

@@ -12,7 +12,7 @@ data = pd.DataFrame(np.zeros((1,60)),columns=predictor.X_test.columns, index=[0]
 
 st.title("*The Ames, Iowa Housing Price Predictor*")
 st.header("Description:")
-st.text("This is a showcase of the regression model, which has been trained using LightGBM and Optuna for hyperparameter tuning on the Ames, Iowa Housing Dataset. On the side are the top 20 features which this model deems the most relevant towards housing prices. Please try from a range of different inputs!")
+st.subheader("This is a showcase of the regression model, which has been trained using LightGBM and Optuna for hyperparameter tuning on the Ames, Iowa Housing Dataset. On the side are the top 20 features which this model deems the most relevant towards housing prices. Please try from a range of different inputs!")
 
 OverallQual = st.sidebar.slider("Overall Quality", 1, 5)
 with st.sidebar:
@@ -45,6 +45,8 @@ with st.sidebar:
 if st.button("Calculate Your House Price!"):
     results = predictor.make_a_prediction(data)
     st.write('{0:.2f}'.format(results[0]))
+    c = st.container()
+    c.write(predictor.create_shap_graphs(data))