update app.py

app.py

@@ -13,6 +13,7 @@ from utils import *
 
 ########## Title for the Web App ##########
 st.title("Property Price Predictor")
+st.markdown('_Creator: GOH Hong Aik [[LinkedIn]](https://www.linkedin.com/in/hongaikgoh/)_')
 st.markdown("""This app predicts your house price based on a few indicators, and displays amenities within 2 km. Please note the following:
 - Only property types allowed are HDB, Condominium, Executive Condominium and Apartment.
 - Model was trained on **resale, leasehold** properties from 2021 onwards to account for COVID-19 effects; predictions for new and/or freehold properties will not be accurate.
@@ -130,16 +131,16 @@ with st.form("inputs"):
         prediction_price = round(prediction_psf * input_floor_area_sqft)
 
         if latlong_geo_nolatlong_encoded['propertyType_Apartment'].item() == 1:
-            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval at ${:,} - ${:,}.".format(
                 prediction_price, int(prediction_price - 2*sd_hdb*input_floor_area_sqft), int(prediction_price + 2*sd_hdb*input_floor_area_sqft)))
         elif latlong_geo_nolatlong_encoded['propertyType_Condominium'].item() == 1:
-            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval at ${:,} - ${:,}.".format(
                 prediction_price, int(prediction_price - 2*sd_condo*input_floor_area_sqft), int(prediction_price + 2*sd_condo*input_floor_area_sqft)))
         elif latlong_geo_nolatlong_encoded['propertyType_Executive_Condominium'].item() == 1:
-            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being ${:,} - ${:,}.".format(
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval at ${:,} - ${:,}.".format(
                 prediction_price, int(prediction_price - 2*sd_ec*input_floor_area_sqft), int(prediction_price + 2*sd_ec*input_floor_area_sqft)))
         elif latlong_geo_nolatlong_encoded['propertyType_HDB'].item() == 1:
-            st.success("The predicted price of your property is ${:,}, with 95% confidence interval being {:,} - {:,}.".format(
+            st.success("The predicted price of your property is ${:,}, with 95% confidence interval at ${:,} - ${:,}.".format(
                 prediction_price, int(prediction_price - 2*sd_hdb*input_floor_area_sqft), int(prediction_price + 2*sd_hdb*input_floor_area_sqft)))
 
         # between Jan 2017 and Oct 2022, propertyType, age, floor area range, storey