Update app.py

app.py

@@ -17,30 +17,30 @@ product_types = [
 # Collect user input for property features
 Product_Id = st.text_input("Id")
 Product_Weight = st.number_input("Weight of Product", min_value=1.00)
-Product_MRP = st.number_input("MRP of Product", min_value=1.00)
-Product_Allocated_Area = st.number_input("Allocated_Area", max_value=1.000)
 Product_Sugar_Content = st.selectbox("Sugar Content", ["Low Sugar", "Regular", "No Sugar"])
+Product_Allocated_Area = st.number_input("Allocated_Area", max_value=1.000)
 Product_Type = st.selectbox("Type", product_types)
+Product_MRP = st.number_input("MRP of Product", min_value=1.00)
+Store_Id = st.text_input("Store Id")
+Store_Establishment_Year = st.number_input("Store Establishment Year", min_value=1950, max_value=2025, step=1)
 Store_Size = st.selectbox("Store Size", ["Medium", "High", "Small"])
 Store_Location_City_Type = st.selectbox("Store Location Type", ["Tier 1", "Tier 2", "Tier 3"])
 Store_Type = st.text_input("Store_Type")
-Store_Id = st.text_input("Store Id")
-Store_Establishment_Year = st.number_input("Store Establishment Year", min_value=1950, max_value=2025, step=1)
 
 
 # Convert user input into a DataFrame
 input_data = pd.DataFrame([{
     'Product_Id': Product_Id,
     'Product_Weight': Product_Weight,
-    'Product_MRP': Product_MRP,
-    'Product_Allocated_Area': Product_Allocated_Area,
     'Product_Sugar_Content': Product_Sugar_Content,
+    'Product_Allocated_Area': Product_Allocated_Area,
     'Product_Type': Product_Type,
+    'Product_MRP': Product_MRP,
+    'Store_Id': Store_Id,
+    'Store_Establishment_Year': Store_Establishment_Year,
     'Store_Size': Store_Size,
     'Store_Location_City_Type': Store_Location_City_Type,
-    'Store_Type': Store_Type,
-    'Store_Id': Store_Id,
-    'Store_Establishment_Year': Store_Establishment_Year
+    'Store_Type': Store_Type
 }])
 
 # Make prediction when the "Predict" button is clicked
@@ -50,4 +50,4 @@ if st.button("Predict"):
         prediction = response.json()['Predicted Price']
         st.success(f"Predicted Price: {prediction}")
     else:
-        st.error("Error making prediction.")
+        st.error("Error making prediction.")