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app.py

@@ -9,17 +9,17 @@ st.title("Store Sales Prediction")
 st.subheader("Online Prediction")
 
 # Collect user input for property features
+Product_Weight = st.number_input("Product_Weight", min_value=0.00, max_value=100.00, step=0.01, value=0.0)
 Product_Sugar_Content = st.selectbox("Product_Sugar_Content" , ["Low Sugar", "Regular", "No Sugar"])
+Product_Allocated_Area = st.number_input("Product_Allocated_Area", min_value=0.000, max_value=1.000, step=0.001, value=0.000)
 Product_Type = st.selectbox("Product_Type" , ["Frozen Foods","Dairy","Canned","Baking Goods","Health and Hygiene","Snack Foods","Meat","Household","Hard Drinks","Fruits and Vegetables","Breads","Soft Drinks","Breakfast","Others","Starchy Foods","Seafood"
 ])
+Product_MRP = st.number_input("Product_MRP", min_value=0.0, step=0.01, value=0.0)
 Store_Id = st.selectbox("Store_Id" , ["OUT001","OUT002","OUT003","OUT004"])
+Store_Establishment_Year = st.number_input("Store_Establishment_Year", min_value=1800, max_value=3000, step=1, value=1900)
 Store_Size = st.selectbox("Store_Size" , ["Small","Medium","High"])
 Store_Location_City_Type = st.selectbox("Store_Location_City_Type" , ["Tier 1","Tier 2","Tier 3"])
 Store_Type = st.selectbox("Store_Type" , ["Supermarket Type1","Supermarket Type2","Departmental Store","Food Mart"])
-Product_Weight = st.number_input("Product_Weight", min_value=0.00, max_value=100.00, step=0.01, value=0.0)
-Product_Allocated_Area = st.number_input("Product_Allocated_Area", min_value=0.000, max_value=1.000, step=0.001, value=0.000)
-Product_MRP = st.number_input("Product_MRP", min_value=0.0, step=0.01, value=0.0)
-Store_Establishment_Year = st.number_input("Store_Establishment_Year", min_value=1800, max_value=3000, step=1, value=1900)
 
 
 # Convert user input into a DataFrame