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app.py

@@ -9,15 +9,15 @@ st.title("SuperKart Product Sales Prediction")
 st.subheader("Online Prediction")
 
 # Collect user input for product features
-Product_Allocated_Area = st.number_input("Product Allocated Area", min_value=0.0, max_value=0.3)
+Product_Allocated_Area = st.number_input("Product Allocated Area", min_value=0.0, max_value=0.3,format="%.3f")
 Product_Group = st.selectbox("Product Group", ["Packaged/Processed Foods", "Perishable Foods", "Non-Food/Household"])
-Product_MRP = st.number_input("Product MRP", min_value=10.0, max_value=300.0)
+Product_MRP = st.number_input("Product MRP", min_value=10.0, max_value=300.0,format="%.2f")
 Store_Id = st.selectbox("Store ID", ["OUT004","OUT003","OUT001","OUT002"])
-Store_Age = st.number_input("Store Age", min_value=1.0, max_value=38.0)
+Store_Age = st.number_input("Store Age", min_value=1, max_value=38,format="%d")
 Store_Size = st.selectbox("Store Size", ["Medium","High","Small"])
 Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier 1","Tier 2","Tier 3"])
 Store_Type = st.selectbox("Store Type", ["Supermarket Type2","Departmental Store","Supermarket Type1","Food Mart"])
-Product_Weight = st.number_input("Product Weight", min_value=4.0, max_value=22.0)
+Product_Weight = st.number_input("Product Weight", min_value=4.0, max_value=22.0,format="%.2f")
 Product_Sugar_Content = st.selectbox("Product Sugar Content", ["Low Sugar","Regular","No Sugar"])
 
 # Convert user input into a DataFrame