Update app.py

app.py

@@ -39,40 +39,39 @@ st.markdown("""
 Just enter the store details below, and our AI model will predict the weekly sales! 💰
 """)
 
-with st.form("prediction_form"):
-    Store = st.number_input("Store ID", min_value=1, max_value=100, value=1)
-    Holiday_Flag = st.selectbox("Is it a Holiday?", [0, 1])
-    Temperature = st.number_input("Temperature (°F)", value=75.0)
-    Fuel_Price = st.number_input("Fuel Price ($)", value=2.5)
-    CPI = st.number_input("CPI", value=211.0)
-    Unemployment = st.number_input("Unemployment Rate (%)", value=7.5)
-    month = st.selectbox("Month", list(range(1, 13)))
-
-    submitted = st.form_submit_button("Predict")
-
-if submitted:
+st.title("🛒 Walmart Sales Prediction")
+st.write("Enter the input features below to predict the weekly sales.")
+
+# Store input (float64)
+store = st.number_input("Enter Store ID (1-50)", min_value=1.0, max_value=50.0, step=1.0, format="%.1f")
+
+# Holiday_Flag input (object, but should be categorical)
+holiday_flag = st.selectbox("Is it a Holiday?", [0,1])
+
+# Temperature input (float64)
+temperature = st.number_input("Enter Temperature (°C)", value=20.0, format="%.2f")
+
+# Fuel Price input (float64)
+fuel_price = st.number_input("Enter Fuel Price", value=3.5, format="%.3f")
+
+# CPI input (float64)
+cpi = st.number_input("Enter CPI", value=200.0, format="%.6f")
+
+# Unemployment input (float64)
+unemployment = st.number_input("Enter Unemployment Rate", value=5.0, format="%.3f")
+
+# Month input (float64)
+month = st.number_input("Enter Month (1-12)", min_value=1.0, max_value=12.0, step=1.0, format="%.1f")
+
+
+# Prediction button
+if st.button("Predict Sales"):
+    #input_features = [[store, holiday_flag, temperature, fuel_price, cpi, unemployment,month]]
+    
     try:
-        # Construct input data
-        input_data = pd.DataFrame([[
-            Store, Holiday_Flag, Temperature, Fuel_Price, CPI, Unemployment, month
-        ]], columns=['Store', 'Holiday_Flag', 'Temperature', 'Fuel_Price', 'CPI', 'Unemployment', 'month'])
-
-        # Ensure proper data types
-        input_data = input_data.astype({
-            'Store': int,
-            'Holiday_Flag': int,
-            'Temperature': float,
-            'Fuel_Price': float,
-            'CPI': float,
-            'Unemployment': float,
-            'month': int
-        })
-
-        # Prediction
-        prediction = model.predict(input_data)[0]
-        st.success(f"🎯 Predicted Weekly Sales: **${prediction:,.2f}**")
-
-    except ValueError as ve:
-        st.error(f"ValueError: {ve}")
+        prediction = model.predict([[store, holiday_flag, temperature, fuel_price, cpi, unemployment, month]])
+        prediction
+        
+        st.success(f"Predicted Weekly Sales: ${prediction[0]:,.2f}")
     except Exception as e:
-        st.error(f"An error occurred: {e}")
+        st.error(f"Error during prediction: {e}")