Update app.py

app.py

@@ -22,7 +22,6 @@ st.sidebar.markdown("**Shop ID**: Unique identifier for a specific shop.")
 st.sidebar.markdown("**Item ID**: Unique identifier for a product.")
 st.sidebar.markdown("**Item Price**: Current price of an item.")
 st.sidebar.markdown("**Item Category ID**: Unique identifier for an item category.")
-st.sidebar.markdown("**Total Sales**: The total daily sales.")
 st.sidebar.markdown("**Day**: Day the product was purchased.")
 st.sidebar.markdown("**Month**: Month the product was purchased.")
 st.sidebar.markdown("**Year**: Year the product was purchased.")
@@ -44,7 +43,7 @@ with col2:
 # Create a button to make a prediction
 if st.button("Predict"):
     # Feature Scaling
-    numerical_cols = ['shop_id', 'item_id', 'item_price', 'item_category_id', 'total_sales', 'day', 'month', 'year', 'day_of_week']
+    numerical_cols = ['shop_id', 'item_id', 'item_price', 'item_category_id', 'day', 'month', 'year']
     scaler = scaler
     input_df = pd.DataFrame(input_data, index=[0])
     input_df_scaled = scaler.fit_transform(input_df[numerical_cols])