update app.py

app.py

@@ -368,19 +368,24 @@ if st.session_state.results:
     # Convert the results to a DataFrame for better visualization
     result_df = pd.DataFrame(st.session_state.results)
 
-    # Show the results in a table format
-    st.write("Processed Results Table:")
-    st.dataframe(result_df[['Location Name', 'Latitude', 'Longitude', 'Calculated Value']])
+    # If the shape type is 'Point', include 'Latitude' and 'Longitude'
+    if shape_type.lower() == 'point':
+        # Show the results in a table format with Latitude and Longitude
+        st.write("Processed Results Table (Points):")
+        st.dataframe(result_df[['Location Name', 'Latitude', 'Longitude', 'Calculated Value']])
+    else:
+        # For polygons, we only show the Location Name and Calculated Value
+        st.write("Processed Results Table (Polygons):")
+        st.dataframe(result_df[['Location Name', 'Calculated Value']])
 
     # Generate the dynamic filename
     filename = f"{main_selection}_{sub_selection}_{start_date.strftime('%Y/%m/%d')}_{end_date.strftime('%Y/%m/%d')}_{shape_type}.csv"
 
     # Convert results to DataFrame for download
-    if st.session_state.results:
-        result_df = pd.DataFrame(st.session_state.results)
-        st.download_button(
-            label="Download results as CSV",
-            data=result_df.to_csv(index=False).encode('utf-8'),
-            file_name=filename,
-            mime='text/csv'
-        )
+    st.download_button(
+        label="Download results as CSV",
+        data=result_df.to_csv(index=False).encode('utf-8'),
+        file_name=filename,
+        mime='text/csv'
+    )
+