chore: better flow

app.py

@@ -84,11 +84,12 @@ with col1:
                 df_right.baseline = df_right.baseline.map(lambda ser: [f for f in ser if f != 0.0])
                 st.session_state['df'] = df_right.copy(deep=True)
                 st.success("Blinking values have been removed!")
+                st.session_state.df_base = df_right
         elif detect_blinking and not number_of_blinks:
             st.caption("No blinking values were found in your data! ")
 
 # Add calculated fields
-if 'df' in list(st.session_state.keys()):
+if 'df' in st.session_state or 'df_right' in st.session_state:
     df_right = st.session_state.df.copy(deep=True)
     if "baseline" in list(df_right.keys()):
         st.markdown(f"A **baseline** feature has been found on your data, do you want to merge it with any of the other features in a new calculated field?")
@@ -98,10 +99,11 @@ if 'df' in list(st.session_state.keys()):
         if add_relative:
             baseline_mean = [sum(s)/len(s) for s in df_right['baseline']]
             df_right[relative_key] = [[field_value - baseline_mean[i] for field_value in df_right[option[0]][i]] for i in range(len(df_right))]
-            st.markdown("After adding calculated fields")
+            st.markdown("After adding calculated fields and removing blinking values (when applied)")
             st.dataframe(df_right)
             csv = convert_df(df_right)
-
+            if 'df_right' not in st.session_state:
+                st.session_state['df_right'] = df_right
             # Save transformations to disk
             downl = st.download_button("Download CSV 💾", csv, "file.csv", "text/csv", key='download-csv')
             if downl: