chore: added some emojis and improve messaging

app.py

@@ -40,15 +40,15 @@ with col1:
             df_base["len_pupil_dilation"] = df_base.pupil_dilation.map(lambda l: len(l))
             df_base["len_baseline"] = df_base.baseline.map(lambda l: len(l))
             st.info(f"number of files: {len(file_names)}")
-            st.markdown("Your original data")
+            st.markdown("Your original data with some extra information about the length of the time-series fields")
             st.dataframe(df_base)
     else:
-        st.caption("Upload your data from the sidebar to start :sunglasses:")
+        st.caption("Upload your data using the sidebar to start :sunglasses:")
 
 with col2:
     if not df_base.empty:
         st.markdown("**Cleaning actions**")
-        detect_blinking = st.button("Detect blinking ('0.0' values)")
+        detect_blinking = st.button("I want to clean my data 🤗")
         number_of_blinks = 0
         if detect_blinking:
             # Initialization of session_state
@@ -69,7 +69,7 @@ with col2:
                         
         if "blinks" in st.session_state.keys():
             st.info(f"blinking values (0.0) were found in {number_of_blinks} time-steps in all your data")
-            remove_blinking  = st.button("Remove blinking")
+            remove_blinking  = st.button("Remove blinking 🧹")
             # df in column 2
             if remove_blinking:
                 df_right = st.session_state.df.copy(deep=True)
@@ -78,14 +78,14 @@ with col2:
                 st.session_state['df'] = df_right.copy(deep=True)
                 st.success("Blinking values have been removed!")
         elif detect_blinking and not number_of_blinks:
-            st.caption("No blinking values were found in your data!")
+            st.caption("No blinking values were found in your data! ")
 
 with col2:
     if 'df' in list(st.session_state.keys()):
         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?")
-            option = st.multiselect('Select a feature to merge', [k for k in list(df_right.keys()) if k != 'baseline'], [[k for k in list(df_right.keys()) if k != 'baseline'][-4]])
+            option = st.multiselect('Select a feature to create relative calculated feature ➕', [k for k in list(df_right.keys()) if k != 'baseline'], [[k for k in list(df_right.keys()) if k != 'baseline'][-4]])
             relative_key = f"relative_{option[0]}"
             add_relative = st.button(f"Add {relative_key}")
             if add_relative:
@@ -95,7 +95,7 @@ with col2:
                 st.dataframe(df_right)
                 csv = convert_df(df_right)
                 downl = st.download_button(
-                   "Press to Download CSV",
+                   "Download CSV 💾",
                    csv,
                    "file.csv",
                    "text/csv",