Update app.py

app.py

@@ -61,8 +61,7 @@ with tab1:
         @st.cache_data()
         def retrieve_building(feature_group=api_building_newest_fg):
             api_building_newest_fg = feature_group.select(["time", "x", "y", "z"])
-            df_building = api_building_newest_fg.read(read_options={"use_hive": True})
-            df_building = pd.DataFrame(data=df_building)            
+            df_building = api_building_newest_fg.read(read_options={"use_hive": True})           
             return df_building
 
         # Retrieving building data
@@ -72,7 +71,7 @@ with tab1:
         building_most_recent_prediction = building_hist_model.predict(building_most_recent_prediction)
         building_new['prediction'] = building_most_recent_prediction
         building_new = building_new.set_index(['time'])
-        st.dataframe(building_new[['prediction']].tail(5).style.applymap(color_prediction, subset=['prediction']))
+        st.dataframe(building_new[['prediction']].tail(5))
 
     with col2:
         st.markdown("Parking place near bikelane:")
@@ -96,7 +95,6 @@ with tab1:
         def retrieve_bikelane(feature_group=api_bikelane_newest_fg):
             api_bikelane_newest_fg = feature_group.select(["time", "x", "y", "z"])
             df_bikelane = api_bikelane_newest_fg.read(read_options={"use_hive": True})
-            df_bikelane = pd.DataFrame(data=df_bikelane)
             return df_bikelane
 
         # Retrieving building data
@@ -107,7 +105,7 @@ with tab1:
         bikelane_most_recent_prediction = bikelane_hist_model.predict(bikelane_most_recent_prediction)
         bikelane_new['prediction'] = bikelane_most_recent_prediction
         bikelane_new = bikelane_new.set_index(['time'])
-        st.dataframe(bikelane_new[['prediction']].tail(5).style.applymap(color_prediction, subset=['prediction'])) 
+        st.dataframe(bikelane_new[['prediction']].tail(5)) 
 
     if st.button("Update status"):
         st.rerun()