Refined Bet Sheet display by removing unnecessary columns, adding sorting by Edge, and implementing prop type filtering for enhanced user experience.

src/streamlit_app.py

@@ -153,11 +153,12 @@ def init_baselines():
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display.replace('', np.nan, inplace=True)
-    raw_display = raw_display[['Name', 'OddsType', 'PropType', 'No Vig', 'Team', 'Projection', 'Edge']]
-    raw_display = raw_display.rename(columns={"Name": "Player", "OddsType": "book", "PropType": "prop_type"})
+    raw_display = raw_display[['Name', 'PropType', 'No Vig', 'Projection', 'Edge']]
+    raw_display = raw_display.rename(columns={"Name": "Player", "PropType": "prop_type"})
     bet_sheet = raw_display.dropna(subset='Player')
     bet_sheet = bet_sheet.reset_index(drop=True)
     bet_sheet = bet_sheet.drop_duplicates(subset=['Player', 'prop_type'], keep='first')
+    bet_sheet = bet_sheet.sort_values(by='Edge', ascending=False)
 
     collection = db["Pick6_Trends"] 
     cursor = collection.find()
@@ -229,8 +230,10 @@ if selected_tab == 'Bet Sheet':
                 st.cache_data.clear()
                 game_model, raw_baselines, player_stats, prop_frame, bet_sheet, pick_frame, market_props, timestamp = init_baselines()
                 t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-        st.dataframe(bet_sheet.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(bet_format, precision=2), use_container_width = True)
-        st.download_button(
+        prop_selection = st.multiselect('Select prop type to view', default = bet_sheet['prop_type'].unique(), options = bet_sheet['prop_type'].unique(), key='prop_selection')
+    bet_sheet = bet_sheet[bet_sheet['prop_type'].isin(prop_selection)]
+    st.dataframe(bet_sheet.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(bet_format, precision=2), use_container_width = True)
+    st.download_button(
         label="Export Bet Sheet",
         data=convert_df_to_csv(bet_sheet),
         file_name='NBA_bet_sheet_export.csv',