added O/U, added some sorting and replacing of null values

app.py

@@ -28,7 +28,10 @@ def init_baselines():
     collection = dfs_db["NCAAF_GameModel"] 
     cursor = collection.find()
     raw_display = pd.DataFrame(list(cursor))
-    game_model = raw_display[['Team', 'Opp', 'Win%', 'Vegas', 'Win% Diff', 'Win Line', 'Vegas Line', 'Line Diff', 'PD Spread', 'Vegas Spread', 'Spread Diff']]
+    game_model = raw_display[['Team', 'Opp', 'Win%', 'Vegas', 'Win% Diff', 'Win Line', 'Vegas Line', 'Line Diff', 'PD Spread', 'Vegas Spread', 'Spread Diff', 'O/U']]
+    game_model = game_model.replace('', np.nan)
+    game_model = game_model.sort_values(by='O/U', ascending=False)
+    game_model.loc[:, ~game_model.columns.isin(['Team', 'Opp'])] = game_model.loc[:, ~game_model.columns.isin(['Team', 'Opp'])].apply(pd.to_numeric)
 
     collection = props_db["NCAAF_Props"] 
     cursor = collection.find()
@@ -69,6 +72,8 @@ prop_table_options = ['NCAAF_GAME_PLAYER_PASSING_YARDS', 'NCAAF_GAME_PLAYER_RUSH
 prop_format = {'L3 Success': '{:.2%}', 'L6_Success': '{:.2%}', 'L10_success': '{:.2%}', 'Trending Over': '{:.2%}', 'Trending Under': '{:.2%}',
                'Implied Over': '{:.2%}', 'Implied Under': '{:.2%}', 'Over Edge': '{:.2%}', 'Under Edge': '{:.2%}'}
 
+game_model, market_props = init_baselines()
+
 tab1, tab2 = st.tabs(["Game Model", "Prop Market"])
 
 with tab1: