Update app.py

app.py

@@ -77,7 +77,7 @@ prop_table_options = ['NFL_GAME_PLAYER_RUSHING_YARDS', 'NFL_GAME_PLAYER_RECEIVIN
 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%}'}
 all_sim_vars = ['NFL_GAME_PLAYER_PASSING_YARDS', 'NFL_GAME_PLAYER_RUSHING_YARDS', 'NFL_GAME_PLAYER_RECEIVING_YARDS', 'NFL_GAME_PLAYER_RECEIVING_RECEPTIONS', 'NFL_GAME_PLAYER_RUSHING_ATTEMPTS', 'NFL_GAME_PLAYER_PASSING_ATTEMPTS']
-sim_all_hold = pd.DataFrame(columns=['Player', 'Team', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge'])
+sim_all_hold = pd.DataFrame(columns=['Player', 'Team', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge'])
 
 tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs(["Game Betting Model", "QB Projections", "RB/WR/TE Projections", "Player Prop Trends", "Player Prop Simulations", "Stat Specific Simulations"])
 
@@ -631,7 +631,7 @@ with tab6:
                                 
                                 final_outcomes = sim_all_hold
                         
-                        # final_outcomes = final_outcomes.dropna()
+                        final_outcomes = final_outcomes.dropna()
                         final_outcomes = final_outcomes.sort_values(by='Edge', ascending=False)
 
                         with df_hold_container: