Refactor app.py to standardize DataFrame column names for leg_outcomes. Changed 'Imp Over' and 'Imp Under' to 'Over' and 'Under' respectively, enhancing clarity and consistency in prop data handling.

app.py

@@ -60,7 +60,7 @@ prop_format = {'L5 Success': '{:.2%}', 'L10_Success': '{:.2%}', 'L20_success': '
                'Implied Over': '{:.2%}', 'Implied Under': '{:.2%}', 'Over Edge': '{:.2%}', 'Under Edge': '{:.2%}'}
 all_sim_vars = ['NHL_GAME_PLAYER_SHOTS_ON_GOAL', 'NHL_GAME_PLAYER_POINTS', 'NHL_GAME_PLAYER_SHOTS_BLOCKED', 'NHL_GAME_PLAYER_ASSISTS']
 pick6_sim_vars = ['Points', 'Shots on Goal', 'Assists', 'Blocks']
-sim_all_hold = pd.DataFrame(columns=['Player', 'Prop Type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Trending Over', 'Over%', 'Imp Under', 'Trending Under', 'Under%', 'Bet?', 'Edge'])
+sim_all_hold = pd.DataFrame(columns=['Player', 'Prop Type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over', 'Trending Over', 'Over%', 'Imp Under', 'Under', 'Trending Under', 'Under%', 'Bet?', 'Edge'])
 
 @st.cache_resource(ttl=200)
 def pull_baselines():
@@ -311,7 +311,7 @@ with tab3:
                         players_only['Player'] = hold_file[['Player']]
                         players_only['Team'] = players_only['Player'].map(team_dict)
 
-                        leg_outcomes = players_only[['Player', 'Team', 'Book', 'Prop Type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Trending Over', 'Over%', 'Imp Under', 'Trending Under', 'Under%', 'Bet?', 'Edge']]
+                        leg_outcomes = players_only[['Player', 'Team', 'Book', 'Prop Type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over', 'Trending Over', 'Over%', 'Imp Under', 'Under', 'Trending Under', 'Under%', 'Bet?', 'Edge']]
                         sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                     
                         final_outcomes = sim_all_hold
@@ -439,7 +439,7 @@ with tab3:
                     players_only['Player'] = hold_file[['Player']]
                     players_only['Team'] = players_only['Player'].map(team_dict)
 
-                    leg_outcomes = players_only[['Player', 'Team', 'Book', 'Prop', 'Prop Type', 'Mean_Outcome', 'Imp Over', 'Trending Over', 'Over%', 'Imp Under', 'Trending Under', 'Under%', 'Bet?', 'Edge']]
+                    leg_outcomes = players_only[['Player', 'Team', 'Book', 'Prop', 'Prop Type', 'Mean_Outcome', 'Imp Over', 'Over', 'Trending Over', 'Over%', 'Imp Under', 'Under', 'Trending Under', 'Under%', 'Bet?', 'Edge']]
                     sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                     
                     final_outcomes = sim_all_hold