cleaned up the stat specific sim

app.py

@@ -408,35 +408,39 @@ with tab6:
                     with df_hold_container.container():
                         if prop_type_var == 'All Props':
                             if game_select_var == 'Aggregate':
+                                prop_df_raw = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                 sim_vars = ['NFL_GAME_PLAYER_PASSING_YARDS', 'NFL_GAME_PLAYER_RUSHING_YARDS', 'NFL_GAME_PLAYER_PASSING_ATTEMPTS', 'NFL_GAME_PLAYER_PASSING_TOUCHDOWNS', 'NFL_GAME_PLAYER_RUSHING_ATTEMPTS',
                                             'NFL_GAME_PLAYER_RECEIVING_RECEPTIONS', 'NFL_GAME_PLAYER_RECEIVING_YARDS', 'NFL_GAME_PLAYER_RECEIVING_TOUCHDOWNS']
                             elif game_select_var == 'Pick6':
+                                prop_df_raw = pick_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                 sim_vars = ['Rush + Rec Yards', 'Rush + Rec TDs', 'Passing Yards', 'Passing Attempts', 'Passing TDs', 'Rushing Attempts', 'Rushing Yards', 'Receptions', 'Receiving Yards', 'Receiving TDs']
+                            
+                            player_df = overall_stats.copy()
+                            
                             for prop in sim_vars:
-                                
-                                if game_select_var == 'Aggregate':
-                                    prop_df_raw = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
-                                elif game_select_var == 'Pick6':
-                                    prop_df_raw = pick_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
-                                
+                                    
                                 for books in book_selections:
                                     prop_df = prop_df_raw[prop_df_raw['book'] == books]
                                     prop_df = prop_df[prop_df['prop_type'] == prop]
                                     prop_df = prop_df[~((prop_df['over_prop'] < 15) & (prop_df['prop_type'] == 'NFL_GAME_PLAYER_RUSHING_YARDS'))]
                                     prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
                                     prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
-                                    prop_df = prop_df.drop_duplicates(subset=['Player'])
-                                    prop_df = prop_df[prop_df['Prop'] != 0]
                                     prop_df['Over'] = 1 / prop_df['over_line']
                                     prop_df['Under'] = 1 / prop_df['under_line']
-                                    df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
-                                    df = df.reset_index(drop=True)
 
-                                    prop_dict = dict(zip(df.Player, df.Prop))
-                                    book_dict = dict(zip(df.Player, df.book))
-                                    over_dict = dict(zip(df.Player, df.Over))
+                                    prop_dict = dict(zip(prop_df.Player, prop_df.Prop))
+                                    prop_type_dict = dict(zip(prop_df.Player, prop_df.prop_type))
+                                    book_dict = dict(zip(prop_df.Player, prop_df.book))
+                                    over_dict = dict(zip(prop_df.Player, prop_df.Over))
+                                    under_dict = dict(zip(prop_df.Player, prop_df.Under))
+
+                                    player_df['book'] = player_df['Player'].map(book_dict)
+                                    player_df['Prop'] = player_df['Player'].map(prop_dict)
+                                    player_df['prop_type'] = player_df['Player'].map(prop_type_dict)
+
+                                    df = player_df.reset_index(drop=True)
+
                                     team_dict = dict(zip(df.Player, df.Team))
-                                    under_dict = dict(zip(df.Player, df.Under))
                                     
                                     total_sims = 1000
             
@@ -521,9 +525,12 @@ with tab6:
                                     sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                                     
                                     final_outcomes = sim_all_hold
-                                    st.write(f'finished {prop}')
+                                    st.write(f'finished {prop} for {books}')
                                 
                         elif prop_type_var != 'All Props':
+
+                            player_df = overall_stats.copy()
+
                             if game_select_var == 'Aggregate':
                                 prop_df_raw = prop_frame[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                             elif game_select_var == 'Pick6':
@@ -571,18 +578,22 @@ with tab6:
 
                                 prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line']]
                                 prop_df = prop_df.rename(columns={"over_prop": "Prop"})
-                                prop_df = prop_df[prop_df['Prop'] != 0]
-                                prop_df = prop_df.drop_duplicates(subset=['Player'])
                                 prop_df['Over'] = 1 / prop_df['over_line']
                                 prop_df['Under'] = 1 / prop_df['under_line']
-                                df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
-                                df = df.reset_index(drop=True)
-                                
-                                prop_dict = dict(zip(df.Player, df.Prop))
-                                book_dict = dict(zip(df.Player, df.book))
-                                over_dict = dict(zip(df.Player, df.Over))
+
+                                prop_dict = dict(zip(prop_df.Player, prop_df.Prop))
+                                prop_type_dict = dict(zip(prop_df.Player, prop_df.prop_type))
+                                book_dict = dict(zip(prop_df.Player, prop_df.book))
+                                over_dict = dict(zip(prop_df.Player, prop_df.Over))
+                                under_dict = dict(zip(prop_df.Player, prop_df.Under))
+
+                                player_df['book'] = player_df['Player'].map(book_dict)
+                                player_df['Prop'] = player_df['Player'].map(prop_dict)
+                                player_df['prop_type'] = player_df['Player'].map(prop_type_dict)
+
+                                df = player_df.reset_index(drop=True)
+
                                 team_dict = dict(zip(df.Player, df.Team))
-                                under_dict = dict(zip(df.Player, df.Under))
                                 
                                 total_sims = 1000
         
@@ -667,7 +678,7 @@ with tab6:
                                 sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                                 
                                 final_outcomes = sim_all_hold
-                                st.write(f'finished {prop_type_var}')
+                                st.write(f'finished {prop_type_var} for {books}')
                         
                         final_outcomes = final_outcomes.dropna()
                         if game_select_var == 'Pick6':