maybe removing .loc helps since it's index based?

app.py

@@ -274,7 +274,7 @@ with tab4:
 
                         df.replace("", 0, inplace=True)
 
-                        player_var = df.loc[df['Player'] == player_check]
+                        player_var = df[df['Player'] == player_check]
                         player_var = player_var.reset_index()
 
                         if prop_type_var == 'points':
@@ -334,8 +334,8 @@ with tab4:
 
                         final_outcomes = players_only[['Player', '10%', 'Mean_Outcome', '90%', 'implied_odds', 'beat_prop']]
                         final_outcomes['Bet?'] = np.where(final_outcomes['beat_prop'] - final_outcomes['implied_odds'] >= .10, "Bet", "No Bet")
-                        final_outcomes = final_outcomes.loc[final_outcomes['Player'] == player_check]
-                        player_outcomes = player_outcomes.loc[player_outcomes['Player'] == player_check]
+                        final_outcomes = final_outcomes[final_outcomes['Player'] == player_check]
+                        player_outcomes = player_outcomes[player_outcomes['Player'] == player_check]
                         player_outcomes = player_outcomes.drop(columns=['Player']).transpose()
                         player_outcomes = player_outcomes.reset_index()
                         player_outcomes.columns = ['Instance', 'Outcome']
@@ -425,10 +425,10 @@ with tab5:
                             for prop in sim_vars:
                                 st.write(prop)
                                 st.table(prop_df_raw)
-                                prop_df = prop_df_raw.loc[prop_df_raw['prop_type'] == prop]
+                                prop_df = prop_df_raw[prop_df_raw['prop_type'] == prop]
                                 
                                 for books in book_selections:
-                                    prop_df = prop_df.loc[prop_df['book'] == books]
+                                    prop_df = prop_df[prop_df['book'] == books]
                                     prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                     prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                     prop_df['Over'] = 1 / prop_df['over_line']
@@ -511,7 +511,7 @@ with tab5:
                                     players_only['Book'] = players_only['Player'].map(book_dict)
                                     players_only['Prop_avg'] = players_only['Prop'].mean() / 100
                                     players_only['prop_threshold'] = .10
-                                    players_only = players_only.loc[players_only['Mean_Outcome'] > 0]
+                                    players_only = players_only[players_only['Mean_Outcome'] > 0]
                                     players_only['Over_diff'] = players_only['Over%'] - players_only['Imp Over']
                                     players_only['Under_diff'] = players_only['Under%'] - players_only['Imp Under']
                                     players_only['Bet_check'] = np.where(players_only['Over_diff'] > players_only['Under_diff'], players_only['Over_diff'] , players_only['Under_diff'])
@@ -537,40 +537,40 @@ with tab5:
                                 prop_df_raw = prop_df_raw.rename(columns={"Full_name": "Player"})
                                 
                             for books in book_selections:
-                                prop_df = prop_df_raw.loc[prop_df_raw['book'] == books]
+                                prop_df = prop_df_raw[prop_df_raw['book'] == books]
 
                                 if prop_type_var == "NBA_GAME_PLAYER_POINTS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS']
                                 elif prop_type_var == "Points":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Points']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Points']
                                 elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS']
                                 elif prop_type_var == "Rebounds":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Rebounds']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Rebounds']
                                 elif prop_type_var == "NBA_GAME_PLAYER_ASSISTS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_ASSISTS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_ASSISTS']
                                 elif prop_type_var == "Assists":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Assists']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Assists']
                                 elif prop_type_var == "NBA_GAME_PLAYER_3_POINTERS_MADE":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_3_POINTERS_MADE']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_3_POINTERS_MADE']
                                 elif prop_type_var == "3-Pointers Made":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == '3-Pointers Made']
+                                    prop_df = prop_df[prop_df['prop_type'] == '3-Pointers Made']
                                 elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS_ASSISTS']
                                 elif prop_type_var == "Points + Assists + Rebounds":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Assists + Rebounds']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Points + Assists + Rebounds']
                                 elif prop_type_var == "NBA_GAME_PLAYER_POINTS_REBOUNDS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_REBOUNDS']
                                 elif prop_type_var == "Points + Rebounds":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Rebounds']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Points + Rebounds']
                                 elif prop_type_var == "NBA_GAME_PLAYER_POINTS_ASSISTS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_ASSISTS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_POINTS_ASSISTS']
                                 elif prop_type_var == "Points + Assists":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Points + Assists']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Points + Assists']
                                 elif prop_type_var == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS_ASSISTS']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'NBA_GAME_PLAYER_REBOUNDS_ASSISTS']
                                 elif prop_type_var == "Assists + Rebounds":
-                                    prop_df = prop_df.loc[prop_df['prop_type'] == 'Assists + Rebounds']
+                                    prop_df = prop_df[prop_df['prop_type'] == 'Assists + Rebounds']
 
                                 prop_df = prop_df[['Player', 'book', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                 prop_df = prop_df.rename(columns={"over_prop": "Prop"})
@@ -650,7 +650,7 @@ with tab5:
                                 players_only['Prop'] = players_only['Player'].map(prop_dict)
                                 players_only['Prop_avg'] = players_only['Prop'].mean() / 100
                                 players_only['prop_threshold'] = .10
-                                players_only = players_only.loc[players_only['Mean_Outcome'] > 0]
+                                players_only = players_only[players_only['Mean_Outcome'] > 0]
                                 players_only['Over_diff'] = players_only['Over%'] - players_only['Imp Over']
                                 players_only['Under_diff'] = players_only['Under%'] - players_only['Imp Under']
                                 players_only['Bet_check'] = np.where(players_only['Over_diff'] > players_only['Under_diff'], players_only['Over_diff'] , players_only['Under_diff'])