added book objects to a bunch of dataframes

app.py

@@ -191,7 +191,7 @@ with tab3:
                                 for books in ['FANDUEL', 'DRAFTKINGS', 'BET365', 'CONSENSUS']:
                                     prop_df = prop_df_raw.loc[prop_df_raw['book'] == books]
                                     prop_df = prop_df.loc[prop_df['prop_type'] == prop]
-                                    prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                                    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.loc[prop_df['Prop'] != 0]
                                     st.table(prop_df)
@@ -200,6 +200,7 @@ with tab3:
                                     df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                                     
                                     prop_dict = dict(zip(df.Player, df.Prop))
+                                    book_dict = dict(zip(df.Player, df.book))
                                     over_dict = dict(zip(df.Player, df.Over))
                                     under_dict = dict(zip(df.Player, df.Under))
                                     
@@ -221,7 +222,7 @@ with tab3:
                                     flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1)
                                     flex_file['STD'] = (flex_file['Median']/3)
                                     flex_file['Prop'] = flex_file['Player'].map(prop_dict)
-                                    flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
+                                    flex_file = flex_file[['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
             
                                     hold_file = flex_file
                                     overall_file = flex_file
@@ -232,12 +233,12 @@ with tab3:
                                     for x in range(0,total_sims):    
                                         prop_file[x] = prop_file['Prop']
             
-                                    prop_file = prop_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                                    prop_file = prop_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
             
                                     for x in range(0,total_sims):
                                         overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
             
-                                    overall_file=overall_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                                    overall_file=overall_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
             
                                     players_only = hold_file[['Player']]
             
@@ -255,6 +256,7 @@ with tab3:
                                     players_only['Imp Under'] = players_only['Player'].map(under_dict)
                                     players_only['Under%'] = players_only[["Under", "Imp Under"]].mean(axis=1)
                                     players_only['Prop'] = players_only['Player'].map(prop_dict)
+                                    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]
@@ -269,7 +271,7 @@ with tab3:
                                     players_only['Player'] = hold_file[['Player']]
                                     players_only['Team'] = players_only['Player'].map(team_dict)
             
-                                    leg_outcomes = players_only[['Player', 'Team', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
+                                    leg_outcomes = players_only[['Player', 'Team', 'Book', 'Prop type', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
                                     sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                                 
                                     final_outcomes = sim_all_hold
@@ -286,7 +288,7 @@ with tab3:
                                 prop_df = prop_df_raw.loc[prop_df_raw['book'] == books]
                                 if prop_type_var == "SOG":
                                     prop_df = prop_df.loc[prop_df['prop_type'] == 'NHL_GAME_PLAYER_SHOTS_ON_GOAL']
-                                    prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                                    prop_df = prop_df[['Player', 'book', 'book', 'over_prop', 'over_line', 'under_line']]
                                     prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                     prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                     st.table(prop_df)
@@ -296,7 +298,7 @@ with tab3:
                                     df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                                 elif prop_type_var == "points":
                                     prop_df = prop_df.loc[prop_df['prop_type'] == 'NHL_GAME_PLAYER_POINTS']
-                                    prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                                    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.loc[prop_df['Prop'] != 0]
                                     st.table(prop_df)
@@ -306,7 +308,7 @@ with tab3:
                                     df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                                 elif prop_type_var == "assists":
                                     prop_df = prop_df.loc[prop_df['prop_type'] == 'NHL_GAME_PLAYER_ASSISTS']
-                                    prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                                    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.loc[prop_df['Prop'] != 0]
                                     st.table(prop_df)
@@ -316,7 +318,7 @@ with tab3:
                                     df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                                 elif prop_type_var == "blocked_shots":
                                     prop_df = prop_df.loc[prop_df['prop_type'] == 'NHL_GAME_PLAYER_BLOCKED_SHOTS']
-                                    prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
+                                    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.loc[prop_df['Prop'] != 0]
                                     st.table(prop_df)
@@ -327,6 +329,7 @@ with tab3:
                                 
                                 st.table(df)
                                 prop_dict = dict(zip(df.Player, df.Prop))
+                                book_dict = dict(zip(df.Player, df.book))
                                 over_dict = dict(zip(df.Player, df.Over))
                                 under_dict = dict(zip(df.Player, df.Under))
                                 
@@ -348,7 +351,7 @@ with tab3:
                                 flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1)
                                 flex_file['STD'] = (flex_file['Median']/3)
                                 flex_file['Prop'] = flex_file['Player'].map(prop_dict)
-                                flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
+                                flex_file = flex_file[['Player', 'Prop', 'book', 'Floor', 'Median', 'Ceiling', 'STD']]
         
                                 hold_file = flex_file
                                 overall_file = flex_file
@@ -359,12 +362,12 @@ with tab3:
                                 for x in range(0,total_sims):    
                                     prop_file[x] = prop_file['Prop']
         
-                                prop_file = prop_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                                prop_file = prop_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
         
                                 for x in range(0,total_sims):
                                     overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
         
-                                overall_file=overall_file.drop(['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
+                                overall_file=overall_file.drop(['Player', 'book', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
         
                                 players_only = hold_file[['Player']]
         
@@ -382,6 +385,7 @@ with tab3:
                                 players_only['Imp Under'] = players_only['Player'].map(under_dict)
                                 players_only['Under%'] = players_only[["Under", "Imp Under"]].mean(axis=1)
                                 players_only['Prop'] = players_only['Player'].map(prop_dict)
+                                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]
@@ -395,7 +399,7 @@ with tab3:
                                 players_only['Player'] = hold_file[['Player']]
                                 players_only['Team'] = players_only['Player'].map(team_dict)
         
-                                leg_outcomes = players_only[['Player', 'Team', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
+                                leg_outcomes = players_only[['Player', 'Team', 'Book', 'Prop', 'Mean_Outcome', 'Imp Over', 'Over%', 'Imp Under', 'Under%', 'Bet?', 'Edge']]
                                 sim_all_hold = pd.concat([sim_all_hold, leg_outcomes], ignore_index=True)
                                 
                                 final_outcomes = sim_all_hold