added some writes and corrected drop_duplicates

app.py

@@ -427,13 +427,12 @@ with tab5:
                                     prop_df = prop_df.loc[prop_df['prop_type'] == prop]
                                     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.dropduplicates(subset=['Player'])
+                                    prop_df = prop_df.drop_duplicates(subset=['Player'])
                                     prop_df = prop_df.loc[prop_df['Prop'] != 0]
                                     prop_df['Over'] = 1 / prop_df['over_line']
                                     prop_df['Under'] = 1 / prop_df['under_line']
                                     df = pd.merge(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                                     df = df.reset_index(drop=True)
-                                    st.table(df)
                                     
                                     prop_dict = dict(zip(df.Player, df.Prop))
                                     team_dict = dict(zip(df.Player, df.Team))
@@ -461,8 +460,6 @@ with tab5:
                                         df['Median'] = df['Points'] + df['Assists']
                                     elif prop == "NBA_GAME_PLAYER_REBOUNDS_ASSISTS" or prop == "Assists + Rebounds":
                                         df['Median'] = df['Rebounds'] + df['Assists']
-                                    
-                                    st.write(prop)
                                         
                                     flex_file = df.copy()
                                     flex_file['Floor'] = flex_file['Median'] * .25
@@ -522,6 +519,7 @@ with tab5:
                                     sim_all_hold = pd.concat([sim_all_hold, leg_outcomes])
                                     
                                     final_outcomes = sim_all_hold
+                                    st.write(f'finished {prop}')
                                 
                         elif prop_type_var != 'All Props':
                             if game_select_var == 'Aggregate':
@@ -569,8 +567,7 @@ with tab5:
                                 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.loc[prop_df['Prop'] != 0]
-                                prop_df = prop_df.dropduplicates(subset=['Player'])
-                                st.table(prop_df)
+                                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(player_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
@@ -661,6 +658,7 @@ with tab5:
                                 sim_all_hold = pd.concat([sim_all_hold, leg_outcomes])
                                 
                                 final_outcomes = sim_all_hold
+                                st.write(f'finished {prop_type_var}')
                         
                         final_outcomes = final_outcomes.dropna()
                         if game_select_var == 'Pick6':