Update app.py

app.py

@@ -259,25 +259,26 @@ with tab2:
                         'STDev_map':dict(zip(raw_baselines.Player,raw_baselines.STDev)),
                         'team_check_map':dict(zip(raw_baselines.Player,raw_baselines.Team))
                         }
-                Sim_Winners = sim_contest(500, st.session_state.working_seed, maps_dict)
+                Sim_Winners = sim_contest(1000, st.session_state.working_seed, maps_dict, sharp_split, Contest_Size)
+                Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners))
                 
-                st.table(Sim_Winners.head(10))
+                #st.table(Sim_Winner_Frame)
                             
-                # # Initial setup
-                # Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners), columns=FinalPortfolio.columns.tolist() + ['Fantasy'])
-                # Sim_Winner_Frame['GPP_Proj'] = (Sim_Winner_Frame['Projection'] + Sim_Winner_Frame['Fantasy']) / 2
-                # Sim_Winner_Frame['unique_id'] = Sim_Winner_Frame['Projection'].astype(str) + Sim_Winner_Frame['Salary'].astype(str) + Sim_Winner_Frame['Own'].astype(str)
-                # Sim_Winner_Frame = Sim_Winner_Frame.assign(win_count=Sim_Winner_Frame['unique_id'].map(Sim_Winner_Frame['unique_id'].value_counts()))
-                
-                # # Type Casting
-                # type_cast_dict = {'Salary': int, 'Projection': np.float16, 'Fantasy': np.float16, 'GPP_Proj': np.float32}
-                # Sim_Winner_Frame = Sim_Winner_Frame.astype(type_cast_dict)
+                # Initial setup
+                Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners), columns=column_names + ['Fantasy'])
+                Sim_Winner_Frame['GPP_Proj'] = (Sim_Winner_Frame['proj'] + Sim_Winner_Frame['Fantasy']) / 2
+                Sim_Winner_Frame['unique_id'] = Sim_Winner_Frame['proj'].astype(str) + Sim_Winner_Frame['salary'].astype(str) + Sim_Winner_Frame['Team'].astype(str) + Sim_Winner_Frame['Secondary'].astype(str)
+                Sim_Winner_Frame = Sim_Winner_Frame.assign(win_count=Sim_Winner_Frame['unique_id'].map(Sim_Winner_Frame['unique_id'].value_counts()))
                 
-                # del FinalPortfolio, insert_port, type_cast_dict
+                # Type Casting
+                type_cast_dict = {'salary': int, 'proj': np.float16, 'Fantasy': np.float16, 'GPP_Proj': np.float32}
+                Sim_Winner_Frame = Sim_Winner_Frame.astype(type_cast_dict)
                 
-                # # Sorting
-                # st.session_state.Sim_Winner_Frame = Sim_Winner_Frame.sort_values(by=['win_count', 'GPP_Proj'], ascending= [False, False]).copy().drop_duplicates(subset='unique_id').head(100)
-                # st.session_state.Sim_Winner_Frame.drop(columns='unique_id', inplace=True)
+                # Sorting
+                st.session_state.Sim_Winner_Frame = Sim_Winner_Frame.sort_values(by=['win_count', 'GPP_Proj'], ascending= [False, False]).copy().drop_duplicates(subset='unique_id').head(100)
+                st.session_state.Sim_Winner_Frame.drop(columns='unique_id', inplace=True)
+
+                st.dataframe(st.session_state.Sim_Winner_Frame)
                 
                 # # Data Copying
                 # st.session_state.Sim_Winner_Export = Sim_Winner_Frame.copy()