Update app.py

app.py

@@ -184,7 +184,6 @@ with tab1:
             elif stack_var1 == 'Full Slate':
                     stack_var2 = [4, 3, 2, 1, 0]
         
-
         if st.button("Prepare data export", key='data_export'):
                 data_export = st.session_state.working_seed.copy()
                 st.download_button(
@@ -193,7 +192,6 @@ with tab1:
                     file_name='MLB_optimals_export.csv',
                     mime='text/csv',
                 )
-        st.write(st.session_state)
             
     with col2:
         if st.button("Load Data", key='load_data'):
@@ -221,12 +219,7 @@ with tab1:
                 
         with st.container():
             if 'data_export_display' in st.session_state:
-                try:
-                    st.table(st.session_state.data_export_display)
-                except:
-                    st.write("resources low, waiting 5 seconds and trying again")
-                    time.sleep(5)
-                    st.table(st.session_state.data_export_display)
+                st.dataframe(st.session_state.data_export_display.style.format(freq_format, precision=2), use_container_width = True)
             
 with tab2:
     col1, col2 = st.columns([1, 7])
@@ -310,52 +303,6 @@ with tab2:
                 # Data Copying
                 st.session_state.Sim_Winner_Display = Sim_Winner_Frame.copy()
                 
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:10].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:9].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
-                st.session_state.player_freq['Position'] = st.session_state.player_freq['Player'].map(maps_dict['Pos_map'])
-                st.session_state.player_freq['Salary'] = st.session_state.player_freq['Player'].map(maps_dict['Salary_map'])
-                st.session_state.player_freq['Proj Own'] = st.session_state.player_freq['Player'].map(maps_dict['Own_map']) / 100
-                st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(1000)
-                st.session_state.player_freq['Edge'] = st.session_state.player_freq['Exposure'] - st.session_state.player_freq['Proj Own']
-                st.session_state.player_freq['Team'] = st.session_state.player_freq['Player'].map(maps_dict['Team_map'])
-
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:2].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:1].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.sp_freq['Freq'] = st.session_state.sp_freq['Freq'].astype(int)
-                st.session_state.sp_freq['Position'] = st.session_state.sp_freq['Player'].map(maps_dict['Pos_map'])
-                st.session_state.sp_freq['Salary'] = st.session_state.sp_freq['Player'].map(maps_dict['Salary_map'])
-                st.session_state.sp_freq['Proj Own'] = st.session_state.sp_freq['Player'].map(maps_dict['Own_map']) / 100
-                st.session_state.sp_freq['Exposure'] = st.session_state.sp_freq['Freq']/(1000)
-                st.session_state.sp_freq['Edge'] = st.session_state.sp_freq['Exposure'] - st.session_state.sp_freq['Proj Own']
-                st.session_state.sp_freq['Team'] = st.session_state.sp_freq['Player'].map(maps_dict['Team_map'])
-
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.team_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,12:13].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.team_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,11:12].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.team_freq['Freq'] = st.session_state.team_freq['Freq'].astype(int)
-                st.session_state.team_freq['Exposure'] = st.session_state.team_freq['Freq']/(1000)
-
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.stack_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,13:14].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.stack_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,12:13].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.stack_freq['Freq'] = st.session_state.stack_freq['Freq'].astype(int)
-                st.session_state.stack_freq['Exposure'] = st.session_state.stack_freq['Freq']/(1000)
-                
             else:
                 if sim_site_var1 == 'Draftkings':
                     st.session_state.working_seed = DK_seed.copy()
@@ -399,56 +346,74 @@ with tab2:
                 # Data Copying
                 st.session_state.Sim_Winner_Display = Sim_Winner_Frame.copy()
                 
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:10].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:9].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
-                st.session_state.player_freq['Position'] = st.session_state.player_freq['Player'].map(maps_dict['Pos_map'])
-                st.session_state.player_freq['Salary'] = st.session_state.player_freq['Player'].map(maps_dict['Salary_map'])
-                st.session_state.player_freq['Proj Own'] = st.session_state.player_freq['Player'].map(maps_dict['Own_map']) / 100
-                st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(1000)
-                st.session_state.player_freq['Edge'] = st.session_state.player_freq['Exposure'] - st.session_state.player_freq['Proj Own']
-                st.session_state.player_freq['Team'] = st.session_state.player_freq['Player'].map(maps_dict['Team_map'])
+            if sim_site_var1 == 'Draftkings':
+                st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:10].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            elif sim_site_var1 == 'Fanduel':
+                st.session_state.player_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:9].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
+            st.session_state.player_freq['Position'] = st.session_state.player_freq['Player'].map(maps_dict['Pos_map'])
+            st.session_state.player_freq['Salary'] = st.session_state.player_freq['Player'].map(maps_dict['Salary_map'])
+            st.session_state.player_freq['Proj Own'] = st.session_state.player_freq['Player'].map(maps_dict['Own_map']) / 100
+            st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(1000)
+            st.session_state.player_freq['Edge'] = st.session_state.player_freq['Exposure'] - st.session_state.player_freq['Proj Own']
+            st.session_state.player_freq['Team'] = st.session_state.player_freq['Player'].map(maps_dict['Team_map'])
 
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:2].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:1].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.sp_freq['Freq'] = st.session_state.sp_freq['Freq'].astype(int)
-                st.session_state.sp_freq['Position'] = st.session_state.sp_freq['Player'].map(maps_dict['Pos_map'])
-                st.session_state.sp_freq['Salary'] = st.session_state.sp_freq['Player'].map(maps_dict['Salary_map'])
-                st.session_state.sp_freq['Proj Own'] = st.session_state.sp_freq['Player'].map(maps_dict['Own_map']) / 100
-                st.session_state.sp_freq['Exposure'] = st.session_state.sp_freq['Freq']/(1000)
-                st.session_state.sp_freq['Edge'] = st.session_state.sp_freq['Exposure'] - st.session_state.sp_freq['Proj Own']
-                st.session_state.sp_freq['Team'] = st.session_state.sp_freq['Player'].map(maps_dict['Team_map'])
+            if sim_site_var1 == 'Draftkings':
+                st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:2].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            elif sim_site_var1 == 'Fanduel':
+                st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:1].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            st.session_state.sp_freq['Freq'] = st.session_state.sp_freq['Freq'].astype(int)
+            st.session_state.sp_freq['Position'] = st.session_state.sp_freq['Player'].map(maps_dict['Pos_map'])
+            st.session_state.sp_freq['Salary'] = st.session_state.sp_freq['Player'].map(maps_dict['Salary_map'])
+            st.session_state.sp_freq['Proj Own'] = st.session_state.sp_freq['Player'].map(maps_dict['Own_map']) / 100
+            st.session_state.sp_freq['Exposure'] = st.session_state.sp_freq['Freq']/(1000)
+            st.session_state.sp_freq['Edge'] = st.session_state.sp_freq['Exposure'] - st.session_state.sp_freq['Proj Own']
+            st.session_state.sp_freq['Team'] = st.session_state.sp_freq['Player'].map(maps_dict['Team_map'])
 
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.team_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,12:13].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.team_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,11:12].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.team_freq['Freq'] = st.session_state.team_freq['Freq'].astype(int)
-                st.session_state.team_freq['Exposure'] = st.session_state.team_freq['Freq']/(1000)
-
-                if sim_site_var1 == 'Draftkings':
-                    st.session_state.stack_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,13:14].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                elif sim_site_var1 == 'Fanduel':
-                    st.session_state.stack_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,12:13].values, return_counts=True)),
-                                                    columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
-                st.session_state.stack_freq['Freq'] = st.session_state.stack_freq['Freq'].astype(int)
-                st.session_state.stack_freq['Exposure'] = st.session_state.stack_freq['Freq']/(1000)
+            if sim_site_var1 == 'Draftkings':
+                st.session_state.team_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,12:13].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            elif sim_site_var1 == 'Fanduel':
+                st.session_state.team_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,11:12].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            st.session_state.team_freq['Freq'] = st.session_state.team_freq['Freq'].astype(int)
+            st.session_state.team_freq['Exposure'] = st.session_state.team_freq['Freq']/(1000)
 
-        with st.container():
-            if 'Sim_Winner_Frame' in st.session_state:
-                st.dataframe(st.session_state.Sim_Winner_Frame)
+            if sim_site_var1 == 'Draftkings':
+                st.session_state.stack_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,13:14].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            elif sim_site_var1 == 'Fanduel':
+                st.session_state.stack_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,12:13].values, return_counts=True)),
+                                                columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
+            st.session_state.stack_freq['Freq'] = st.session_state.stack_freq['Freq'].astype(int)
+            st.session_state.stack_freq['Exposure'] = st.session_state.stack_freq['Freq']/(1000)
             
+        with st.container():
+            if 'player_freq' in st.session_state: 
+                player_split_var2 = st.radio("Are you wanting to isolate any lineups with specific players?", ('Full Players', 'Specific Players'), key='player_split_var2')
+                if player_split_var2 == 'Specific Players':
+                          find_var2 = st.multiselect('Which players must be included in the lineups?', options = st.session_state.player_freq['Player'].unique())
+                elif player_split_var2 == 'Full Players':
+                          find_var2 = st.session_state.player_freq.Player.values.tolist()
+    
+                if player_split_var2 == 'Specific Players':
+                          st.session_state.Sim_Winner_Display = st.session_state.Sim_Winner_Frame[np.equal.outer(st.session_state.Sim_Winner_Frame.to_numpy(), find_var2).any(axis=1).all(axis=1)]
+                if player_split_var2 == 'Full Players':
+                          st.session_state.Sim_Winner_Display = st.session_state.Sim_Winner_Frame
+            if 'Sim_Winner_Display' in st.session_state:
+                st.dataframe(st.session_state.Sim_Winner_Display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Own']).format(precision=2), use_container_width = True)
+            if 'Sim_Winner_Export' in st.session_state:
+                st.download_button(
+                    label="Export Full Frame",
+                    data=st.session_state.Sim_Winner_Export.to_csv().encode('utf-8'),
+                    file_name='MLB_consim_export.csv',
+                    mime='text/csv',
+                )  
+                
         with st.container():
             tab1, tab2, tab3, tab4 = st.tabs(['Overall Exposures', 'SP Exposures', 'Team Exposures', 'Stack Size Exposures'])
             with tab1: