Update app.py

app.py

@@ -63,16 +63,21 @@ def init_baselines():
           raw_display.replace('', np.nan, inplace=True)
           prop_frame = raw_display.dropna(subset='Team')
           
+          worksheet = sh.worksheet('Prop_results')
+          raw_display = pd.DataFrame(worksheet.get_all_records())
+          raw_display.replace('', np.nan, inplace=True)
+          betsheet_frame = raw_display.dropna(subset='proj')
+          
           worksheet = sh.worksheet('Pick6_ingest')
           raw_display = pd.DataFrame(worksheet.get_all_records())
           raw_display.replace('', np.nan, inplace=True)
           pick_frame = raw_display.dropna(subset='Player')
           
-          return pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp
+          return pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp
 
-pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
+pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
 
-tab1, tab2, tab3, tab4, tab5 = st.tabs(["Game Betting Model", "Pitcher Prop Projections", "Hitter Prop Projections", "Player Prop Simulations", "Stat Specific Simulations"])
+tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs(["Game Betting Model", "Pitcher Prop Projections", "Hitter Prop Projections", "Player Prop Simulations", "Stat Specific Simulations", "Bet Sheet"])
 
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
@@ -81,7 +86,7 @@ with tab1:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset1'):
               st.cache_data.clear()
-              pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
+              pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
     line_var1 = st.radio('How would you like to display odds?', options = ['Percentage', 'American'], key='line_var1')
     if line_var1 == 'Percentage':
         team_frame = team_frame[['Names', 'Game', 'Win Percentage', 'Spread', 'Cover Spread Percentage', 'Avg Score', 'Game Total', 'Avg Fifth Inning', 'Fifth Inning Lead Percentage']]
@@ -105,7 +110,7 @@ with tab2:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset2'):
               st.cache_data.clear()
-              pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
+              pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
     split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
     if split_var1 == 'Specific Teams':
         team_var1 = st.multiselect('Which teams would you like to include in the tables?', options = pitcher_stats['Team'].unique(), key='team_var1')
@@ -127,7 +132,7 @@ with tab3:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset3'):
               st.cache_data.clear()
-              pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
+              pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
     split_var2 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var2')
     if split_var2 == 'Specific Teams':
         team_var2 = st.multiselect('Which teams would you like to include in the tables?', options = hitter_stats['Team'].unique(), key='team_var2')
@@ -149,7 +154,7 @@ with tab4:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset4'):
               st.cache_data.clear()
-              pitcher_stats, hitter_stats, team_frame, prop_frame, pick_frame, t_stamp = init_baselines()
+              pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
     col1, col2 = st.columns([1, 5])
     
     with col2:
@@ -556,4 +561,27 @@ with tab5:
                                 mime='text/csv',
                                 key='prop_proj',
                             )
-                                        
+
+with tab6:
+    st.info(t_stamp)
+    if st.button("Reset Data", key='reset6'):
+            st.info('This sheet is more or less a static represenation of the Stat Specific Simulations. ROR is rate of return based on hit rate and payout. Use the over and under EDGEs to place bets. 20%+ should be considered a 1 unit bet, 15-20% is .75 units, 10-15% is .50 units, 5-10% is .25 units, and 0-5% is .1 units.')
+            st.cache_data.clear()
+            pitcher_stats, hitter_stats, team_frame, prop_frame, betsheet_frame, pick_frame, t_stamp = init_baselines()
+    split_var6 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var6')
+    if split_var6 == 'Specific Teams':
+        team_var6 = st.multiselect('Which teams would you like to include in the tables?', options = betsheet_frame['Team'].unique(), key='team_var6')
+    elif split_var6 == 'All':
+        team_var6 = pitcher_stats.Team.values.tolist()
+    betsheet_disp = betsheet_frame.copy()
+    betsheet_disp = betsheet_disp[betsheet_disp['Team'].isin(team_var6)]
+    betsheet_disp = betsheet_disp.set_index('Player')
+    betsheet_disp = betsheet_disp.sort_values(by='over_EDGE', ascending=False)
+    st.dataframe(betsheet_disp.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+    st.download_button(
+        label="Export Betsheet",
+        data=convert_df_to_csv(betsheet_disp),
+        file_name='MLB_Betsheet_export.csv',
+        mime='text/csv',
+        key='MLB_Betsheet_export',
+    )