Update app.py

app.py

@@ -59,8 +59,15 @@ def init_baselines():
     raw_display = pd.DataFrame(worksheet.get_all_records())
     raw_display.replace('', np.nan, inplace=True)
     raw_display.rename(columns={"Name": "Player"}, inplace = True)
-    raw_display = raw_display[['Player', 'Position', 'Team', 'Opp', 'Minutes', '3P', 'Points', 'Rebounds', 'Assists', 'Steals', 'Blocks', 'Turnovers', 'Fantasy']]
-    player_stats = raw_display[raw_display['Minutes'] > 0]
+    
+    raw_baselines = raw_display[['Player', 'Position', 'Team', 'Opp', 'Minutes', 'FGM', 'FGA', 'FG2M', 'FG2A', 'Threes', 'FG3A', 'FTM', 'FTA', 'TRB', 'AST', 'STL', 'BLK', 'TOV']]
+    raw_baselines = raw_baselines[raw_baselines['Minutes'] > 0]
+    raw_baselines['Player'].replace(['Jaren Jackson', 'Nic Claxton', 'Jabari Smith', 'Lu Dort', 'Moe Wagner', 'Kyle Kuzma', 'Trey Murphy', 'Cameron Thomas'],
+                                 ['Jaren Jackson Jr.', 'Nicolas Claxton', 'Jabari Smith Jr.', 'Luguentz Dort', 'Moritz Wagner', 'Kyle Kuzma Jr.',
+                                  'Trey Murphy III', 'Cam Thomas'], inplace=True)
+    
+    player_stats = raw_display[['Player', 'Position', 'Team', 'Opp', 'Minutes', '3P', 'Points', 'Rebounds', 'Assists', 'Steals', 'Blocks', 'Turnovers', 'Fantasy']]
+    player_stats = player_stats[player_stats['Minutes'] > 0]
 
     player_stats['Player'].replace(['Jaren Jackson', 'Nic Claxton', 'Jabari Smith', 'Lu Dort', 'Moe Wagner', 'Kyle Kuzma', 'Trey Murphy', 'Cameron Thomas'],
                                  ['Jaren Jackson Jr.', 'Nicolas Claxton', 'Jabari Smith Jr.', 'Luguentz Dort', 'Moritz Wagner', 'Kyle Kuzma Jr.',
@@ -85,21 +92,22 @@ def init_baselines():
     pick_frame['Player'].replace(['Jaren Jackson', 'Nic Claxton', 'Jabari Smith', 'Lu Dort', 'Moe Wagner', 'Kyle Kuzma', 'Trey Murphy', 'Cameron Thomas'],
                                  ['Jaren Jackson Jr.', 'Nicolas Claxton', 'Jabari Smith Jr.', 'Luguentz Dort', 'Moritz Wagner', 'Kyle Kuzma Jr.',
                                   'Trey Murphy III', 'Cam Thomas'], inplace=True)
-    return game_model, player_stats, prop_frame, pick_frame, timestamp
+    
+    return game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp
 
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-game_model, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
 t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
-tab1, tab2, tab3, tab4, tab5 = st.tabs(["Game Betting Model", "Player Projections", "Prop Trend Table", "Player Prop Simulations", "Stat Specific Simulations"])
+tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs(["Game Betting Model", "Player Projections", "Prop Trend Table", "Player Prop Simulations", "Stat Specific Simulations", "Testing"])
 
 with tab1:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset1'):
               st.cache_data.clear()
-              game_model, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+              game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
     line_var1 = st.radio('How would you like to display odds?', options = ['Percentage', 'American'], key='line_var1')
     team_frame = game_model
@@ -124,7 +132,7 @@ with tab2:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset2'):
               st.cache_data.clear()
-              game_model, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+              game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
     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':
@@ -146,7 +154,7 @@ with tab3:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset3'):
               st.cache_data.clear()
-              game_model, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+              game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
     split_var5 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var5')
     if split_var5 == 'Specific Teams':
@@ -170,7 +178,7 @@ with tab4:
     st.info(t_stamp)
     if st.button("Reset Data", key='reset4'):
               st.cache_data.clear()
-              game_model, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+              game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
     col1, col2 = st.columns([1, 5])
     
@@ -315,7 +323,7 @@ with tab5:
     st.info('The Over and Under percentages are a composite percentage based on simulations, historical performance, and implied probabilities, and may be different than you would expect based purely on the median projection. Likewise, the Edge of a bet is not the only indicator of if you should make the bet or not as the suggestion is using a base acceptable threshold to determine how much edge you should have for each stat category.')
     if st.button("Reset Data/Load Data", key='reset5'):
               st.cache_data.clear()
-              game_model, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+              game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
               t_stamp = f"Last Update: " + str(timestamp) + f" CST"
     col1, col2 = st.columns([1, 5])
     
@@ -618,4 +626,24 @@ with tab5:
                                 file_name='Nba_prop_proj.csv',
                                 mime='text/csv',
                                 key='prop_proj',
-                            )
+                            )
+with tab6:
+    st.info(t_stamp)
+    if st.button("Reset Data", key='reset6'):
+              st.cache_data.clear()
+              game_model, raw_baselines, player_stats, prop_frame, pick_frame, timestamp = init_baselines()
+              t_stamp = f"Last Update: " + str(timestamp) + f" CST"
+    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 = player_stats['Team'].unique(), key='team_var6')
+    elif split_var6 == 'All':
+        team_var6 = player_stats.Team.values.tolist()
+    raw_baselines_disp = raw_baselines[raw_baselines['Team'].isin(team_var6)]\
+    raw_stats_disp = raw_stats_disp.sort_values(by='Minutes', ascending=False)
+    st.data_editor(raw_stats_disp.format(precision=2), use_container_width = True)
+    st.download_button(
+        label="Export Customizable Model",
+        data=convert_df_to_csv(player_stats),
+        file_name='NBA_stats_export.csv',
+        mime='text/csv',
+    )