Update app.py

app.py

@@ -49,6 +49,8 @@ gcservice_account = init_conn()
 NBAGetGameData = 'https://docs.google.com/spreadsheets/d/1tRQrF_I5rS7Q0g9vE8NrENDZ2P3_DvtbBZzKEakwOI0/edit#gid=1373653837'
 NBABettingModel = 'https://docs.google.com/spreadsheets/d/1WBnvOHQi_zVTGF63efejK5ho02AY00HiYrMHnMJXY1E/edit#gid=1157978351'
 
+game_format = {'Win %', 'Injury and Rotation Adjusted Win %'}
+
 percentages_format = {'Playoff Odds': '{:.2%}', 'Division Odds': '{:.2%}', 'Top 4 Seed Odds': '{:.2%}', '1 Seed Odds': '{:.2%}', 'Win 1st Round': '{:.2%}',
                       'Win 2nd Round': '{:.2%}', 'Win Conference': '{:.2%}', 'Win Title': '{:.2%}', '1': '{:.2%}', '2': '{:.2%}', '3': '{:.2%}',
                       '4': '{:.2%}', '5': '{:.2%}', '6': '{:.2%}', '7': '{:.2%}', '8': '{:.2%}', '9': '{:.2%}', '10': '{:.2%}', '11': '{:.2%}',
@@ -67,6 +69,7 @@ def init_baselines():
     cols_to_check = ['Win %', 'Injury and Rotation Adjusted Win %']
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
     raw_display = raw_display.apply(pd.to_numeric, errors='coerce').fillna(raw_display)
+    raw_display = raw_display.drop(columns=['Day of season', 'Team', 'Opp', 'Date Num', 'DR Team', 'In Minutes File'])
     game_model = raw_display[raw_display['Injury and Rotation Adjusted Win %'] != ""]
     game_model['Team Date'] = game_model['Team'] + " " + game_model['Date']
 
@@ -81,57 +84,79 @@ def init_baselines():
     raw_display.loc[:, cols_to_check] = raw_display.loc[:, cols_to_check].replace({'%': ''}, regex=True).astype(float) / 100
     raw_display = raw_display.apply(pd.to_numeric, errors='coerce').fillna(raw_display)
     season_model = raw_display[raw_display['Team'] != ""]
+    title_sims = season_model[['Team', 'Conference', 'Division', 'Power Rank', 'Team PointMarginPerGame', 'SeasonSimLookup', 'Win Projection Now',
+                               'Playoff Odds', 'Division Odds', 'Top 4 Seed Odds', '1 Seed Odds', 'Win 1st Round', 'Win 2nd Round', 'Win Conference', 'Win Title']]
+    seed_probs = season_model[['Team', 'Conference', 'Division', 'Avg Seed', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15']]
 
-    return game_model, season_model
+    return game_model, season_model, seed_probs, title_sims
 
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-game_model, season_model = init_baselines()
+game_model, season_model, seed_probs, title_sims = init_baselines()
 
 tab1, tab2 = st.tabs(["Game Betting Model", "Season and Futures"])
 
 with tab1:
-    if st.button("Reset Data", key='reset1'):
-              st.cache_data.clear()
-              game_model, season_model = 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 = game_model['Team'].unique(), key='team_var1')
-    elif split_var1 == 'All':
-        team_var1 = game_model.Team.values.tolist()
-    date_split_var1 = st.radio("Would you like to view all Dates or specific ones?", ('All', 'Specific Dates'), key='date_split_var1')
-    if date_split_var1 == 'Specific Teams':
-        date_var1 = st.multiselect('Which Dates would you like to include in the tables?', options = game_model['Date'].unique(), key='date_var1')
-    elif date_split_var1 == 'All':
-        date_var1 = game_model.Date.values.tolist()
-    game_display = game_model[game_model['Team'].isin(team_var1)]
-    game_display = game_display[game_display['Date'].isin(date_var1)]
-    game_display = game_display.set_index('Team Date')
-    st.dataframe(game_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
-    st.download_button(
-        label="Export Game Model",
-        data=convert_df_to_csv(game_model),
-        file_name='AmericanNumbers_Game_Model_export.csv',
-        mime='text/csv',
-    )
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset1'):
+                  st.cache_data.clear()
+                  game_model, season_model, seed_probs, title_sims = 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 = game_model['Team'].unique(), key='team_var1')
+        elif split_var1 == 'All':
+            team_var1 = game_model.Team.values.tolist()
+        date_split_var1 = st.radio("Would you like to view all Dates or specific ones?", ('All', 'Specific Dates'), key='date_split_var1')
+        if date_split_var1 == 'Specific Teams':
+            date_var1 = st.multiselect('Which Dates would you like to include in the tables?', options = game_model['Date'].unique(), key='date_var1')
+        elif date_split_var1 == 'All':
+            date_var1 = game_model.Date.values.tolist()
+    with col2:
+        game_display = game_model[game_model['Team'].isin(team_var1)]
+        game_display = game_display[game_display['Date'].isin(date_var1)]
+        game_display = game_display.set_index('Team Date')
+        st.dataframe(game_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        st.download_button(
+            label="Export Game Model",
+            data=convert_df_to_csv(game_model),
+            file_name='AmericanNumbers_Game_Model_export.csv',
+            mime='text/csv',
+        )
 
 with tab2:
-    if st.button("Reset Data", key='reset2'):
-              st.cache_data.clear()
-              game_model, season_model = 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 = season_model['Team'].unique(), key='team_var2')
-    elif split_var2 == 'All':
-        team_var2 = season_model.Team.values.tolist()
-    season_model = season_model[season_model['Team'].isin(team_var2)]
-    season_display = season_model.set_index('Team')
-    season_display = season_display.sort_values(by=['Win Projection Now'], ascending=False)
-    st.dataframe(season_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
-    st.download_button(
-        label="Export Futures Model",
-        data=convert_df_to_csv(season_model),
-        file_name='AmericanNumbers_Season_Futures.csv',
-        mime='text/csv',
-    )
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset2'):
+                  st.cache_data.clear()
+                  game_model, season_model, seed_probs, title_sims = init_baselines()
+        view_var2 = st.radio("Would you like to view title odds and win projections or seeding probabilities?", ('Win Odds', 'Seed Probabilities'), key='view_var2')
+        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 = season_model['Team'].unique(), key='team_var2')
+        elif split_var2 == 'All':
+            team_var2 = season_model.Team.values.tolist()
+    with col2:
+        if view_var2 == 'Win Odds':
+            title_sims = title_sims[title_sims['Team'].isin(team_var2)]
+            season_display = title_sims.set_index('Team')
+            season_display = season_display.sort_values(by=['Win Projection Now'], ascending=False)
+            st.dataframe(season_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
+            st.download_button(
+                label="Export Futures Model",
+                data=convert_df_to_csv(title_sims),
+                file_name='AmericanNumbers_Season_Futures.csv',
+                mime='text/csv',
+            )
+        elif view_var2 == 'Seed Probabilities':
+            seed_probs = seed_probs[seed_probs['Team'].isin(team_var2)]
+            season_display = seed_probs.set_index('Team')
+            season_display = season_display.sort_values(by=['Win Projection Now'], ascending=False)
+            st.dataframe(season_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(percentages_format, precision=2), use_container_width = True)
+            st.download_button(
+                label="Export Futures Model",
+                data=convert_df_to_csv(seed_probs),
+                file_name='AmericanNumbers_Season_Futures.csv',
+                mime='text/csv',
+            )