Update app.py

app.py

@@ -36,6 +36,8 @@ gcservice_account = init_conn()
 
 NBA_Data = 'https://docs.google.com/spreadsheets/d/1Yq0vGriWK-bS79e-bD6_u9pqrYE6Yrlbb_wEkmH-ot0/edit#gid=1808117109'
 
+percentages_format = {'PG': '{:.2%}', 'SG': '{:.2%}', 'SF': '{:.2%}', 'PF': '{:.2%}', 'C': '{:.2%}'}
+
 @st.cache_resource(ttl = 600)
 def init_baselines():
     sh = gcservice_account.open_by_url(NBA_Data)
@@ -78,7 +80,17 @@ def init_baselines():
                                             'Passes', 'Alt Assists', 'FT Assists', 'Assists', 'Stl', 'Blk', 'Tov', 'PF', 'DD', 'TD', 'Fantasy', 'FD_Fantasy',
                                             'Rebound%', 'Assists/Pass', 'Touch_per_min', 'Fantasy/Touch', 'FD Fantasy/Touch'], axis=1)
     
-    return gamelog_table
+    worksheet = sh.worksheet('Rotations')
+    raw_display = pd.DataFrame(worksheet.get_values())
+    raw_display.columns = raw_display.iloc[0]
+    raw_display = raw_display[1:]
+    raw_display = raw_display.reset_index(drop=True)
+    rot_table = raw_display[raw_display['Player'] != ""]
+    rot_table = rot_table[['Player', 'Team', 'PG', 'SG', 'SF', 'PF', 'C', 'Given Pos']]
+    data_cols = ['PG', 'SG', 'SF', 'PF', 'C']
+    rot_table[data_cols] = rot_table[data_cols].apply(pd.to_numeric, errors='coerce')
+    
+    return gamelog_table, rot_table
 
 @st.cache_data(show_spinner=False)
 def seasonlong_build(data_sample):
@@ -179,7 +191,7 @@ def split_frame(input_df, rows):
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-gamelog_table = init_baselines()
+gamelog_table, rot_table = init_baselines()
 basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
 basic_season_cols = ['Pos', 'Team', 'Min']
 data_cols = ['Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -196,14 +208,14 @@ indv_players = gamelog_table.drop_duplicates(subset='Player')
 total_players = indv_players.Player.values.tolist()
 total_dates = gamelog_table.Date.values.tolist()
 
-tab1, tab2, tab3 = st.tabs(['Gamelogs', 'Correlation Matrix', 'Position vs. Opp'])
+tab1, tab2, tab3, tab4 = st.tabs(['Gamelogs', 'Correlation Matrix', 'Position vs. Opp', 'Rotations'])
 
 with tab1:
     col1, col2 = st.columns([1, 9])
     with col1:
         if st.button("Reset Data", key='reset1'):
                   st.cache_data.clear()
-                  gamelog_table = init_baselines()
+                  gamelog_table, rot_table = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -319,7 +331,7 @@ with tab2:
     with col1:
         if st.button("Reset Data", key='reset2'):
                   st.cache_data.clear()
-                  gamelog_table = init_baselines()
+                  gamelog_table, rot_table = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -401,7 +413,7 @@ with tab3:
     with col1:
         if st.button("Reset Data", key='reset3'):
                   st.cache_data.clear()
-                  gamelog_table = init_baselines()
+                  gamelog_table, rot_table = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -470,4 +482,42 @@ with tab3:
                 data=convert_df_to_csv(gamelog_display),
                 file_name='Matchups_NBA_View.csv',
                 mime='text/csv',
+        )
+
+with tab4:
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset3'):
+                  st.cache_data.clear()
+                  gamelog_table, rot_table = init_baselines()
+                  basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
+                  basic_season_cols = ['Pos', 'Team', 'Min']
+                  data_cols = ['Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
+                               'FG3A', 'FG3%', 'FTM', 'FTA', 'FT%', 'OREB Chance', 'OREB', 'DREB Chance', 'DREB', 'REB Chance', 'REB',
+                               'Passes', 'Alt Assists', 'FT Assists', 'Assists', 'Stl', 'Blk', 'Tov', 'PF', 'DD', 'TD', 'Fantasy', 'FD_Fantasy',
+                               'Rebound%', 'Assists/Pass', 'Touch_per_min', 'Fantasy/Touch', 'FD Fantasy/Touch']
+                  season_data_cols = ['Touches', 'Touch/Min', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M', 'FG3A',
+                                      'FG3%', 'FTM', 'FTA', 'FT%', 'OREB Chance', 'OREB', 'DREB Chance', 'DREB', 'REB Chance', 'REB',
+                                      'Passes', 'Alt Assists', 'FT Assists', 'Assists', 'Stl', 'Blk', 'Tov', 'PF', 'DD', 'TD', 'Fantasy', 'FD_Fantasy',
+                                      'Rebound%', 'Assists/Pass', 'Fantasy/Touch', 'FD Fantasy/Touch']
+                  indv_teams = gamelog_table.drop_duplicates(subset='Team')
+                  total_teams = indv_teams.Team.values.tolist()
+                  indv_players = gamelog_table.drop_duplicates(subset='Player')
+                  total_players = indv_players.Player.values.tolist()
+                  total_dates = gamelog_table.Date.values.tolist()
+        
+        team_var4 = st.selectbox('Which team would you like to view?', options = total_teams, key='team_var4')
+    
+    with col2:
+        working_data = rot_table
+        rot_display = working_data[working_data['Team'] == team_var4]
+        display = st.container()
+
+        rot_display = rot_display.set_index('Player')
+        display.dataframe(rot_display.style.format(percentages_format, precision=2), height=500, use_container_width=True)
+        st.download_button(
+                label="Export Rotations Model",
+                data=convert_df_to_csv(rot_display),
+                file_name='Rotations_NBA_View.csv',
+                mime='text/csv',
         )