Update app.py

app.py

@@ -4,12 +4,15 @@ st.set_page_config(layout="wide")
 for name in dir():
     if not name.startswith('_'):
         del globals()[name]
-
+        
 import numpy as np
 import pandas as pd
 import streamlit as st
 import gspread
 import gc
+import plotly.express as px
+import plotly.io as pio
+pio.renderers.default='browser'
 
 @st.cache_resource
 def init_conn():
@@ -78,6 +81,8 @@ def init_baselines():
     gamelog_table['spread'] = (gamelog_table['opp_score'] - gamelog_table['team_score']).abs()
     gamelog_table['GAME_DATE'] = pd.to_datetime(gamelog_table['GAME_DATE']).dt.date
     
+    spread_dict = dict(zip(gamelog_table['GAME_ID'], gamelog_table['spread']))
+    
     gamelog_table = gamelog_table.set_axis(['Player', 'Pos', 'game_id', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min', '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',
@@ -94,9 +99,20 @@ def init_baselines():
     rot_table[data_cols] = rot_table[data_cols].apply(pd.to_numeric, errors='coerce')
     rot_table = rot_table[rot_table['Player'] != 0]
     
+    worksheet = sh.worksheet('Rotation_stats')
+    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)
+    game_rot = raw_display[raw_display['PLAYER_NAME'] != ""]
+    data_cols = game_rot.columns.drop(['PLAYER_NAME', 'POS', 'TEAM_ABBREVIATION', 'OPP_ABBREVIATION', 'TEAM_NAME', 'OPP_NAME', 'GAME_DATE',
+                                       'MATCHUP', 'WL', 'backlog_lookup', 'Task', 'game_players'])
+    game_rot[data_cols] = game_rot[data_cols].apply(pd.to_numeric, errors='coerce')
+    game_rot['spread'] = game_rot['GAME_ID'].map(spread_dict)
+    
     timestamp = gamelog_table['Date'].max()
     
-    return gamelog_table, rot_table, timestamp
+    return gamelog_table, rot_table, game_rot, timestamp
 
 @st.cache_data(show_spinner=False)
 def seasonlong_build(data_sample):
@@ -197,7 +213,7 @@ def split_frame(input_df, rows):
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
-gamelog_table, rot_table, timestamp = init_baselines()
+gamelog_table, rot_table, game_rot, timestamp = init_baselines()
 t_stamp = f"Updated through: " + str(timestamp) + f" CST"
 basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
 basic_season_cols = ['Pos', 'Team', 'Min']
@@ -217,7 +233,7 @@ 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, tab4 = st.tabs(['Gamelogs', 'Correlation Matrix', 'Position vs. Opp', 'Rotations'])
+tab1, tab2, tab3, tab4, tab5 = st.tabs(['Gamelogs', 'Correlation Matrix', 'Position vs. Opp', 'Positional Percentages', 'Game Rotations'])
 
 with tab1:
     st.info(t_stamp)
@@ -225,7 +241,7 @@ with tab1:
     with col1:
         if st.button("Reset Data", key='reset1'):
                   st.cache_data.clear()
-                  gamelog_table, rot_table = init_baselines()
+                  gamelog_table, rot_table, game_rot, timestamp = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['team_score', 'opp_score', 'spread', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -350,7 +366,7 @@ with tab2:
     with col1:
         if st.button("Reset Data", key='reset2'):
                   st.cache_data.clear()
-                  gamelog_table, rot_table = init_baselines()
+                  gamelog_table, rot_table, game_rot, timestamp = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['team_score', 'opp_score', 'spread', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -441,7 +457,7 @@ with tab3:
     with col1:
         if st.button("Reset Data", key='reset3'):
                   st.cache_data.clear()
-                  gamelog_table, rot_table = init_baselines()
+                  gamelog_table, rot_table, game_rot, timestamp = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['team_score', 'opp_score', 'spread', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -524,7 +540,7 @@ with tab4:
     with col1:
         if st.button("Reset Data", key='reset4'):
                   st.cache_data.clear()
-                  gamelog_table, rot_table = init_baselines()
+                  gamelog_table, rot_table, game_rot, timestamp = init_baselines()
                   basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
                   basic_season_cols = ['Pos', 'Team', 'Min']
                   data_cols = ['team_score', 'opp_score', 'spread', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M',
@@ -563,4 +579,100 @@ with tab4:
                 data=convert_df_to_csv(rot_display),
                 file_name='Rotations_NBA_View.csv',
                 mime='text/csv',
-        )
+        )
+
+with tab1:
+    st.info(t_stamp)
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset5'):
+                  st.cache_data.clear()
+                  gamelog_table, rot_table, game_rot, timestamp = init_baselines()
+                  basic_cols = ['Player', 'Pos', 'Team', 'Opp', 'Season', 'Date', 'Matchup', 'Min']
+                  basic_season_cols = ['Pos', 'Team', 'Min']
+                  data_cols = ['team_score', 'opp_score', 'spread', '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_rot_teams = rot_table.drop_duplicates(subset='Team')
+                  total_rot_teams = indv_rot_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()
+        
+        game_rot_view = st.radio("What set would you like to view?", ('Team Rotations', 'Player Rotations'), key='game_rot_view')
+        
+        if game_rot_view == 'Team Rotations':
+            game_rot_team = st.selectbox("What team would you like to work with?", options = total_teams, key='game_rot_team')
+            team_backlog = game_rot[game_rot['TEAM_ABBREVIATION'] == game_rot_team]
+            
+            game_id_var = st.selectbox("What game would you like to view?", options = team_backlog['backlog_lookup'], key='game_id_var')
+            
+            game_rot_spread = st.slider("Is there a certain spread range you want to view?", 0, 100, (0, 100), key='game_rot_spread')
+            
+            game_rot_min = st.slider("Is there a certain minutes range you want to view?", 0, 60, (0, 60), key='game_rot_min')
+            
+            game_rot_dates = st.radio("Would you like to view all dates or specific ones?", ('All', 'Specific Dates'), key='game_rot_dates')
+            
+            if game_rot_dates == 'Specific Dates':
+                game_rot_low_date = st.date_input('Min Date:', value=None, format="YYYY-MM-DD", key='game_rot_low_date')
+                if game_rot_low_date is not None:
+                    game_rot_low_date = pd.to_datetime(low_date).date()
+                game_rot_high_date = st.date_input('Max Date:', value=None, format="YYYY-MM-DD", key='game_rot_high_date')
+                if game_rot_high_date is not None:
+                    game_rot_high_date = pd.to_datetime(high_date).date()
+            elif game_rot_dates == 'All':
+                game_rot_low_date = gamelog_table['Date'].min()
+                game_rot_high_date = gamelog_table['Date'].max()
+            
+        
+    
+    with col2:
+        working_data = game_rot
+        if game_rot_view == 'Player Rotations':
+            display = st.container()
+            working_data = working_data[working_data['GAME_DATE'] >= game_rot_low_date]
+            working_data = working_data[working_data['GAME_DATE'] <= game_rot_high_date]
+            working_data = working_data[working_data['MIN'] >= game_rot_min[0]]
+            working_data = working_data[working_data['MIN'] <= game_rot_min[1]]
+            working_data = working_data[working_data['spread'] >= game_rot_spread[0]]
+            working_data = working_data[working_data['spread'] <= game_rot_spread[1]]
+            check_rotation = working_data[working_data['backlog_lookup'] == game_id_var]
+
+            fig = px.timeline(check_rotation, x_start="Start", x_end="Finish", y="Task", range_x=[0,check_rotation["Finish"].max()], text='minutes')
+            fig.update_yaxes(autorange="reversed") 
+
+            fig.layout.xaxis.type = 'linear'
+            fig.data[0].x = check_rotation.delta.tolist()
+            fig.add_vline(x=12, line_width=3, line_dash="dash", line_color="green")
+            fig.add_vline(x=24, line_width=3, line_dash="dash", line_color="green")
+            fig.add_vline(x=36, line_width=3, line_dash="dash", line_color="green")
+            # pages = pages.set_index('Player')
+            display.plotly_chart(fig, use_container_width=True)
+            
+        elif game_rot_view == 'Team Rotations':
+            display = st.container()
+            working_data = working_data[working_data['GAME_DATE'] >= game_rot_low_date]
+            working_data = working_data[working_data['GAME_DATE'] <= game_rot_high_date]
+            working_data = working_data[working_data['MIN'] >= game_rot_min[0]]
+            working_data = working_data[working_data['MIN'] <= game_rot_min[1]]
+            working_data = working_data[working_data['spread'] >= game_rot_spread[0]]
+            working_data = working_data[working_data['spread'] <= game_rot_spread[1]]
+            check_rotation = working_data[working_data['backlog_lookup'] == game_id_var]
+
+            fig = px.timeline(check_rotation, x_start="Start", x_end="Finish", y="Task", range_x=[0,check_rotation["Finish"].max()], text='minutes')
+            fig.update_yaxes(autorange="reversed") 
+
+            fig.layout.xaxis.type = 'linear'
+            fig.data[0].x = check_rotation.delta.tolist()
+            fig.add_vline(x=12, line_width=3, line_dash="dash", line_color="green")
+            fig.add_vline(x=24, line_width=3, line_dash="dash", line_color="green")
+            fig.add_vline(x=36, line_width=3, line_dash="dash", line_color="green")
+            # pages = pages.set_index('Player')
+            display.plotly_chart(fig, use_container_width=True)