Update app.py

app.py

@@ -130,6 +130,23 @@ def seasonlong_build(data_sample):
 
     return season_long_table
 
+@st.cache_data(show_spinner=False)
+def run_corr(data_sample):
+    cor_testing = data_sample
+    cor_testing = cor_testing[cor_testing['Season'] == '22023']
+    date_list = cor_testing['Date'].unique().tolist()
+    player_list = cor_testing['Player'].unique().tolist()
+    corr_frame = pd.DataFrame()
+    corr_frame['DATE'] = date_list
+    for player in player_list:
+        player_testing = cor_testing[cor_testing['Player'] == player]
+        fantasy_map = dict(zip(player_testing['Date'], player_testing['Fantasy']))
+        corr_frame[player] = corr_frame['DATE'].map(fantasy_map)
+    players_fantasy = corr_frame.drop('DATE', axis=1)
+    corrM = players_fantasy.corr()
+    
+    return corrM
+
 @st.cache_data(show_spinner=False)
 def split_frame(input_df, rows):
     df = [input_df.loc[i : i + rows - 1, :] for i in range(0, len(input_df), rows)]
@@ -145,84 +162,142 @@ indv_players = gamelog_table.drop_duplicates(subset='Player')
 total_players = indv_players.Player.values.tolist()
 total_dates = gamelog_table.Date.values.tolist()
 
-col1, col2 = st.columns([1, 9])
-with col1:
-    if st.button("Reset Data", key='reset1'):
-              st.cache_data.clear()
-              gamelog_table = init_baselines()
-              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()
-    
-    split_var1 = st.radio("What table would you like to view?", ('Season Logs', 'Gamelogs'), key='split_var1')
-    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_var1 = st.multiselect('Which teams would you like to include in the tables?', options = total_teams, key='team_var1')
-    elif split_var2 == 'All':
-        team_var1 = total_teams
+tab1, tab2 = st.tabs(['Gamelogs', 'Correlation Matrix'])
+
+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()
+                  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()
         
-    split_var3 = st.radio("Would you like to view all dates or specific ones?", ('All', 'Specific Dates'), key='split_var3')
-    
-    if split_var3 == 'Specific Dates':
-        low_date = st.date_input('Min Date:', value=None, format="YYYY-MM-DD", key='low_date')
-        if low_date is not None:
-            low_date = pd.to_datetime(low_date).date()
-        high_date = st.date_input('Max Date:', value=None, format="YYYY-MM-DD", key='high_date')
-        if high_date is not None:
-            high_date = pd.to_datetime(high_date).date()
-    elif split_var3 == 'All':
-        low_date = gamelog_table['Date'].min()
-        high_date = gamelog_table['Date'].max()
-    
-    split_var4 = st.radio("Would you like to view all players or specific ones?", ('All', 'Specific Players'), key='split_var4')
-    
-    if split_var4 == 'Specific Players':
-        player_var1 = st.multiselect('Which players would you like to include in the tables?', options = total_players, key='player_var1')
-    elif split_var4 == 'All':
-        player_var1 = total_players
-    
-    min_var1 = st.slider("Is there a certain minutes range you want to view?", 0, 60, (0, 60), key='min_var1')
-
-with col2:
-    if split_var1 == 'Season Logs':
-        display = st.container()
-        gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date]
-        gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date]
-        gamelog_table = gamelog_table[gamelog_table['Min'] >= min_var1[0]]
-        gamelog_table = gamelog_table[gamelog_table['Min'] <= min_var1[1]]
-        gamelog_table = gamelog_table[gamelog_table['Team'].isin(team_var1)]
-        gamelog_table = gamelog_table[gamelog_table['Player'].isin(player_var1)]
-        season_long_table = seasonlong_build(gamelog_table)
-        season_long_table = season_long_table.set_index('Player')
-        display.dataframe(season_long_table.style.format(precision=2), use_container_width = True)  
+        split_var1 = st.radio("What table would you like to view?", ('Season Logs', 'Gamelogs'), key='split_var1')
+        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_var1 = st.multiselect('Which teams would you like to include in the tables?', options = total_teams, key='team_var1')
+        elif split_var2 == 'All':
+            team_var1 = total_teams
+            
+        split_var3 = st.radio("Would you like to view all dates or specific ones?", ('All', 'Specific Dates'), key='split_var3')
+        
+        if split_var3 == 'Specific Dates':
+            low_date = st.date_input('Min Date:', value=None, format="YYYY-MM-DD", key='low_date')
+            if low_date is not None:
+                low_date = pd.to_datetime(low_date).date()
+            high_date = st.date_input('Max Date:', value=None, format="YYYY-MM-DD", key='high_date')
+            if high_date is not None:
+                high_date = pd.to_datetime(high_date).date()
+        elif split_var3 == 'All':
+            low_date = gamelog_table['Date'].min()
+            high_date = gamelog_table['Date'].max()
+        
+        split_var4 = st.radio("Would you like to view all players or specific ones?", ('All', 'Specific Players'), key='split_var4')
+        
+        if split_var4 == 'Specific Players':
+            player_var1 = st.multiselect('Which players would you like to include in the tables?', options = total_players, key='player_var1')
+        elif split_var4 == 'All':
+            player_var1 = total_players
         
-    elif split_var1 == 'Gamelogs':
-        gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date]
-        gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date]
-        gamelog_table = gamelog_table[gamelog_table['Min'] >= min_var1[0]]
-        gamelog_table = gamelog_table[gamelog_table['Min'] <= min_var1[1]]
-        gamelog_table = gamelog_table[gamelog_table['Team'].isin(team_var1)]
-        gamelog_table = gamelog_table[gamelog_table['Player'].isin(player_var1)]
-        gamelog_table = gamelog_table.reset_index(drop=True)
-        display = st.container()
+        min_var1 = st.slider("Is there a certain minutes range you want to view?", 0, 60, (0, 60), key='min_var1')
     
-        bottom_menu = st.columns((4, 1, 1))
-        with bottom_menu[2]:
-            batch_size = st.selectbox("Page Size", options=[25, 50, 100])
-        with bottom_menu[1]:
-            total_pages = (
-                int(len(gamelog_table) / batch_size) if int(len(gamelog_table) / batch_size) > 0 else 1
-            )
-            current_page = st.number_input(
-                "Page", min_value=1, max_value=total_pages, step=1
-            )
-        with bottom_menu[0]:
-            st.markdown(f"Page **{current_page}** of **{total_pages}** ")
+    with col2:
+        if split_var1 == 'Season Logs':
+            display = st.container()
+            gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date]
+            gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date]
+            gamelog_table = gamelog_table[gamelog_table['Min'] >= min_var1[0]]
+            gamelog_table = gamelog_table[gamelog_table['Min'] <= min_var1[1]]
+            gamelog_table = gamelog_table[gamelog_table['Team'].isin(team_var1)]
+            gamelog_table = gamelog_table[gamelog_table['Player'].isin(player_var1)]
+            season_long_table = seasonlong_build(gamelog_table)
+            season_long_table = season_long_table.set_index('Player')
+            display.dataframe(season_long_table.style.format(precision=2), use_container_width = True)  
+            
+        elif split_var1 == 'Gamelogs':
+            gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date]
+            gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date]
+            gamelog_table = gamelog_table[gamelog_table['Min'] >= min_var1[0]]
+            gamelog_table = gamelog_table[gamelog_table['Min'] <= min_var1[1]]
+            gamelog_table = gamelog_table[gamelog_table['Team'].isin(team_var1)]
+            gamelog_table = gamelog_table[gamelog_table['Player'].isin(player_var1)]
+            gamelog_table = gamelog_table.reset_index(drop=True)
+            display = st.container()
         
+            bottom_menu = st.columns((4, 1, 1))
+            with bottom_menu[2]:
+                batch_size = st.selectbox("Page Size", options=[25, 50, 100])
+            with bottom_menu[1]:
+                total_pages = (
+                    int(len(gamelog_table) / batch_size) if int(len(gamelog_table) / batch_size) > 0 else 1
+                )
+                current_page = st.number_input(
+                    "Page", min_value=1, max_value=total_pages, step=1
+                )
+            with bottom_menu[0]:
+                st.markdown(f"Page **{current_page}** of **{total_pages}** ")
+            
+            
+            pages = split_frame(gamelog_table, batch_size)
+            # pages = pages.set_index('Player')
+            display.dataframe(data=pages[current_page - 1].style.format(precision=2), use_container_width=True)
+            
+with tab2:
+    col1, col2 = st.columns([1, 9])
+    with col1:
+        if st.button("Reset Data", key='reset2'):
+                  st.cache_data.clear()
+                  gamelog_table = init_baselines()
+                  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()
         
-        pages = split_frame(gamelog_table, batch_size)
-        # pages = pages.set_index('Player')
-        display.dataframe(data=pages[current_page - 1].style.format(precision=2), use_container_width=True)
+        split_var1_t2 = st.radio("Would you like to view specific teams or specific players?", ('Specific Teams', 'Specific Players'), key='split_var1_t2')
+        
+        if split_var1_t2 == 'Specific Teams':
+            corr_var1_t2 = st.multiselect('Which teams would you like to include in the correlation?', options = total_teams, key='corr_var1_t2')
+        elif split_var1_t2 == 'Specific Players':
+            corr_var1_t2 = st.multiselect('Which players would you like to include in the correlation?', options = total_players, key='corr_var1_t2')
+            
+        split_var2_t2 = st.radio("Would you like to view all dates or specific ones?", ('All', 'Specific Dates'), key='split_var3_t2')
+        
+        if split_var2_t2 == 'Specific Dates':
+            low_date_t2 = st.date_input('Min Date:', value=None, format="YYYY-MM-DD", key='low_date_t2')
+            if low_date_t2 is not None:
+                low_date_t2 = pd.to_datetime(low_date_t2).date()
+            high_date_t2 = st.date_input('Max Date:', value=None, format="YYYY-MM-DD", key='high_date_t2')
+            if high_date_t2 is not None:
+                high_date_t2 = pd.to_datetime(high_date_t2).date()
+        elif split_var2_t2 == 'All':
+            low_date_t2 = gamelog_table['Date'].min()
+            high_date_t2 = gamelog_table['Date'].max()
+        
+        min_var1_t2 = st.slider("Is there a certain minutes range you want to view?", 0, 60, (0, 60), key='min_var1_t2')
+    
+    with col2:
+        if split_var1_t2 == 'Specific Teams':
+            display = st.container()
+            gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date_t2]
+            gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date_t2]
+            gamelog_table = gamelog_table[gamelog_table['Min'] >= min_var1_t2[0]]
+            gamelog_table = gamelog_table[gamelog_table['Min'] <= min_var1_t2[1]]
+            gamelog_table = gamelog_table[gamelog_table['Team'].isin(corr_var1_t2)]
+            corr_display = run_corr(gamelog_table)
+            display.dataframe(corr_display.style.format(precision=2), use_container_width = True)  
+            
+        elif split_var1_t2 == 'Specific Players':
+            display = st.container()
+            gamelog_table = gamelog_table[gamelog_table['Date'] >= low_date_t2]
+            gamelog_table = gamelog_table[gamelog_table['Date'] <= high_date_t2]
+            gamelog_table = gamelog_table[gamelog_table['Min'] >= min_var1_t2[0]]
+            gamelog_table = gamelog_table[gamelog_table['Min'] <= min_var1_t2[1]]
+            gamelog_table = gamelog_table[gamelog_table['Player'].isin(corr_var1_t2)]
+            corr_display = run_corr(gamelog_table)
+            display.dataframe(corr_display.style.format(precision=2), use_container_width = True)