Update app.py

app.py

@@ -131,7 +131,7 @@ def seasonlong_build(data_sample):
     return season_long_table
 
 @st.cache_data(show_spinner=False)
-def run_corr(data_sample):
+def run_fantasy_corr(data_sample):
     cor_testing = data_sample
     cor_testing = cor_testing[cor_testing['Season'] == '22023']
     date_list = cor_testing['Date'].unique().tolist()
@@ -147,6 +147,23 @@ def run_corr(data_sample):
     
     return corrM
 
+@st.cache_data(show_spinner=False)
+def run_min_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['Min']))
+        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)]
@@ -259,6 +276,8 @@ with tab2:
                   total_players = indv_players.Player.values.tolist()
                   total_dates = gamelog_table.Date.values.tolist()
         
+        corr_var = st.radio("Are you correlating fantasy or minutes?", ('Fantasy', 'Minutes'), key='corr_var')
+        
         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':
@@ -284,20 +303,28 @@ with tab2:
     with col2:
         if split_var1_t2 == 'Specific Teams':
             display = st.container()
+            gamelog_table = gamelog_table.sort_values(by='Fantasy', ascending=False)
             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)
+            if corr_var == 'Fantasy':
+                corr_display = run_fantasy_corr(gamelog_table)
+            elif corr_var == 'Minutes':
+                corr_display = run_min_corr(gamelog_table)
             display.dataframe(corr_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=1000, use_container_width = True)
             
         elif split_var1_t2 == 'Specific Players':
             display = st.container()
+            gamelog_table = gamelog_table.sort_values(by='Fantasy', ascending=False)
             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)
+            if corr_var == 'Fantasy':
+                corr_display = run_fantasy_corr(gamelog_table)
+            elif corr_var == 'Minutes':
+                corr_display = run_min_corr(gamelog_table)
             display.dataframe(corr_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)