Update correlation functions to use dynamic season parameter and adjust calls in correlation matrix display logic.

src/streamlit_app.py

@@ -236,7 +236,7 @@ def seasonlong_build(data_sample):
 @st.cache_data(show_spinner=False)
 def run_fantasy_corr(data_sample, season):
     cor_testing = data_sample
-    # cor_testing = cor_testing[cor_testing['Season'] == '22024']
+    cor_testing = cor_testing[cor_testing['Season'] == season]
     date_list = cor_testing['Date'].unique().tolist()
     player_list = cor_testing['Player'].unique().tolist()
     corr_frame = pd.DataFrame()
@@ -251,9 +251,9 @@ def run_fantasy_corr(data_sample, season):
     return corrM
 
 @st.cache_data(show_spinner=False)
-def run_min_corr(data_sample):
+def run_min_corr(data_sample, season):
     cor_testing = data_sample
-    # cor_testing = cor_testing[cor_testing['Season'] == '22024']
+    cor_testing = cor_testing[cor_testing['Season'] == season]
     date_list = cor_testing['Date'].unique().tolist()
     player_list = cor_testing['Player'].unique().tolist()
     corr_frame = pd.DataFrame()
@@ -486,9 +486,9 @@ if selected_tab == 'Correlation Matrix':
             working_data = working_data[working_data['spread'] <= spread_var1_t2[1]]
             working_data = working_data[working_data['Team'].isin(corr_var1_t2)]
             if corr_var == 'Fantasy':
-                corr_display = run_fantasy_corr(working_data)
+                corr_display = run_fantasy_corr(working_data, '22025')
             elif corr_var == 'Minutes':
-                corr_display = run_min_corr(working_data)
+                corr_display = run_min_corr(working_data, '22025')
             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':
@@ -502,9 +502,9 @@ if selected_tab == 'Correlation Matrix':
             working_data = working_data[working_data['spread'] <= spread_var1_t2[1]]
             working_data = working_data[working_data['Player'].isin(corr_var1_t2)]
             if corr_var == 'Fantasy':
-                corr_display = run_fantasy_corr(working_data)
+                corr_display = run_fantasy_corr(working_data, '22025')
             elif corr_var == 'Minutes':
-                corr_display = run_min_corr(working_data)
+                corr_display = run_min_corr(working_data, '22025')
             display.dataframe(corr_display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
         st.download_button(
                 label="Export Correlations Model",