Add Stack Priority filtering option in app.py to enhance user control over scoring percentages display. Users can now isolate data based on specific Stack Priority selections, improving data analysis capabilities.

app.py

@@ -280,7 +280,12 @@ with tab1:
     with st.expander("Info and Filters"):
         with st.container():
             slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate', 'Turbo Slate'), key='slate_var1')
-            own_var1 = st.radio("How would you like to display team ownership?", ('Sum', 'Average'), key='own_var1')
+            prio_split = st.radio("Do you want to isolate a specific Stack Priority?", ('Yes', 'No'), key='prio_split')
+            if prio_split == 'Yes':
+                prio_var = st.radio("Which Stack Priority are you looking for?", ['Outfield', 'Infield'], key='prio_var')
+            else:
+                prio_var = None
+
     
     if site_var == 'Draftkings':
         if slate_var1 == 'Main Slate':
@@ -360,6 +365,8 @@ with tab1:
         scoring_percentages = scoring_percentages.set_index('Names', drop=True)
         st.dataframe(scoring_percentages.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Own%']).format(game_format, precision=2), height=750, use_container_width = True)
     elif view_var == "Advanced":
+        if prio_var is not None:
+            scoring_percentages = scoring_percentages[scoring_percentages['Stack_Prio'] == prio_var]
         scoring_percentages = scoring_percentages.set_index('Names', drop=True)
         st.dataframe(scoring_percentages.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').background_gradient(cmap='RdYlGn_r', subset=['Avg_Salary', 'Own%']).format(game_format, precision=2), height=750, use_container_width = True)