Update app.py

app.py

@@ -520,29 +520,29 @@ with tab1:
                 summary_df = pd.DataFrame({
                     'Metric': ['Min', 'Average', 'Max'],
                     'Salary': [
-                        st.session_state.Sim_Winner_Display['salary'].min(),
-                        st.session_state.Sim_Winner_Display['salary'].mean(),
-                        st.session_state.Sim_Winner_Display['salary'].max()
+                        freq_copy['salary'].min(),
+                        freq_copy['salary'].mean(),
+                        freq_copy['salary'].max()
                     ],
                     'Proj': [
-                        st.session_state.Sim_Winner_Display['proj'].min(),
-                        st.session_state.Sim_Winner_Display['proj'].mean(),
-                        st.session_state.Sim_Winner_Display['proj'].max()
+                        freq_copy['proj'].min(),
+                        freq_copy['proj'].mean(),
+                        freq_copy['proj'].max()
                     ],
                     'Own': [
-                        st.session_state.Sim_Winner_Display['Own'].min(),
-                        st.session_state.Sim_Winner_Display['Own'].mean(),
-                        st.session_state.Sim_Winner_Display['Own'].max()
+                        freq_copy['Own'].min(),
+                        freq_copy['Own'].mean(),
+                        freq_copy['Own'].max()
                     ],
                     'Fantasy': [
-                        st.session_state.Sim_Winner_Display['Fantasy'].min(),
-                        st.session_state.Sim_Winner_Display['Fantasy'].mean(),
-                        st.session_state.Sim_Winner_Display['Fantasy'].max()
+                        freq_copy['Fantasy'].min(),
+                        freq_copy['Fantasy'].mean(),
+                        freq_copy['Fantasy'].max()
                     ],
                     'GPP_Proj': [
-                        st.session_state.Sim_Winner_Display['GPP_Proj'].min(),
-                        st.session_state.Sim_Winner_Display['GPP_Proj'].mean(),
-                        st.session_state.Sim_Winner_Display['GPP_Proj'].max()
+                        freq_copy['GPP_Proj'].min(),
+                        freq_copy['GPP_Proj'].mean(),
+                        freq_copy['GPP_Proj'].max()
                     ]
                 })
 
@@ -557,17 +557,17 @@ with tab1:
                     'Fantasy': '{:.2f}',
                     'GPP_Proj': '{:.2f}'
                 }).background_gradient(cmap='RdYlGn', axis=0, subset=['Salary', 'Proj', 'Own', 'Fantasy', 'GPP_Proj']), use_container_width=True)
-                
+
         with tab2:
             if 'Sim_Winner_Display' in st.session_state:
                 # Apply position mapping to FLEX column
-                flex_positions = st.session_state.Sim_Winner_Display['FLEX'].map(maps_dict['Pos_map'])
+                flex_positions = freq_copy['FLEX'].map(maps_dict['Pos_map'])
                 
                 # Count occurrences of each position in FLEX
                 flex_counts = flex_positions.value_counts()
                 
                 # Calculate average statistics for each FLEX position
-                flex_stats = st.session_state.Sim_Winner_Display.groupby(flex_positions).agg({
+                flex_stats = freq_copy.groupby(flex_positions).agg({
                     'proj': 'mean',
                     'Own': 'mean',
                     'Fantasy': 'mean',