Update player and stack counts display logic in app.py for improved clarity

- Added a new column for exposure percentages in player counts, enhancing the data representation for user analysis.
- Simplified the stack counts display by removing the count column, focusing on percentage exposure for better clarity.
- Ensured consistent naming conventions for exposure metrics across the application.

app.py

@@ -194,13 +194,15 @@ with tab2:
         player_5per_counts = pd.Series(list(players_5per[player_columns].values.flatten())).value_counts()
         player_10per_counts = pd.Series(list(players_10per[player_columns].values.flatten())).value_counts()
         player20_per_counts = pd.Series(list(players_20per[player_columns].values.flatten())).value_counts()
+        each_set_name = ['1%', '5%', '10%', '20%']
         with st.container():
             tab1, tab2 = st.tabs(['Player Used Info', 'Stack Used Info'])
             with tab1:
                 for each_set in [player_counts, player_1per_counts, player_5per_counts, player_10per_counts, player20_per_counts]:
                     set_frame = each_set.to_frame().reset_index().rename(columns={'index': 'Player', 'count': 'Count'})
                     set_frame['Percent'] = set_frame['Count'] / len(working_df)
-                    set_frame = set_frame[['Player', 'Count', 'Percent']]
+                    set_frame = set_frame[['Player', 'Percent']]
+                    set_frame = set_frame.rename(columns={'Percent': f'Exposure Top {each_set_name}'})
                     if 'player_frame' not in st.session_state:
                         st.session_state['player_frame'] = set_frame
                     else:
@@ -210,7 +212,7 @@ with tab2:
                 stack_counts = pd.Series(list(working_df['stack'])).value_counts()
                 stack_frame = stack_counts.to_frame().reset_index().rename(columns={'index': 'Stack', 'count': 'Count'})
                 stack_frame['Percent'] = stack_frame['Count'] / len(working_df)
-                stack_frame = stack_frame[['Stack', 'Count', 'Percent']]
+                stack_frame = stack_frame[['Stack', 'Percent']]
                 st.dataframe(stack_frame)