Add player exposure formatting and enhance dataframe display in app.py

- Introduced a dictionary for player exposure formatting to standardize percentage displays across the application.
- Updated the logic for displaying player exposure percentages in the dataframe, applying background gradients for improved visual clarity.
- Ensured consistent handling of player counts by referencing the correct data frames for percentage calculations, enhancing overall data representation.

app.py

@@ -17,6 +17,8 @@ from global_func.highlight_rows import highlight_changes, highlight_changes_winn
 from global_func.load_csv import load_csv
 from global_func.find_csv_mismatches import find_csv_mismatches
 
+player_exposure_format = {'Exposure Overall': '{:.2%}', 'Exposure Top 1%': '{:.2%}', 'Exposure Top 5%': '{:.2%}', 'Exposure Top 10%': '{:.2%}', 'Exposure Top 20%': '{:.2%}'}
+
 tab1, tab2 = st.tabs(["Data Load", "Contest Analysis"])
 with tab1:
     if st.button('Clear data', key='reset1'):
@@ -195,13 +197,14 @@ with tab2:
         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 = ['Overall', ' Top 1%', ' Top 5%', 'Top 10%', 'Top 20%']
+        each_frame_set = [contest_players, players_1per, players_5per, players_10per, players_20per]
         with st.container():
             tab1, tab2 = st.tabs(['Player Used Info', 'Stack Used Info'])
             with tab1:
                 count_var = 0
                 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['Percent'] = set_frame['Count'] / len(each_frame_set[count_var])
                     set_frame = set_frame[['Player', 'Percent']]
                     set_frame = set_frame.rename(columns={'Percent': f'Exposure {each_set_name[count_var]}'})
                     if 'player_frame' not in st.session_state:
@@ -209,7 +212,7 @@ with tab2:
                     else:
                         st.session_state['player_frame'] = pd.merge(st.session_state['player_frame'], set_frame, on='Player', how='outer')
                     count_var += 1
-                st.dataframe(st.session_state['player_frame'])
+                st.dataframe(st.session_state['player_frame'].style.background_gradient(cmap='RgYlGn').format(player_exposure_format, precision=2), hide_index=True)
             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'})