Optimize player frequency table generation in tab2

- Modify DataFrame creation to add salary column after initial setup
- Reorder columns for better readability
- Set player name as index for improved table display
- Apply changes consistently for both Regular and Showdown slate frequency tables

app.py

@@ -385,13 +385,15 @@ with tab2:
                     # Create a DataFrame with the results
                     summary_df = pd.DataFrame({
                         'Player': value_counts.index,
-                        'Salary': value_counts.index.map(player_salaries),
                         'Frequency': value_counts.values,
                         'Percentage': percentages.values
                     })
                     
                     # Sort by frequency in descending order
+                    summary_df['Salary'] = summary_df['Player'].map(player_salaries)
+                    summary_df = summary_df[['Player', 'Salary', 'Frequency', 'Percentage']]
                     summary_df = summary_df.sort_values('Frequency', ascending=False)
+                    summary_df = summary_df.set_index('Player')
                     
                     # Display the table
                     st.write("Player Frequency Table:")
@@ -418,13 +420,15 @@ with tab2:
                     # Create a DataFrame with the results
                     summary_df = pd.DataFrame({
                         'Player': value_counts.index,
-                        'Salary': value_counts.index.map(player_salaries),
                         'Frequency': value_counts.values,
                         'Percentage': percentages.values
                     })
                     
                     # Sort by frequency in descending order
+                    summary_df['Salary'] = summary_df['Player'].map(player_salaries)
+                    summary_df = summary_df[['Player', 'Salary', 'Frequency', 'Percentage']]
                     summary_df = summary_df.sort_values('Frequency', ascending=False)
+                    summary_df = summary_df.set_index('Player')
                     
                     # Display the table
                     st.write("Seed Frame Frequency Table:")