Enhance portfolio concatenation in distribute_preset function by increasing the limit to the top 10 entries and adding a step to remove duplicates based on 'median', 'salary', and 'Own' for improved data relevance and accuracy.

global_func/distribute_preset.py

@@ -27,7 +27,8 @@ def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols:
                     curr_own_type_max = working_portfolio.loc[i, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[i, 'Weighted Own'])
             
             working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
-            concat_portfolio = pd.concat([concat_portfolio, working_portfolio.head(5)])
+            concat_portfolio = pd.concat([concat_portfolio, working_portfolio.head(10)])
+            concat_portfolio = concat_portfolio.drop_duplicates(subset=['median', 'salary', 'Own'])
 
         if len(concat_portfolio) >= lineup_target:
             return concat_portfolio.sort_values(by='Finish_percentile', ascending=True).head(lineup_target)