James McCool
Update sorting logic in distribute_preset function to sort 'median' in descending order for improved portfolio selection accuracy
b9ea55a
| import pandas as pd | |
| def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols: list): | |
| for slack_var in range(1, 20): | |
| concat_portfolio = pd.DataFrame(columns=portfolio.columns) | |
| for finishing_range in range(1, 20): | |
| rows_to_drop = [] | |
| working_portfolio = portfolio.copy() | |
| working_portfolio = working_portfolio[(working_portfolio['Finish_percentile'] <= (finishing_range / 100)) & (working_portfolio['Finish_percentile'] >= ((finishing_range - 1) / 100))].sort_values(by='median', ascending = False) | |
| working_portfolio = working_portfolio.reset_index(drop=True) | |
| curr_own_type_max = working_portfolio.loc[0, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[0, 'Weighted Own']) | |
| for i in range(1, len(working_portfolio)): | |
| if working_portfolio.loc[i, 'Weighted'] > curr_own_type_max: | |
| rows_to_drop.append(i) | |
| else: | |
| curr_own_type_max = working_portfolio.loc[i, 'Weighted'] + (slack_var / 20 * working_portfolio.loc[i, 'Weighted']) | |
| working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True) | |
| concat_portfolio = pd.concat([concat_portfolio, working_portfolio]) | |
| if len(concat_portfolio) >= lineup_target: | |
| return concat_portfolio.sort_values(by='Finish_percentile', ascending=True).head(lineup_target) | |
| return concat_portfolio.sort_values(by='Finish_percentile', ascending=True) | |