James McCool
Refactor large_field_preset function to simplify ranking logic by removing median and finish percentile rankings, and adjust filtering criteria to focus on 'Finish_percentile' for team-based selection, enhancing accuracy in lineup targeting.
1107ea4
| import pandas as pd | |
| def large_field_preset(portfolio: pd.DataFrame, lineup_target: int): | |
| for slack_var in range(1, 20): | |
| concat_portfolio = pd.DataFrame(columns=portfolio.columns) | |
| for team in portfolio['Stack'].unique(): | |
| rows_to_drop = [] | |
| working_portfolio = portfolio.copy() | |
| working_portfolio = working_portfolio[working_portfolio['Stack'] == team].sort_values(by='median', ascending = False) | |
| working_portfolio = working_portfolio.reset_index(drop=True) | |
| curr_own_type_max = working_portfolio.loc[0, 'Finish_percentile'] + (slack_var / 20 * working_portfolio.loc[0, 'Finish_percentile']) | |
| for i in range(1, len(working_portfolio)): | |
| if working_portfolio.loc[i, 'Finish_percentile'] < curr_own_type_max: | |
| rows_to_drop.append(i) | |
| else: | |
| curr_own_type_max = working_portfolio.loc[i, 'Finish_percentile'] + (slack_var / 20 * working_portfolio.loc[i, 'Finish_percentile']) | |
| 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) | |