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import pandas as pd
def small_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[portfolio['Stack'] == team].sort_values(by='Own', ascending = False).reset_index(drop=True)
working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= .10]
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 Own'] > curr_own_type_max:
rows_to_drop.append(i)
else:
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])
if len(concat_portfolio) >= lineup_target:
return concat_portfolio.sort_values(by='Own', ascending=False).head(lineup_target)
return concat_portfolio.sort_values(by='Own', ascending=False)
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