import pandas as pd

def create_stack_exposures(df: pd.DataFrame, entrants: list = None):
    stack_exposures = pd.DataFrame()
    if entrants is not None:
        overall_stacks = pd.Series(list(df[df['BaseName'].isin(entrants)]['stack'])).value_counts()
    else:
        overall_stacks = pd.Series(list(df['stack'])).value_counts()
    top_1per_stacks = pd.Series(list(df[df['percentile_finish'] <= 0.01]['stack'])).value_counts()
    top_5per_stacks = pd.Series(list(df[df['percentile_finish'] <= 0.05]['stack'])).value_counts()
    top_10per_stacks = pd.Series(list(df[df['percentile_finish'] <= 0.10]['stack'])).value_counts()
    top_20per_stacks = pd.Series(list(df[df['percentile_finish'] <= 0.20]['stack'])).value_counts()
    stacks_contest_len = len(df)
    stacks_len_1per = len(df[df['percentile_finish'] <= 0.01])
    stacks_len_5per = len(df[df['percentile_finish'] <= 0.05])
    stacks_len_10per = len(df[df['percentile_finish'] <= 0.10])
    stacks_len_20per = len(df[df['percentile_finish'] <= 0.20])
    each_set_name = ['Overall', ' Top 1%', ' Top 5%', 'Top 10%', 'Top 20%']
    each_stacks_set = [overall_stacks, top_1per_stacks, top_5per_stacks, top_10per_stacks, top_20per_stacks]
    each_stacks_len_set = [stacks_contest_len, stacks_len_1per, stacks_len_5per, stacks_len_10per, stacks_len_20per]
    stack_count_var = 0
    for each_stack in each_stacks_set:
        stack_frame = each_stack.to_frame().reset_index().rename(columns={'index': 'Stack', 'count': 'Count'})
        stack_frame['Percent'] = stack_frame['Count'] / each_stacks_len_set[stack_count_var]
        stack_frame = stack_frame[['Stack', 'Percent']]
        stack_frame = stack_frame.rename(columns={'Percent': f'Exposure {each_set_name[stack_count_var]}'})
        if len(stack_exposures) == 0:
            stack_exposures = stack_frame
        else:
            stack_exposures = pd.merge(stack_exposures, stack_frame, on='Stack', how='outer')
        stack_count_var += 1

    return stack_exposures