new_contents: import pandas as pd
  import matplotlib.pyplot as plt
  import seaborn as sns
  from clean_and_std import clean_std
  
  # load csv files
  players = pd.read_csv('Master.csv')
  hall_of_fame = pd.read_csv('HallOfFame.csv')
  salaries = pd.read_csv('Salaries.csv')
  batting = pd.read_csv('Batting.csv')
  
  
  # eliminate stats for players with low batting stats(i.e. pitchers)
  batting = batting[batting['RBI'] > 15]
  
  # player born after 1980 dataframe
  after_1980 = players[players['birthYear'] > 1980]
  # merge with salaries dataframe
  after_1980_salaries = after_1980.merge(salaries, on='playerID', how='left')
  # extract the top paid 15%
  top15 = after_1980_salaries[after_1980_salaries.salary > after_1980_salaries.salary.quantile(.85)]
  
  top_stats = clean_std(top15, batting, 'playerID', 'salary', 'RBI')
  # add Hall of Fame boolean column
  top_stats['HallOfFame'] = pd.Series([False] * len(top_stats['salary']), dtype=bool)
  
  
  # hall of fame players
  hall_salaries = hall_of_fame.merge(salaries, on='playerID', how='inner')
  hall_stats = clean_std(hall_salaries, batting, 'playerID', 'salary', 'RBI')
  # add Hall of Fame boolean column
  hall_stats['HallOfFame'] = pd.Series([True] * len(hall_stats['salary']), dtype=bool)
  
  # combine dataframes
  combine = top_stats.merge(hall_stats, how='outer')
  
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