There is a Pandas dataframe: performer hits chart_debut time_on_chart consecutive_weeks decade num_of_hits 3428 Glee Cast Somebody To Love, Friday, Loser Like Me, Baby,... 2009 290 47.0 2000-2010 191 8478 Taylor Swift Fifteen, Fearless, London Boy, Teardrops On My... 2008 14299 11880.0 2000-2010 166 2543 Drake Summer Sixteen, The Language, Weston Road Flow... 2016 7449 6441.0 2010-2020 125 10397 YoungBoy Never Broke Again Kacey Talk, Put It On Me, Dirty Iyanna, Lil To... 2020 1012 625.0 2020-2030 75 458 Aretha Franklin Chain Of Fools, My Song, Respect, Until You Co... 1967 3490 2921.0 1960-1970 66 8625 The Beatles Sgt. Pepper's Lonely Hearts Club Band/With A L... 1978 3548 2798.0 1970-1980 66 Write a year_leaders function that will build a new data frame and leave only the rows that have the maximum value of num_of_hits in it when grouped by the chart_debut column

df = pd.DataFrame({'chart_debut': ['2012', '2012', '2012', '2014', '2017'], 'num_of_hits': [1,2,3,4,5]})

def year_leaders(df):
  return df.groupby('chart_debut').max()
  
year_leaders(df)