There is a Pandas dataframe user_id name date hotel profit_per_room how_find_us resting_time rating 0 1 Ksenia Rodionova 2021-07-01 Alpina 1639.000000 by_recommendation 48 3.0 1 2 Ulyana Selezneva 2021-07-01 AquaMania 930.000000 by_airbnb.com 97 4.0 2 3 Konstantin Prokhorov 2021-07-01 Breeze 1057.720000 agg_trivago.com 173 4.0 3 4 Petrov Vladimir 2021-07-01 Moreon 1403.000000 agg_onlinetours.ru 229 4.0 4 5 Arina Selivanova 2021-07-01 Alpina 1639.000000 agg_sutochno.ru 63 4.0 Filter this dataframe and leave only the rows where the values in the name column are duplicated. Merge the rows with duplicates and sort the name column in ascending order

def filter_df(df, column):
  return df[df[column].duplicated(keep=False)].sort_values(column)
    
df = pd.DataFrame({'name': ['Ksenia Rodionova', 'Ulyana Selezneva', 'Konstantin Prokhorov',
                            'Petrov Vladimir', 'Arina Selivanova', 'Ksenia Rodionova'],
                   'profit_per_room': [1639.000000, 930.000000, 1057.720000, 1403.000000, 1639.000000, 1639.000000]})
    
filter_df(df, 'name')