def METHOD_NAME(airline_df):
  arr = airline_df.rename(columns={
      'arrival_airport': 'airport'
  }).airport.value_counts()
  dep = airline_df.rename(columns={
      'departure_airport': 'airport'
  }).airport.value_counts()
  total = arr + dep
  # Note we keep all to include duplicates - this ensures the result is
  # deterministic.
  # NaNs can be included in the output in pandas 1.4.0 and above, so we
  # explicitly drop them.
  top_airports = total.nlargest(10, keep='all').dropna()
  at_top_airports = airline_df['arrival_airport'].isin(
      top_airports.index.values)
  return airline_df[at_top_airports].mean()