import pandas as pd

df = pd.DateFrame(people)
print(df.sort_values(by=['last', 'first'], ascending = [False, True]).reset_index(drop = True))
# OR (they are equal)
print(df.sort_values(by=['last', 'first'], ascending = [False, True], ignore_index = True))

############################################
mpg.sort_values(ascending = False, inplace = True)
mpg.sort_index(inplace = True)

############################################
titanic.nlargest(n = 5, columns = 'fare')
titanic.nsmallest(n = 5, columns = 'fare')
cars.nlargest(n = 10, columns = "weight")

############################################
top_20_percent = df.nlargest(int(len(df) * 0.2), columns='column_name')

############################################
titanic.loc[titanic.age.idxmin()]