Check if new column values in groupby of old column values

import pandas as pd

# create some data
data = [['Alex','A','B'],
        ['Alex','C','A'],
        ['Alex','B','A'],
        ['Amanda','A','B'],
        ['Amanda','C','D'],
        ['Amanda','B','A'],
        ['Aaron','A','A'],
        ['Aaron','B','C'],
        ['Aaron','C','A']]

# create dataframe
df = pd.DataFrame(data,columns=['Name','Old Grade','New Grade'])

# make copies of dataframe
df_old = df.copy()
df_new = df.copy()

# transform dataframe with list of old grades for each student
df_old['Old Grades List'] = df_old['Old Grade']
df_old = df_old[['Name','New Grade','Old Grades List']].groupby(['Name'])['Old Grades List'].apply(list).reset_index()

# transform dataframe with list of new grades for each student
df_new['New Grades List'] = df_new['New Grade']
df_new = df_new[['Name','New Grade','New Grades List']].groupby(['Name'])['New Grades List'].apply(list).reset_index()

# merge dataframes
df_result = pd.merge(df_old, df_new, how="outer", on=["Name"])

# add column to check if each new grade in is old grade list
df_result['Match'] = ~(df_result['New Grades List'].apply(set) - df_result['Old Grades List'].apply(set)).astype(bool)