Groupby最大值并返回pandas dataframe中对应的行

import pandas as pd

data = {'Name': ['Tom', 'Nick', 'John', 'Tom', 'Nick', 'John'],
        'Age': [20, 21, 19, 22, 23, 20],
        'Score': [85, 90, 92, 88, 87, 94]}
df = pd.DataFrame(data)

max_scores = df.groupby('Name').agg({'Score': 'max'})

result = pd.merge(df, max_scores, on=['Name', 'Score'])

import pandas as pd

data = {'Name': ['Tom', 'Nick', 'John', 'Tom', 'Nick', 'John'],
        'Age': [20, 21, 19, 22, 23, 20],
        'Score': [85, 90, 92, 88, 87, 94]}
df = pd.DataFrame(data)

max_scores = df.groupby('Name').agg({'Score': 'max'})
result = pd.merge(df, max_scores, on=['Name', 'Score'])

print(result)

   Name  Age  Score
0   Tom   22     88
1  Nick   23     87
2  John   19     94