如何获取pandas数据帧重复行的聚合统计？

import pandas as pd

# 创建一个示例DataFrame
data = {
    'A': [1, 2, 2, 3, 4, 4],
    'B': [10, 20, 20, 30, 40, 40],
    'C': [100, 200, 200, 300, 400, 400]
}
df = pd.DataFrame(data)

# 找出重复行
duplicates = df[df.duplicated(keep=False)]

# 对重复行进行聚合统计
aggregated_stats = duplicates.groupby(df.columns.tolist()).agg({
    'A': ['sum', 'mean'],
    'B': ['sum', 'mean'],
    'C': ['sum', 'mean']
})

print(aggregated_stats)

aggregated_stats = duplicates.dropna().groupby(df.columns.tolist()).agg({
    'A': ['sum', 'mean'],
    'B': ['sum', 'mean'],
    'C': ['sum', 'mean']
})

def custom_agg(x):
    return x.max() - x.min()

aggregated_stats = duplicates.groupby(df.columns.tolist()).agg({
    'A': ['sum', 'mean', custom_agg],
    'B': ['sum', 'mean', custom_agg],
    'C': ['sum', 'mean', custom_agg]
})