如何通过切片选择某些列来替换NaN之后的groupby值？

import pandas as pd
import numpy as np

# 创建示例DataFrame
data = {
    'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
    'B': [1, 2, np.nan, 4, 5, np.nan, 7, 8],
    'C': [np.nan, 2, 3, np.nan, 5, 6, 7, np.nan]
}
df = pd.DataFrame(data)

print("原始DataFrame:")
print(df)

# 分组并替换NaN值
def fill_nan(group):
    group.fillna(group.mean(), inplace=True)
    return group

result = df.groupby('A').apply(fill_nan)

print("\n替换NaN后的DataFrame:")
print(result)

def fill_nan_median(group):
    group.fillna(group.median(), inplace=True)
    return group

result_median = df.groupby('A').apply(fill_nan_median)
print("\n使用中位数替换NaN后的DataFrame:")
print(result_median)