如何合并多个Groupby Dataframe和更改列名--获取NAs

import pandas as pd

# 假设有两个Groupby Dataframe df1 和 df2
df1 = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar'],
                    'B': ['one', 'one', 'two', 'two'],
                    'C': [1, 2, 3, 4]})
df2 = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar'],
                    'B': ['one', 'one', 'two', 'two'],
                    'D': [5, 6, 7, 8]})

# 对每个Dataframe进行分组操作
grouped_df1 = df1.groupby(['A', 'B']).sum()
grouped_df2 = df2.groupby(['A', 'B']).sum()

# 合并多个Groupby Dataframe
merged_df = pd.merge(grouped_df1, grouped_df2, left_index=True, right_index=True)

# 更改列名
merged_df.columns = ['New_Column_1', 'New_Column_2']

# 打印合并后的Dataframe
print(merged_df)

# 假设merged_df中存在NAs
# 使用0填充NAs
filled_df = merged_df.fillna(0)

# 使用平均值填充NAs
mean_value = merged_df.mean()
filled_df = merged_df.fillna(mean_value)

# 打印填充后的Dataframe
print(filled_df)