合并具有匹配和不同列的多个数据帧，并将NA

import pandas as pd
import numpy as np

# 示例数据帧
df1 = pd.DataFrame({
    'key': ['A', 'B', 'C', 'D'],
    'value1': [1, 2, np.nan, 4]
})

df2 = pd.DataFrame({
    'key': ['B', 'D', 'E', 'F'],
    'value2': [5, np.nan, 7, 8]
})

# 内连接
inner_join_df = pd.merge(df1, df2, on='key', how='inner')
print("Inner Join:\n", inner_join_df)

# 外连接
outer_join_df = pd.merge(df1, df2, on='key', how='outer')
print("Outer Join:\n", outer_join_df)

# 左连接
left_join_df = pd.merge(df1, df2, on='key', how='left')
print("Left Join:\n", left_join_df)

# 右连接
right_join_df = pd.merge(df1, df2, on='key', how='right')
print("Right Join:\n", right_join_df)

# 处理NA值
# 例如，用0填充所有NA值
filled_df = outer_join_df.fillna(0)
print("Filled DataFrame:\n", filled_df)