如何根据列值和不同的dataframe索引来计算pandas数据帧中的差异？

merged_df = pd.merge(df1, df2, on='key')

merged_df['diff'] = merged_df.apply(lambda row: row['col1_x'] - row['col1_y'], axis=1)

import pandas as pd

# 创建示例数据
data1 = {'key': ['A', 'B', 'C', 'D'],
         'col1': [1, 2, 3, 4]}
data2 = {'key': ['A', 'B', 'C', 'E'],
         'col1': [2, 2, 4, 5]}

df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

# 合并dataframe
merged_df = pd.merge(df1, df2, on='key')

# 计算差异
merged_df['diff'] = merged_df.apply(lambda row: row['col1_x'] - row['col1_y'], axis=1)

# 打印结果
print(merged_df)

  key  col1_x  col1_y  diff
0   A       1       2    -1
1   B       2       2     0
2   C       3       4    -1