基于两个数据帧的列的条件平均值

import pandas as pd

# 示例数据帧
data1 = {'A': [1, 2, 3], 'B': [4, 5, 6]}
data2 = {'A': [7, 8, 9], 'B': [10, 11, 12]}
df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

# 合并数据帧
df_merged = pd.concat([df1, df2], ignore_index=True)

# 单条件平均值
condition_single = df_merged['A'] > 5
average_single = df_merged.loc[condition_single, 'B'].mean()
print(f"单条件平均值（A > 5）: {average_single}")

# 多条件平均值
condition_multi = (df_merged['A'] > 3) & (df_merged['B'] < 11)
average_multi = df_merged.loc[condition_multi, 'A'].mean()
print(f"多条件平均值（A > 3 且 B < 11）: {average_multi}")

df_merged = pd.concat([df1, df2], ignore_index=True)

condition_single = df_merged['A'] > 5  # 确保条件正确

average_single = df_merged.loc[condition_single, 'B'].dropna().mean()