如何比较不同列具有不同容差值的两个数据帧？

import pandas as pd

# 示例数据帧
df1 = pd.DataFrame({
    'A': [1.0, 2.0, 3.0],
    'B': [10.0, 20.0, 30.0]
})

df2 = pd.DataFrame({
    'A': [1.05, 2.02, 3.01],
    'B': [10.5, 20.3, 30.2]
})

# 定义每列的容差值
tolerances = {
    'A': 0.1,
    'B': 1.0
}

# 比较函数
def compare_with_tolerance(row1, row2, tolerances):
    results = {}
    for col in tolerances:
        abs_tol = tolerances[col]
        rel_tol = abs_tol / max(abs(row1[col]), abs(row2[col]))
        if abs(row1[col] - row2[col]) <= abs_tol or abs(row1[col] - row2[col]) <= rel_tol * max(abs(row1[col]), abs(row2[col])):
            results[col] = True
        else:
            results[col] = False
    return pd.Series(results)

# 应用比较函数
comparison_result = df1.apply(lambda row: compare_with_tolerance(row, df2.loc[row.name], tolerances), axis=1)
print(comparison_result)

       A      B
0   True   True
1   True   True
2   True   True