我有一个员工报销费用的数据框架：

import pandas as pd

data = {'Claim ID': [1, 2, 3, 4, 5, 6, 7],
        'User': ['John', 'John', 'Jake', 'Bob', 'Bob', 'Tom', 'Tom'],
        'Category': ['Meal', 'Meal', 'Stationary', 'Phone Charges', 'Phone Charges', 'Transport', 'Transport'],
        'Amount': [12.00, 13.00, 20.00, 30, 30, 60, 60]}

df = pd.DataFrame(data)

Output:
     Claim ID  User       Category  Amount
            1  John           Meal    12.0
            2  John           Meal    13.0
            3  Jake     Stationary    20.0
            4   Bob  Phone Charges    30.0
            5   Bob  Phone Charges    30.0
            6   Tom      Transport    60.0
            7   Tom      Transport    60.0

我使用了以下代码查找基于User、Category和Amount的重复索赔，并为所发现的每组重复索赔赋予了一个唯一的组号：

# Tag each duplicate set with a unique number
conditions = ['User', 'Amount', 'Category']
df['Group'] = df.groupby(conditions).ngroup().add(1)

# Then remove groups with only one row
df = df[df.groupby('Group')['Group'].transform('count') > 1]

Output:
 Claim ID User       Category  Amount  Group
        4  Bob  Phone Charges    30.0      1
        5  Bob  Phone Charges    30.0      1
        6  Tom      Transport    60.0      5
        7  Tom      Transport    60.0      5

现在，我的问题是，我希望找到具有相同User、Category的重复项，但不是完全相同的Amount，我希望允许索赔金额有几美元的容差，比如1美元左右。因此，使用给定的样本 Dataframe ，预期输出如下所示：

Claim ID  User       Category  Amount  Group
        1  John           Meal    12.0      1
        2  John           Meal    13.0      1
        3   Tom      Transport    30.0      2
        4   Tom      Transport    30.0      2
        5   Bob  Phone Charges    60.0      3
        6   Bob  Phone Charges    60.0      3