Pandas DateOffset 复制其他列

Question

我有一个数据框，其中包含提供给账户 (account_id) 的贷款 (loan_id)、贷款期限 (loan_duration) 和每月还款额 (monthly_loan_payment).

最后，我想提取每个客户每个月的月付款总和。为了到达那里，我试图提取一个数据框，该数据框为我提供 account_id、每笔贷款的月份和每月还款额及其持续时间的每个月。假设一笔贷款是在 07/1993 发放的，每月支付 1000 美元，期限为 12 个月，我想 return 与 account_id、loan_id 和贷款期限 12 个月中每一个月的每月付款信息。 df 中的每笔贷款都相同。

我尝试了 df.groupby('account_id').apply(lambda x: x['date'] + pd.DateOffset(months = x['loan_duration'], axis=1)['monthly_payment'] 但没有成功。如何在每一行上进行日期偏移，同时复制其他列的内容？

Answer 1

您可以为每笔贷款创建一个 pd.date_range 并使用 df.explode 获取所有单独的付款。

# sample data
# please always provide a callable line of code with your data
# you can get it with `df.head().to_dict('split')`
df = pd.DataFrame({
    'account_id': [1, 1, 2, 3, 3],
    'loan_id': [1, 2, 3, 4, 5],
    'date': ['1993-07-01', '1993-08-01', '1993-09-01', '1993-09-01', '1993-09-01'],
    'loan_duration_months': [12, 6, 5, 10, 10],
    'monthly_payment': [1000, 500, 1000, 1000, 1000]
})
df['date'] = pd.to_datetime(df['date'])

df['payment_date'] = [
    pd.date_range(start, periods=duration, freq='M')
    for start, duration in zip(df['date'], df['loan_duration_months'])
]
df = df.explode('payment_date', ignore_index=True)

输出

    account_id  loan_id       date  loan_duration_months  monthly_payment payment_date
0            1        1 1993-07-01                    12             1000   1993-07-31
1            1        1 1993-07-01                    12             1000   1993-08-31
2            1        1 1993-07-01                    12             1000   1993-09-30
3            1        1 1993-07-01                    12             1000   1993-10-31
4            1        1 1993-07-01                    12             1000   1993-11-30
5            1        1 1993-07-01                    12             1000   1993-12-31
6            1        1 1993-07-01                    12             1000   1994-01-31
7            1        1 1993-07-01                    12             1000   1994-02-28
8            1        1 1993-07-01                    12             1000   1994-03-31
9            1        1 1993-07-01                    12             1000   1994-04-30
10           1        1 1993-07-01                    12             1000   1994-05-31
11           1        1 1993-07-01                    12             1000   1994-06-30
12           1        2 1993-08-01                     6              500   1993-08-31
13           1        2 1993-08-01                     6              500   1993-09-30
14           1        2 1993-08-01                     6              500   1993-10-31
15           1        2 1993-08-01                     6              500   1993-11-30
16           1        2 1993-08-01                     6              500   1993-12-31
17           1        2 1993-08-01                     6              500   1994-01-31
18           2        3 1993-09-01                     5             1000   1993-09-30
19           2        3 1993-09-01                     5             1000   1993-10-31
20           2        3 1993-09-01                     5             1000   1993-11-30
21           2        3 1993-09-01                     5             1000   1993-12-31
22           2        3 1993-09-01                     5             1000   1994-01-31
23           3        4 1993-09-01                    10             1000   1993-09-30
24           3        4 1993-09-01                    10             1000   1993-10-31
25           3        4 1993-09-01                    10             1000   1993-11-30
26           3        4 1993-09-01                    10             1000   1993-12-31
27           3        4 1993-09-01                    10             1000   1994-01-31
28           3        4 1993-09-01                    10             1000   1994-02-28
29           3        4 1993-09-01                    10             1000   1994-03-31
30           3        4 1993-09-01                    10             1000   1994-04-30
31           3        4 1993-09-01                    10             1000   1994-05-31
32           3        4 1993-09-01                    10             1000   1994-06-30
33           3        5 1993-09-01                    10             1000   1993-09-30
34           3        5 1993-09-01                    10             1000   1993-10-31
35           3        5 1993-09-01                    10             1000   1993-11-30
36           3        5 1993-09-01                    10             1000   1993-12-31
37           3        5 1993-09-01                    10             1000   1994-01-31
38           3        5 1993-09-01                    10             1000   1994-02-28
39           3        5 1993-09-01                    10             1000   1994-03-31
40           3        5 1993-09-01                    10             1000   1994-04-30
41           3        5 1993-09-01                    10             1000   1994-05-31
42           3        5 1993-09-01                    10             1000   1994-06-30

Pandas DateOffset 复制其他列

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