如何使用 pandas 根据之前的行值填充数据框？

问：

我有以下数据帧：

df = pd.DataFrame(data={
    "id": ['a', 'd'],
    "amount": [3000, 4000],
    "rate": [0.2, 0.3],
    "date": ["2022-07-21", "2022-08-11"],
    "months": [4, 5],
})

我想为给定的交易创建分期付款。输出应如下所示：

  id    interest   principal        date       balance  installment
0  a   50.000000  731.508250  2022-07-21  2.268492e+03   781.508250
1  a   37.808196  743.700055  2022-08-21  1.524792e+03   781.508250
2  a   25.413195  756.095055  2022-09-21  7.686966e+02   781.508250
3  a   12.811611  768.696640  2022-10-21  0.00000        781.508250
4  d  100.000000  760.987444  2022-08-11  3.239013e+03   860.987444
5  d   80.975314  780.012130  2022-09-11  2.459000e+03   860.987444
6  d   61.475011  799.512433  2022-10-11  1.659488e+03   860.987444
7  d   41.487200  819.500244  2022-11-11  8.399877e+02   860.987444
8  d   20.999694  839.987750  2022-12-11  0.00000        860.987444

这里的关键点是下一行值取决于前一行值。第一次是源数据帧。balancebalanceamount

我目前的解决方案：

import numpy_financial as npf
import pandas as pd
from dateutil.relativedelta import relativedelta

df = pd.DataFrame(data={
    "id": ['a', 'd'],
    "amount": [3000, 4000],
    "rate": [0.2, 0.3],
    "date": ["2022-07-21", "2022-08-11"],
    "months": [4, 5],
})


def get_output_df(df):
    columns = ["id", "interest", "principal", "date", "balance"]
    output_df = pd.DataFrame(columns=columns)

    for _, row in df.iterrows():
        rate = row["rate"] / 12
        months = row["months"]
        amount = row["amount"]
        date = pd.to_datetime(row["date"]).date()
        installment_amount = npf.pmt(rate=rate, nper=months, pv=-amount)
        prior_balance = amount

        loan_installment_data = []
        for i in range(months):
            interest_amount = rate * prior_balance
            principal_amount = installment_amount - interest_amount
            balance = prior_balance - principal_amount

            loan_installment_data.append(
                {
                    "id": row["id"],
                    "interest": interest_amount,
                    "principal": principal_amount,
                    "date": date,
                    "installment": installment_amount,
                    "balance": balance
                }
            )

            prior_balance = balance
            date += relativedelta(months=1)

        output_df = output_df.append(loan_installment_data, ignore_index=True)
    return output_df


output_df = get_output_df(df)

是否有任何 pandas 功能可用于执行相同的实现？