How to loop through a list of loans in Python to generate amortization schedule?

Question

I'm new to Python and am trying to generate an amortization schedule for a list of 400 loans. The final result only contains the loan_id and remaining_balance for each month end till the loan is paid off.

I found a post on amortize function and need help on how to loop through my list of loans.

My loan list looks like this:

Below is the code I currently using:

def amortize(loan_id, principal, remaining_balance, interest_rate, years, annual_payments=12, start_date=date.today()):

    pmt = -round(np.pmt(interest_rate/annual_payments, years*annual_payments, principal), 2)
    # initialize the variables to keep track of the periods and running balances
    p = 1
    beg_balance = remaining_balance
    end_balance = remaining_balance

    while end_balance > 0:

        # Recalculate the interest based on the current balance
        interest = round(((interest_rate/annual_payments) * beg_balance), 2)

        # Determine payment based on whether or not this period will pay off the loan
        pmt = min(pmt, beg_balance + interest)
        principal = pmt - interest

        # Ensure additional payment gets adjusted if the loan is being paid off
        end_balance = beg_balance - principal 

        yield OrderedDict([('Load ID', loan_id),
                           ('Month',start_date),
                           ('Period', p),
                           ('Begin Balance', beg_balance),
                           ('Payment', pmt),
                           ('Principal', principal),
                           ('Interest', interest),
                           ('End Balance', end_balance)])

        # Increment the counter, balance and date
        p += 1
        start_date += relativedelta(months=1)
        beg_balance = end_balance

I only know how to apply the amortize function to selected row but how can I write a loop to all my lists? (list is the name of my loan dataframe)

amo_schedule = pd.DataFrame(amortize(list['id'][0],
                                     list['origination'][0],
                                     list['remaining_balance'][0],
                                     list['interest'][0]/100,
                                     list['term'][0],
                                     start_date=date(2020,11,1)))

I got an error msg with the following code when I removed the index.

test = pd.DataFrame(amortize(list['id'],
                    list['origination'],
                    list['remaining_balance'],
                   list['interest'],
                   list['term'],
                    start_date=date(2020,11,1)))

ValueError                                Traceback (most recent call last)
<ipython-input-314-11e01c7c284f> in <module>
----> 1 test = pd.DataFrame(amortize(list['id'],
      2                     list['origination'],
      3                     list['remaining_balance'],
      4                    list['interest'],
      5                    list['term'],

~\Anaconda3\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy)
    500         elif isinstance(data, abc.Iterable) and not isinstance(data, (str, bytes)):
    501             if not isinstance(data, (abc.Sequence, ExtensionArray)):
--> 502                 data = list(data)
    503             if len(data) > 0:
    504                 if is_dataclass(data[0]):

<ipython-input-281-f6ccf21b26cb> in amortize(loan_id, principal, remaining_balance, interest_rate, years, annual_payments, start_date)
      7     end_balance = remaining_balance
      8 
----> 9     while end_balance > 0:
     10 
     11         # Recalculate the interest based on the current balance

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   1327 
   1328     def __nonzero__(self):
-> 1329         raise ValueError(
   1330             f"The truth value of a {type(self).__name__} is ambiguous. "
   1331             "Use a.empty, a.bool(), a.item(), a.any() or a.all()."

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().