from sepa import parser
import re
import csv
import pandas as pd
import numpy as np

# Utility function to remove additional namespaces from the XML
def strip_namespace(xml):
    return re.sub(' xmlns="[^"]+"', '', xml, count=1)

# Read file
with open('test.xml', 'r') as f:
    input_data = f.read()

# Parse the bank statement XML to dictionary
camt_dict = parser.parse_string(parser.bank_to_customer_statement, bytes(strip_namespace(input_data), 'utf8'))

statements = pd.DataFrame.from_dict(camt_dict['statements'])
all_entries = []

for i, _ in statements.iterrows():
    if 'entries' in camt_dict['statements'][i]:
        df = pd.DataFrame()
        dd = pd.DataFrame.from_records(camt_dict['statements'][i]['entries'])
        dg = dd['entry_details']
        df['Date'] = dd['value_date'].str['date']
        df['Date'] = pd.to_datetime(df['Date']).dt.strftime('%d-%m-%Y')
        iban = camt_dict['statements'][i]['account']['id']['iban']
        df['IBAN'] = iban
        df['Currency'] = dd['amount'].str['currency']

        # Sort Credit/Debit in separate Columns
        df['Credit'] = np.where(dd['credit_debit_indicator'] == 'CRDT', dd['amount'].str['_value'], '')
        df['Debit'] = np.where(dd['credit_debit_indicator'] == 'DBIT', dd['amount'].str['_value'], '')

        # Get destination IBAN
        getlength = len(dg.index) #2
        
        for i in range(0, getlength):
            result = str(dd['entry_details'][i])
            print(result + "Resultat " + str(i))
            search_for_iban = re.search("CH\d{2}[ ]\d{4}[ ]\d{4}[ ]\d{4}[ ]\d{4}[ ]\d{1}|CH\d{19}", result)
            if(search_for_iban is None):
                print('the search is none')
                df['Test'] = 'None'
            else:
                print('the search is a match')
                df['Test'] = 'Yes'

        all_entries.append(df)

df_entries = pd.concat(all_entries)
print(df_entries)

我的问题就出在这段代码上

for i in range(0, getlength):
            result = str(dd['entry_details'][i])
            search_for_iban = re.search("CH\d{2}[ ]\d{4}[ ]\d{4}[ ]\d{4}[ ]\d{4}[ ]\d{1}|CH\d{19}", result)
            
            if(search_for_iban is None):
                df['Test'] = 'None'
            else:
                df['Test'] = search_for_iban.group()

        all_entries.append(df)

我已经尝试过通过索引来解决各种问题，这在变量i中的计数也很高，并且getlength对于2个条目也是正确的

我期待什么如果在'search_for_iban'（使用正则表达式查找（re.search））中有一个IBAN号码与第2行匹配，我希望该iban仅在第2行（ Dataframe ）“测试”如下：

what i expect

我得到了什么我得到了第1行和第2行中的两个条目，尽管在第1行中没有找到。我忽略了什么，我的头很痛！：D

what i got
我想我在正常的for循环和panda条目之间犯了一个思维错误