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Convert Plutus pdf statement to csv file with running balance
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| import re | |
| import sys | |
| import pandas as pd | |
| import pdfplumber | |
| re_transaction = re.compile( | |
| r'(Transaction|Card Transaction|Service Fee|Card Transfer)[\n\s](\d{4}/\d{2}/\d{2}, \d{2}:\d{2})\s+(-?\s?.\d*.?\d{0,2})\n?(.*)') | |
| re_deposit = re.compile(r'(Card Deposit|Deposit)[\n\s](\d{4}/\d{2}/\d{2}, \d{2}:\d{2})\s+(.\d*.?\d{0,2})()') | |
| re_page = re.compile(r'\n\d{1,2}/\d{1,2}/\d{4} \d+ / \d+') | |
| def clean_row(row): | |
| return [cell for cell in row if cell is not None and cell != ''] | |
| def parse(pdf_file_loc, csv_file_loc): | |
| with pdfplumber.open(pdf_file_loc) as pdf: | |
| content = '\n'.join([page.extract_text_simple() for page in pdf.pages]).replace('\xa0', ' ') | |
| columns = ['Type', 'Date', 'Amount', 'Transaction'] | |
| content = re_page.sub('', content) | |
| deposits = re_deposit.findall(content) | |
| transactions = re_transaction.findall(content) | |
| df = pd.DataFrame(deposits + transactions, columns=columns) | |
| df['Amount'] = df['Amount'].replace(r'^(-?)\s?.(\d*\.?\d{0,2})$', value=r"\1\2", regex=True).astype(float) | |
| df['Date'] = pd.to_datetime(df['Date'], format='%Y/%d/%m, %H:%M') | |
| df = df.set_index('Date').sort_index() | |
| df['Balance'] = df['Amount'].cumsum() | |
| print(df) | |
| df.to_csv(csv_file_loc, float_format="%.2f") | |
| if __name__ == '__main__': | |
| args = sys.argv[1:] | |
| parse(*args) |
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