Convert Plutus pdf statement to csv file with running balance

plutus_statement_to_csv.py

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)