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Python snippet to convert Revolut export to Wallet
import argparse
import datetime
import pandas as pd
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('input', help='Input revolut export file')
parser.add_argument('--output', default="rev2wall-{CURRENCY}-{TIMESTAMP}.csv", help='Input Revolut file')
return parser.parse_args()
def load_df(input_file):
_df = (pd
.read_csv(input_file, sep=';', parse_dates=['Completed Date '], thousands=',', na_values=[' '])
.rename(columns=lambda x: x.strip())
return _df
def get_currency(df):
return df.filter(like='Paid Out').columns[0][-4:-1]
def wrangle_format(_df, cur):
df = (_df
paid_out_currency=lambda x: x['Paid Out ({})'.format(cur)].astype(float),
paid_in_currency=lambda x: x['Paid In ({})'.format(cur)].astype(float),
amount=lambda x: x.paid_in_currency.where(x.paid_in_currency.notna(), -x.paid_out_currency),
date=lambda x: pd.to_datetime(x['Completed Date']).dt.strftime('%Y/%m/%d'),
note=lambda x: (x['Notes'] + ' ' + x['Category']).str.strip(),
type=lambda x: (x['paid_in_currency'].notna()).map({True: "Income", False: "Expense"}),
.rename(columns=lambda x: x.lower())
.filter(['date', 'currency', 'amount', 'note', 'type'])
return df
def main(input_file):
_df = load_df(input_file)
cur = get_currency(_df)
df = wrangle_format(_df, cur)
return df, cur
if __name__ == "__main__":
args = parse_args()
df, cur = main(args.input)
output = args.output.format(CURRENCY=cur,"%Y%m%dT%H%M%S"))
except KeyError:
output = args.output
df.to_csv(output, index=False, sep=";")
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troych commented Jul 25, 2019

Yeah, that's annoying. I guess that could be solved by changing thousands here.

Thanks, I've ended up doing it like this:

.read_csv(input_file, sep=';', parse_dates=['Completed Date '], decimal=',', na_values=['  '])

Works as intended now, thank you very much. :)

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