Pandas DataFrame currency conversion

Question

I have DataFrame with two columns:

col1     | col2

20         EUR
31         GBP
5          JPY

I may have 10000 rows like this

How to do fast currency conversion to base currency being GBP?

should I use easymoney? I know how to apply conversion to single row but I do not know how to iterate through all the rows fast.

EDIT: I would like to apply sth as:

def convert_currency(amount, currency_symbol):
    converted = ep.currency_converter(amount=1000, from_currency=currency_symbol, to_currency="GBP")
    return converted


df.loc[df.currency != 'GBP', 'col1'] = convert_currency(currency_data.col1, df.col2
                                                                                  )

but it does not work yet.

Overwrite the said row, something like this `df['col1'] = formulae*df['col1']`. I think so — aspo, Sep 14 '17 at 20:49
is there no fast option to intake currency ratios with pandas ? what is I have 30 diff currencies? — , Sep 14 '17 at 20:56

Dan · Answer 1 · 2017-09-14T22:20:26.950

1

Join a third column with the conversion rates for each currency, joining on the currency code in col2. Then create a column with the translated amount.

dfRate:
code | rate
EUR    1.123
USD    2.234

df2 = pd.merge(df1, dfRate, how='left', left_on=['col2'], right_on=['code'])

df2['translatedAmt'] = df2['col1'] / df2['rate']

edited Sep 14 '17 at 22:20

answered Sep 14 '17 at 21:40

Dan

651
7
11

it does it only for the first 'x' column where 'x' equals len of dfRate. – Sep 14 '17 at 22:03
for all following columns it inputs NaN – Sep 14 '17 at 22:04
Are you iterating through either of the DataFrames? – Dan Sep 14 '17 at 22:25

score 1 · Answer 2 · answered Sep 14 '17 at 23:17

df = pd.DataFrame([[20, 'EUR'], [31, 'GBP'], [5, 'JPY']], columns=['value', 'currency'])
print df

   value currency
0     20      EUR
1     31      GBP
2      5      JPY

def convert_to_gbp(args):  # placeholder for your fancy conversion function
    amount, currency = args
    rates = {'EUR': 2, 'JPY': 10, 'GBP': 1}
    return rates[currency] * amount

df.assign(**{'In GBP': df.apply(convert_to_gbp, axis=1)})

   value currency  In GBP
0     20      EUR      40
1     31      GBP      31
2      5      JPY      50

Pandas DataFrame currency conversion

2 Answers2

Linked