def worth_at_date(money_transactions, date):
df = prg.to_dataframe(money_transactions)
qs = df[df.dt_date <= date].groupby(["owner", "ticker"]).quantity.sum()
return str(
pd.DataFrame(qs)
.apply(lambda x: cv.in_CZK(date, x.name[1]) * x.quantity, axis=1)
.reset_index()
.groupby("owner")
.sum()
)
def appreciation(money_transactions, stocks, owner):
m = prg.to_dataframe(money_transactions)
m = m[m.owner == owner]
m['neg'] = m.apply(lambda x: (x.quantity * (-1)), axis=1)
subset = m[['dt_date', 'neg']]
investments = [tuple(x) for x in subset.values]
assets = st.worth_at_date_czk(stocks, date.today())
assets = assets.loc[owner]
assets = assets.iloc[0]
assetss = (date.today(), assets)
investments.append(assetss)
return xirr(investments)
def read_file(transaction_file):
return prg.to_dataframe(rt.read_file(transaction_file))
def invested(money_transactions):
df = prg.to_dataframe(money_transactions)
byowner = df.groupby("owner")
return str(byowner["quantity"].sum())
def sum_money(money_transactions):
dt = prg.to_dataframe(money_transactions)
dt["cum_sum"] = dt.quantity.cumsum()
return dt
def test_transaction_at_missing_inter():
df = prg.to_dataframe(rt.read_file('transactions'))
tr = prg.transaction_at("2014-04-09", df)
field_by_field_equal(tr, example_dict_inter)
def test_transaction_at_direct():
df = prg.to_dataframe(rt.read_file('transactions'))
tr = prg.transaction_at("2014-04-10", df)
field_by_field_equal(tr, example_dict)
