def _gen_real_prices(self):
''' Attempt to generate real prices. Returns None if prices cannot be found '''
prices = Ticker(f'{self.code}.AX').history(start=self.dates[0],
end=TOMORROW)
if isinstance(prices, dict):
return None
prices = prices.reset_index()[['date', 'close']].set_index('date')
prices.columns = ['price']
return prices
def load_data(codes, start=str(LAST_WEEK), end=TOMORROW, verbose=True):
''' Takes list of shares and returns data from the start date '''
daily = pd.DataFrame({'date': []})
codes = tqdm(codes) if verbose else codes
# Load data
for code in codes:
df = Ticker(f'{code}.AX').history(start=start, end=end).reset_index()[['date', 'close']]
df.columns = ['date', code]
daily = pd.merge(daily, df, on='date', how='outer')
daily['date'] = pd.to_datetime(daily.date)
daily = daily.sort_values('date').ffill().set_index('date')
return daily
# https://gist.github.com/rodrigobercini/8bbee7fc735ad7d696f7a2ec31df9610
from yahooquery import Ticker
# Período máximo
petr = Ticker("PETR4.SA")
petr.history(period='max')
# Datas específicas
petr.history(start='2005-05-01', end='2013-12-31')
# Intraday - 30 minutos
abev = Ticker('ABEV3.SA')
abev.history(period='60d', interval="30m")
# Intraday - 1 minuto
abev = abev.history(period='7d', interval="1m")
abev
# Informações financeiras
petr = Ticker("PETR4.SA") # Coleta dados
petr = petr.income_statement() # Chama função de Demonstração de resultados
petr = petr.transpose() # Transpõe a matriz
petr.columns = petr.iloc[0, :] # Renomeia colunas
petr = petr.iloc[2:, :-1] # Seleciona dados
petr = petr.iloc[:, ::-1] # Inverte colunas
petr
from yahooquery import Ticker
# financial report
petr = Ticker("PETR4.SA") # Pick up data
petr = petr.income_statement() # Call income statement function
petr = petr.transpose() # Transpor matrix
petr.columns = petr.iloc[0, :] # Rename columns
petr = petr.iloc[2:, :-1] # Select data
petr = petr.iloc[:, ::-1] # Invert columns
print(petr)
support_lines = None
for ta in tas:
data = Data()
data.support_lines = ta.resistance_lines("s")
data.resistance_lines = ta.resistance_lines("r")
ta.run(run, data)
plot_ta(ta)
current_price = ta.data['close'].iloc[-1]
support = last_resistance_line(ta.resistance_lines('s'))
support_distance = -(current_price - support) / current_price * 100
resistance = last_resistance_line(ta.resistance_lines('r'))
resistance_distance = (resistance -
current_price) / current_price * 100
print("{:4.2f} {:4.2f} {:4.2f} {:4.2f} {:4.2f}".format(
current_price, support, support_distance, resistance,
resistance_distance))
# plot_ta(ta)
print(symbol_list)
print(tickers[0].asset_profile)
exit(0)
# Informações financeiras
petr = Ticker("PETR4.SA")
petr = petr.income_statement()
petr = petr.transpose()
petr.columns = petr.iloc[0, :]
petr = petr.iloc[2:, :-1]
petr = petr.iloc[:, ::-1]
print(petr)
