def get_shorting_volume_by_date(fromdate, todate, ticker, market="KOSPI"): if isinstance(fromdate, datetime.datetime): fromdate = _datetime2string(fromdate) if isinstance(todate, datetime.datetime): todate = _datetime2string(todate) isin = krx.get_stock_ticker_isin(ticker) return krx.get_shorting_volume_by_date(fromdate, todate, isin, market)
def get_market_fundamental_by_date(fromdate, todate, ticker, freq='d'): isin = krx.get_stock_ticker_isin(ticker) df = krx.get_market_fundamental_by_date(fromdate, todate, isin) if df.empty: return df df['PBR'] = df['PER'] * df['EPS'] / df['BPS'] df.loc[df['BPS'] == 0, 'PBR'] = 0 how = { 'DIV': 'first', 'BPS': 'first', 'PER': 'first', 'EPS': 'first', 'PBR': 'first' } return resample_ohlcv(df, freq, how)
def get_market_fundamental_by_date(fromdate, todate, ticker, freq='d'): if isinstance(fromdate, datetime.datetime): fromdate = _datetime2string(fromdate) if isinstance(todate, datetime.datetime): todate = _datetime2string(todate) isin = krx.get_stock_ticker_isin(ticker) df = krx.get_market_fundamental_by_date(fromdate, todate, isin) if df.empty: return df df.columns.name = get_market_ticker_name(ticker) df['PBR'] = df['PER'] * df['EPS'] / df['BPS'] df.loc[df['BPS'] == 0, 'PBR'] = 0 how = {'DIV': 'first', 'BPS': 'first', 'PER': 'first', 'EPS': 'first', 'PBR': 'first'} return resample_ohlcv(df, freq, how)
def get_shorting_balance_by_ticker(fromdate, todate, ticker): isin = krx.get_stock_ticker_isin(ticker) mark = krx.get_stock_market_from(ticker) return krx.get_shorting_balance_by_ticker(fromdate, todate, isin, mark)
def get_shorting_status_by_date(fromdate, todate, ticker): isin = krx.get_stock_ticker_isin(ticker) return krx.get_shorting_status_by_date(fromdate, todate, isin)