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)
