def parse_option_data_by_symbol(self, symbol):
df = pd.read_hdf(self.option_data_file, symbol)
if df is not None:
print '{} data exists, parse it to object...'.format(symbol)
equity = Equity()
equity.symbol = symbol
equity.tradeTime = self.trade_date
self.equity_records.append(equity)
for index, row in df.iterrows():
equity.lastPrice = row['Underlying_Price']
option = Option()
option.symbol = symbol
option.tradeTime = self.trade_date,
option.expirationDate = row['Expiry']
option.optionType = row['Type']
option.strikePrice = row['Strike']
option.bidPrice = row['Bid']
option.lastPrice = row['Last']
option.priceChange = row['Change']
option.volatility = row['ImpliedVolatility']
option.theoretical = row['TheoreticalValue']
option.delta = row['Delta']
option.gamma = row['Gamma']
option.rho = row['Rho']
option.theta = row['Theta']
option.vega = row['Vega']
option.openInterest = row['Open Int']
option.volume = row['Volume']
self.option_records.append(option)
else:
print 'Missing data for {} ...'.format(symbol)
def combine_records(symbol, records):
equity = Equity()
equity.symbol = symbol
equity.tradeTime = records[-1][0]
equity.openPrice = records[0][1]
equity.highPrice = max(map(lambda x:x[2], records))
equity.lowPrice = min(map(lambda x:x[3],records))
equity.lastPrice = records[-1][4]
volume = sum(filter(lambda y: y is not None, map(lambda x: x[5], records)))
if volume != 0:
equity.volume = volume
return equity