Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
import pandas as pd import numpy as np class AdaptableYellowGreenElephant(QCAlgorithm): def Initialize(self): self.SetStartDate(2020, 11, 12) # Set Start Date self.SetEndDate(2020, 11, 12) # Set End Date self.SetCash(100000) # Set Strategy Cash self.AddEquity("IBM", Resolution.Daily) self.AddEquity("AAPL", Resolution.Daily) self.flag=True def OnData(self, data): if self.flag: self.index = pd.MultiIndex.from_tuples([('zone', 'a'), ('zone', 'b'), ('two', 'a'), ('two', 'b')]) self.s = pd.Series(np.arange(1.0, 5.0), index=self.index) self.Log ("\n"+"Dataframe on pandas"+ "\n"+str(self.s)+"\n") self.u=self.s.unstack(level=0) self.Log ("\n"+"Whos is dataframe.unstack at level=0 on pandas"+ "\n"+str(self.u)+"\n") self.dataframe = self.History([self.Symbol("IBM"), self.Symbol("AAPL")], 2) self.Log ("\n"+"Dataframes on history"+ "\n"+str(self.dataframe)+"\n") self.unc=self.dataframe["close"] self.Log ("\n"+"Dataframes close price on history, no unstack done yet"+ "\n"+str(self.unc)+"\n") self.uncz= self.dataframe["close"].unstack(level=0) self.Log ("\n"+"Unstacking close price at level=0 (aka dataframe(close price).unstack at level=0 on QC\history)" + "\n" + str(self.uncz)+"\n") self.Log ("\n"+"Why isnt dataframe.unstack at level=0 on pandas looking the same as dataframe.unstack at level=0 through Quantconnect\history?" + "\n") self.flag=False