'numpy.float64' object has no attribute 'values'

[Daiiszuki]

I tried to implement https://github.com/AI4Finance-Foundation/FinRL-Meta/blob/master/tutorials/2-Advance/FinRL_PortfolioAllocation_Explainable_DRL.ipynb for crypto portfolio allocation, but got

AttributeError                            Traceback (most recent call last)
[<ipython-input-103-4fbf8c9df76f>](https://localhost:8080/#) in <module>
     12 
     13 
---> 14 cryptoEnv =cryptoPortfolioAllocationEnvironment(path=PATH, **envKwargs)

1 frames
[<ipython-input-102-10be5fc69e51>](https://localhost:8080/#) in <listcomp>(.0)
     39       self.frame = self.dataFrame.loc[self.dateIncriment, :]
     40       self.covarianceList = self.frame['covarianceList'][0]
---> 41       self.stateVar = np.append(np.array(self.covarianceList),[self.frame[indic].values.tolist() for indic in  self.indicatorList],axis=0)
     42       #self.state =  np.append(np.array(self.covs), [self.data[tech].values.tolist() for tech in self.tech_indicator_list ], axis=0)
     43 

AttributeError: 'numpy.float64' object has no attribute 'values'`

The data is in a csv as follows;

and my environment:

class cryptoPortfolioAllocationEnvironment(gym.Env):
    metadata = {'render.modes': ['human']}

    def __init__(self, 
               path,
                cryptoDimension,
                maxCryptos,
                startingCapital,
                transactionFeePercentage,
                agentRewardFactor,
                stateSpace,
                actionSpace,
                indicatorList,
                turbulance=None,
                lookbackPeriod=252,
                dateIncriment = 0):

      self.dateIncriment = dateIncriment
      self.lookbackPeriod = lookbackPeriod
      self.dataFrame = panda.read_csv(path)
      self.cryptoDimension = cryptoDimension
      self.maxCryptos = maxCryptos
      self.startingCapital = startingCapital
      self.transactionFeePercentage = transactionFeePercentage
      self.agentRewardFactor = agentRewardFactor
      self.stateSpace = stateSpace
      self.actionSpace = actionSpace
      self.indicatorList = indicatorList
      self.turbulance=None

      self.actionSpace = spaces.Box(low = 0, high = 1, shape=(self.actionSpace,))
      print(actionSpace)
      self.observationSpace = spaces.Box( low=np.inf, high = np.inf, shape = ( self.stateSpace+ len(indicatorList), stateSpace))
      self.frame = self.dataFrame.loc[self.dateIncriment, :]
      self.covarianceList = self.frame['covarianceList'][0]
      self.stateVar = np.append(np.array((self.covarianceList),[self.frame[indic].values.toList() for indic in self.indicatorList],axis=0))

      self.term  =False
      self.turbulance=turbulance

      self.portfolioValue = self.startingCapital
      self.portfolioHistory = [self.startingCapital]

      self.portFolioReturnHistory = [0]
      self.actionHistory = [[[1/cryptoDimension] * cryptoDimension]] 
      self.dateHistory = [self.frame.date.unique()[0]]

The error occurs with the following params;

envKwargs = {
    "maxCryptos": 5, 
    "startingCapital": 1000000, 
    "transactionFeePercentage": 0.001, 
    "stateSpace": stateSpace, 
    "cryptoDimension": cryptoDimension, 
    "indicatorList": INDICATOR_LIST, 
    "actionSpace": cryptoDimension, 
    "agentRewardFactor": 1e-4

}

cryptoEnv =cryptoPortfolioAllocationEnvironment(path=PATH, **envKwargs)

[Daiiszuki]

Changing

self.frame = self.dataFrame.loc[self.dateIncriment, :]

to self.frame = self.dataFrame.loc[[self.dateIncriment]]

achieves the same result and ensures that a series is returned