Read data from Pandas

grat

Hi,
I'm new in backtrader

I have a data in pickle and read:

         _Symbol="EURUSD"
         cTF='1min' 
         dataframe = pd.read_pickle("data/"+_Symbol+""+cTF+".pkl")
         dataframe.head()

output:

	Date	open	high	low	close	volume	datetime
0	2016-04-01 00:00:00	1.13784	1.13793	1.13767	1.13788	252.53	2016-04-01 00:00:00
1	2016-04-01 00:01:00	1.13788	1.13802	1.13777	1.13800	262.13	2016-04-01 00:01:00
2	2016-04-01 00:02:00	1.13801	1.13817	1.13801	1.13816	233.21	2016-04-01 00:02:00
3	2016-04-01 00:03:00	1.13816	1.13821	1.13811	1.13818	215.07	2016-04-01 00:03:00
4	2016-04-01 00:04:00	1.13817	1.13820	1.13810	1.13815	171.65	2016-04-01 00:04:00

class PandasData(bt.feed.DataBase):
    '''
    The ``dataname`` parameter inherited from ``feed.DataBase`` is the pandas
    DataFrame
    '''

    params = (
        # Possible values for datetime (must always be present)
        #  None : datetime is the "index" in the Pandas Dataframe
        #  -1 : autodetect position or case-wise equal name
        #  >= 0 : numeric index to the colum in the pandas dataframe
        #  string : column name (as index) in the pandas dataframe
        ('datetime', -1),

        # Possible values below:
        #  None : column not present
        #  -1 : autodetect position or case-wise equal name
        #  >= 0 : numeric index to the colum in the pandas dataframe
        #  string : column name (as index) in the pandas dataframe
        ('open', -1),
        ('high', -1),
        ('low', -1),
        ('close', -1),
        ('volume', -1),
        ('openinterest', None),
    )

     def runstrat():
          # Create a cerebro entity
          cerebro = bt.Cerebro(stdstats=False)

          # Add a strategy
          cerebro.addstrategy(TestStrategy)

          dataframe = pd.read_pickle("data/"+_Symbol+""+cTF+".pkl")
          data = PandasData(dataname=dataframe)

           # Add the Data Feed to Cerebro
           cerebro.adddata(data)
   
          # Set our desired cash start
          cerebro.broker.setcash(100000.0)

          # Print out the starting conditions
          print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
   
          # Run over everything
          cerebro.run()

          # Print out the final result
          print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

# Create a Stratey
         class TestStrategy(bt.Strategy):
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])

        if self.dataclose[0] < self.dataclose[-1]:
            # current close less than previous close

            if self.dataclose[-1] < self.dataclose[-2]:
                # previous close less than the previous close

                # BUY, BUY, BUY!!! (with all possible default parameters)
                self.log('BUY CREATE, %.2f' % self.dataclose[0])
                self.buy()

       runstrat()

I'm have output:

* Starting Portfolio Value: 100000.00
* Final Portfolio Value: 100000.00

Where is my mistake? I also trying data with datatime index. The same output.

Thanks Milan

grat

Hi,

is a simple:

df = pd.read_pickle("data/"+_Symbol+""+cTF+".pkl")
data = bt.feeds.PandasData(dataname=df,timeframe=1,openinterest=None)

backtrader

Glad it worked.

timeframe=1 seems anyhow odd because that is the actual value for bt.TimeFrame.Ticks and the data seems to be made up of 1-minute bars.

The platform will not complain (especially if no resampling is done), but you can see that later in a plot.

The suggestion would be to use: timeframe=bt.TimeFrame.Minutes (symbolic names seem better)