retrieve backtraders information as a dataframe

Jens Halsberghe

Hi,

I'm pretty new to backtrader. I've read through the manual but haven't found the answer yet to a question I have. Is there a way to retrieve everything you feed into backtrader as a dataframe.

for example, we feed OHLC data into backtrader, we create 2 moving averages, we add a long and short signal when crossing over etc.

Is there a way to then also get all this information in a dataframe? eg the columns would look something like:

Date, Open, High, Low, Close, MA1, MA2, Signal

thanks

run-out

Using analyzers. The return of running cerebro is a strategy object.

strat = cerebro.run()

'strat' in this case is a strategy object and will contain any analyzers you have built and added to the cerebro engine. The analyzer will be the data in the form of a dictionary. In your case because you desire your custom indicators along with your OHLCV, you could build a custom analyzer. Here is an example you can use for the class definition:


class OHLCMMS(bt.analyzers.Analyzer):
    """This analyzer reports the OHLCV +lines of each of datas.
    Params:
      - timeframe (default: ``None``)
        If ``None`` then the timeframe of the 1st data of the system will be
        used
      - compression (default: ``None``)
        Only used for sub-day timeframes to for example work on an hourly
        timeframe by specifying "TimeFrame.Minutes" and 60 as compression
        If ``None`` then the compression of the 1st data of the system will be
        used
    Methods:
      - get_analysis
        Returns a dictionary with returns as values and the datetime points for
        each return as keys
    """

    def start(self):
        tf = min(d._timeframe for d in self.datas)
        self._usedate = tf >= bt.TimeFrame.Days
        self.rets = {}

    def next(self):

        self.rets[self.data.datetime.datetime()] = [
            self.datas[0].open[0],
            self.datas[0].high[0],
            self.datas[0].low[0],
            self.datas[0].close[0],
            self.MA1[0],
            self.MA2[0],
            self.signal[0],
        ]

    def get_analysis(self):
        return self.rets

To add this to cerebro:

cerebro.addanalyzer(OHLCMMS, _name="OHLCMMS")

After you run the backtest you can extract your information from 'strat' as follows:

strat[0].analyzers.getbyname("OHLCMMS").get_analysis()

Which you can then turn into a dataframe as:

df = pd.DataFrame.from_dict(
        strat[0].analyzers.getbyname("OHLCMMS").get_analysis(),
        orient="index",
        columns=["open", "high", "low", "close", "MA1", "MA2", "signal"],
    )

Jens Halsberghe

@run-out thanks a lot, really appreciated! hadn't read that far yet so should have just read the full guide first.

Bard Tim

@run-out that is smart,thanks