resampling Pandas dataframe

Brad Lloyd

not sure if anyone else has had trouble with loading data from a pandas dataframe and then using cerebro.resample, but we did. The dataframe for minute data loads find and then when I go to pass the dataframte to cerebro.resample I get nan values. if I use a csv it loads and resamples with no problems

so we ended up using pandas own resample feature which works just fine

backtrader

If you can share an example it can for sure be looked into.

Directly resampling with pandas is of course ok. The resampling in backtrader is there to keep the code the same across (for example) backtesting data and live data.

Brad Lloyd

not sure how to get the formatted code to paste

startdate = datetime.datetime(2012, 1, 1)
enddate = datetime.datetime(2013, 1, 3)
def get_mstar_data(sym, startdate, enddate):
    s = startdate.year
    e = enddate.year
    df = None
    for i in range(s, e + 1):
        for filename in glob.glob("%s/%d/%s*_1min.gz" % (m_star_cbot_path, i, sym)):
            filedf = _create_df(filename)
            filedf = filedf.ix[startdate:enddate]
            print (len(filedf.index))
            df = filedf if df is None else df.append(filedf)



    return mstar(
        fromdate=startdate,
        todate=enddate,
        dataname=df,
        name=sym,
        datetime=None

    )


data = get_mstar_data('ZC0Y', startdate, enddate):

cerebro.adddata(data)
cerebro.resampledata(data, name=ZC0Y15m, timeframe=bt.Timeframe.Minutes, compression=15)

Brad Lloyd

note we solved it by creating a new cerebro class that lets us do the following

cerebro.add_feeds(startdate, enddate, portfolio_symbols, conflations)

backtrader

The code is clear but the actual problem you faced (at least on this side) is not yet clear.

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