Is this a valid way of analyzing multiple timeframes?

[Taewoo Kim]

I am adding data, then resampling data to get multiple time frame trend analysis.. but it's the same data feed. Source code:

'''

df = csv_to_pandas(args.data, timeframe="1Min")

cerebro_data = bt.feeds.PandasData(dataname=df)

logging.info("Adding pandas dataframe to cerebro")

cerebro.adddata(cerebro_data)

logging.info("Adding resampled pandas dataframe for higher timeframe to cerebro")
cerebro.resampledata(cerebro_data, timeframe=bt.TimeFrame.Minutes, compression=60) # 1 hour

'''
Is this correct? For some reason the resulting graph doesn't look right

[backtrader]

@Taewoo-Kim said in Is this a valid way of analyzing multiple timeframes?:

cerebro_data = bt.feeds.PandasData(dataname=df)

Missing timeframe/compression? The default is timeframe=bt.TimeFrame.Days

[Taewoo Kim]

@backtrader I already resampled in pandas... is this "un-kosher"? Should I be letting backtrader doing this?

[backtrader]

You can resample 1000 times in pandas if you wish, there is nothing against it. It will actually probably save you time (more if you save it to disk/database/something-else) and read it from there each time.

But you are simply not telling the platform to what you actually resampled to and therefore the default settings bt.TimeFrame.Days/1 are applied.