@backtrader It's my mistake. I read it wrong. Thank you for directing me in right way .

@abyaby Hi abyaby, For my own informaiton, please, how do you import in backtrader BTC/ETH trading data? I thank you in advance for your feedback. Have a good evening. Best regards, Pierre

Hi, To the interested readers: maybe to confirm there are some other users interested, and to see how many, can you take part to the poll and vote for this feature? The button to vote is quite hidden actually: you have to look at it in the right top corner of Justin Zhang's initial post: there is one tiny ^ , next to it the number of votes, and then a as tiny v next to it like this: ^ 1 v for instance To vote up, you have logically to click on ^ symbol :). I thank you for your involvement. Bests, Pierre

Thanks for the replies, I'll double check the code and will see what happens.

@pipeline-punch said in Struggling to implement custom Pandas data feed: If the custom Pandas DataFrame contained the same columns as we have been working with, but multiple "assets" instead of just one (as in the example we've been working with) - how would everything work? Similar to how we've done it above, or something a bit different to deal with the dual-indexing? bt's PandasData requires separate DataFrame for each stock ticker. But since Now that I know the structure of how to do this, I feel confident I can now pull in any custom Pandas data frame I would like! than you can write your own Pandas data feed which will take care about multiple assets in the single DataFrame. It depends on the amount of time you have and your python skills.

PyCharm IDE solve this plotting problem. I changed from Spyder IDE to PyCharm.

See: Community - Release 1.9.72.122

See: Community - Release 1.9.72.122 The trivial fix would have helped, but it wasn't the right one. The real fix was somewhere else, being also mostly trivial. The SMMA and EMA indicators rely on the previous value to calculate the new one. As soon as one value is NaN, the result will always be the same and NaN. Non-recursive indicators, mostly every other, will recover after a number of calcualtions which is what made it possible for the error to remain undetected for a long while. The code will work now without having to create null delay object as in class RelativeVolatility(bt.Indicator): alias = ('RV',) lines = ('rv', 'nU', 'nD',) params = dict( p1=10, p2=14, movav=bt.ind.EMA, ) def __init__(self): stddev = bt.ind.StdDev(self.data, period=self.p.p1) u = bt.If(self.data > self.data(-1), stddev, 0.0) d = bt.If(self.data < self.data(-1), stddev, 0.0) self.l.nU = nU = self.p.movav(u, period=self.p.p2) self.l.nD = nD = self.p.movav(d, period=self.p.p2) self.l.rv = 100.0 * nU / (nU + nD)

Cool, thank you. I've been working mostly with java and c++ lately so my syntax's are all mixed up. If anyone is interested, I'll upload progress on the library to this thread.

I assume that @ab_trader has nailed it and you are looking to backfill a live data. If not, I then fail to understand what the actual goal is.

No. It's not the same problem and your thread has been answered.

Yes. do as @ab_trader points out. You cannot buy if you haven't got any cash. You need to sell first to inject cash into your account.

https://medium.com/@danjrod/interactive-brokers-in-python-with-backtrader-23dea376b2fc