@asdasda Using slicing could be an option. Docs here

@aalli If the separator is set to tab or space, the date and time will become a separate columns. In this case the dtformat and tmformat need to be specified as well as datetime and time columns should have valid column indexes.

@asdasda Read up on how to create and add analyzers to backtrader. You should find you answer there.

@asdasda This feels a bit hacky but try:

len(self.datas[0].array)

@asdasda Create an indicator line that returns the positive values.

self.abs = bt.If( (self.datas[0].close - self.datas[0].open) < 0, -(self.datas[0].close - self.datas[0].open), (self.datas[0].close - self.datas[0].open), )

@rishabmah5 It would be significantly more helpful if you supplied OHLC data for each bar, if we are going to analyze OHLC to answer the question.

@asdasda load the data into pandas and check the condition of no. of records if it's more than required then load the data to bt.feeds

https://stackoverflow.com/questions/63471764/importerror-cannot-import-name-warnings-from-matplotlib-dates

@rajanprabu I noticed the other df was timezone aware, I made it tz naive and that solved the issue and I am not getting duplicate outputs anymore. But out of curiosity, do you know why having a tz aware prints duplicate outputs?

@run-out when i open it in excel it is in one column with coma separated values without headers,

used this code to download the file from binance,

import config, csv

from binance.client import Client

client = Client(config.API_KEY, config.SECRET_KEY)

candles = client.get_historical_klines("BTCBUSD", Client.KLINE_INTERVAL_1MINUTE, "365 day ago UTC")

csvfile = open('1min.csv', 'w', newline='')
Klinewriter = csv.writer(csvfile,delimiter=',')

for candlestick in candles:

Klinewriter.writerow(candlestick)

csvfile.close()

Maybe some of this thread helps? https://community.backtrader.com/topic/2/limit-order-with-a-day-valid-never-gets-executed-220/13

@calebsandfort Sure just input earlier data, and then in your next check the date before starting to trade. So for example, you would start your data 2015,1,1 and then in your strategy:

def __init__(self): self.trade_start = datetime.datetime(2016, 1, 1, 0, 0) def next(self): dt = self.data.datetime.datetime() if dt < self.trade_start: return

Or enter trade_start as a parameter.

@prnvat8197 Aah, finally read the documentation thoroughly and did some tickering around, the Generic csv data is required as input

data = btfeeds.GenericCSVData( dataname=datapath, fromdate=datetime.datetime(2021, 7, 1), todate=datetime.datetime(2021, 7, 16), nullvalue=0.0, dtformat=('%Y-%m-%d %H:%M:%S'), timeframe = bt.TimeFrame.Minutes, compression = 15, Datetime=0, High=2, Low=3, Open=1, Close=4, Volume=7, Adj_Close=6)

Thanks to everyone who replied to this thread! Really appreciate the community :D