Hi, thank you very much for help. I'm creating the cerebro entity with stdstats=False right now, but as you can see in the figure, arrows placed in the middle of the candles. Is there a way to add some kind of margin space between arrows and candles?

Hi guys, I've just started using backtrader and I am struggling with plotting.
Buy sell arrows don't seem in the correct place. There is some kind of scaling issue. I have a csv data with 5m frames. As you can see in my script I'm using

timeframe=bt.TimeFrame.Minutes,
compression=5

Any help is appreciated.

Plot:

You can see my config below:

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import backtrader as bt
import backtrader.feeds as btfeeds
import datetime
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])
import numpy


# Create a Stratey
class TestStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close
        self.datahigh = self.datas[0].high

        # To keep track of pending orders and buy price/commission
        self.order = None
        self.buyprice = None
        self.buycomm = None

        # Add a MovingAverageSimple indicator
        self.ma7 = bt.indicators.SimpleMovingAverage(self.datas[0], period=7)
        self.ma25 = bt.indicators.SimpleMovingAverage(self.datas[0], period=25)

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enough cash
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Price: %.8f, Cost: %.8f, Comm %.8f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))

                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:  # Sell
                self.log('SELL EXECUTED, Price: %.8f, Cost: %.8f, Comm %.8f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order
        self.order = None

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.8f, NET %.8f' %
                 (trade.pnl, trade.pnlcomm))

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.8f' % self.dataclose[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        if self.order:
            return

        # Check if we are in the market
        if not self.position:

            # Not yet ... we MIGHT BUY if ...

            if self.ma7[0] > self.ma25[0]:

                # BUY, BUY, BUY!!! (with all possible default parameters)
                self.log('BUY CREATE, %.8f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()

        else:

            if self.ma7[0] < self.ma25[0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.8f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'ohlcv1.csv')

    data = btfeeds.GenericCSVData(
        dataname=datapath,
        dtformat='%Y-%m-%d %H:%M:%S',
        datetime=0,
        open=1,
        high=2,
        low=3,
        close=4,
        volume=5,
        openinterest=-1,
        timeframe = bt.TimeFrame.Minutes,
        compression=5
    )


    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(1000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=0.2)

    # Set the commission
    cerebro.broker.setcommission(commission=0.001)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.8f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.8f' % cerebro.broker.getvalue())


    # Plot the result
    cerebro.plot(style='candlestick', barup='green', bardown='red')