@dasch @run-out Yes the problem was the wrong order in my CSV.
@ab_trader thanks for the suggestion. I will check it out.
I got it to work by reversing the order in the CSV. Thanks everyone for your help:)
In case anyone wants to use my quick and dirty way:
import pandas as pd
# load csv and use row 0 as headers
df = pd.read_csv("file_name.csv", header = 0)
# reverse data and save
df=df.iloc[::-1]
df.set_index('timestamp', inplace=True)
df.to_csv('reversed.csv')
@rajanprabu Thanks for your response! I tried your suggestion and still got the error.
Do you know what else might be wrong?
fromdate=datetime.datetime(2019, 1, 2),
todate=datetime.datetime(2020, 12, 31),
reverse=True,
Hi, I am a newbie trying to work through the quickstart guide.
I get IndexError: array assignment index out of range when I try to use a generic CSV with a date range. It works without date range, meaning if I don't pass
fromdate=datetime.datetime(2019, 1, 2),
todate=datetime.datetime(2020, 12, 31),
I have also tried variations of different dates for the date range with this generic CSV and got the same IndexError. I have checked that the CSV data has the dates.
There is no index error with using the original file and code from the guide.
data = bt.feeds.YahooFinanceCSVData(
dataname='orcl-1995-2014.txt',
# Do not pass values before this date
fromdate=datetime.datetime(2000, 1, 1),
# Do not pass values before this date
todate=datetime.datetime(2000, 12, 31),
# Do not pass values after this date
reverse=False)
Can someone help point out what I am doing wrong? My csv(snipped), code and traceback:
timestamp,open,high,low,close,adjusted_close,volume,dividend_amount,split_coefficient
2021-03-03,687.99,700.7,651.705,653.2,653.2,29693988,0.0000,1.0
2021-03-02,718.28,721.11,685.0,686.44,686.44,23732158,0.0000,1.0
2021-03-01,690.11,719.0,685.05,718.43,718.43,27136239,0.0000,1.0
...
2020-12-31,699.99,718.72,691.12,705.67,705.67,49649928,0.0000,1.0
2020-12-30,672.0,696.6,668.3603,694.78,694.78,42846021,0.0000,1.0
2020-12-29,661.0,669.9,655.0,665.99,665.99,22910811,0.0000,1.0
...
2019-01-04,306.0,318.0,302.73,317.69,63.538,7394100,0.0000,1.0
2019-01-03,307.0,309.4,297.38,300.36,60.072,6965200,0.0000,1.0
2019-01-02,306.1,315.13,298.8,310.12,62.024,11658600,0.0000,1.0
from __future__ import (absolute_import, division, print_function,
unicode_literals)
%matplotlib widget
import datetime # For datetime objects
import os.path # To manage paths
import sys # To find out the script name (in argv[0])
# Import the backtrader platform
import backtrader as bt
# Create a Stratey
class TestStrategy(bt.Strategy):
params = (
('maperiod', 15),
)
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
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
# Add a MovingAverageSimple indicator
self.sma = bt.indicators.SimpleMovingAverage(
self.datas[0], period=self.params.maperiod)
# Indicators for the plotting show
bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
bt.indicators.WeightedMovingAverage(self.datas[0], period=25,
subplot=True)
bt.indicators.StochasticSlow(self.datas[0])
bt.indicators.MACDHisto(self.datas[0])
rsi = bt.indicators.RSI(self.datas[0])
bt.indicators.SmoothedMovingAverage(rsi, period=10)
bt.indicators.ATR(self.datas[0], plot=False)
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: %.2f, Cost: %.2f, Comm %.2f' %
(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: %.2f, Cost: %.2f, Comm %.2f' %
(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 %.2f, NET %.2f' %
(trade.pnl, trade.pnlcomm))
def next(self):
# Simply log the closing price of the series from the reference
self.log('Close, %.2f' % 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.dataclose[0] > self.sma[0]:
# BUY, BUY, BUY!!! (with all possible default parameters)
self.log('BUY CREATE, %.2f' % self.dataclose[0])
# Keep track of the created order to avoid a 2nd order
self.order = self.buy()
else:
if self.dataclose[0] < self.sma[0]:
# SELL, SELL, SELL!!! (with all possible default parameters)
self.log('SELL CREATE, %.2f' % 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)
# Create a Data Feed
data = bt.feeds.GenericCSVData(
dataname='alpha_vantage_TSLA.csv',
fromdate=datetime.datetime(2019, 1, 2),
todate=datetime.datetime(2020, 12, 31),
nullvalue=0.0,
dtformat=('%Y-%m-%d'),
datetime=0,
time=-1,
open=1,
high=2,
low=3,
close=5,
volume=6,
openinterest=-1
)
# 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=10)
# Set the commission
cerebro.broker.setcommission(commission=0.002)
# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
# Run over everything
cerebro.run()
# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
# Plot the result
cerebro.plot()
Starting Portfolio Value: 1000.00
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-11-63f0d7e87f7b> in <module>
157
158 # Run over everything
--> 159 cerebro.run()
160
161 # Print out the final result
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\cerebro.py in run(self, **kwargs)
1125 # let's skip process "spawning"
1126 for iterstrat in iterstrats:
-> 1127 runstrat = self.runstrategies(iterstrat)
1128 self.runstrats.append(runstrat)
1129 if self._dooptimize:
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\cerebro.py in runstrategies(self, iterstrat, predata)
1291 self._runonce_old(runstrats)
1292 else:
-> 1293 self._runonce(runstrats)
1294 else:
1295 if self.p.oldsync:
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\cerebro.py in _runonce(self, runstrats)
1650 '''
1651 for strat in runstrats:
-> 1652 strat._once()
1653 strat.reset() # strat called next by next - reset lines
1654
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\lineiterator.py in _once(self)
295
296 for indicator in self._lineiterators[LineIterator.IndType]:
--> 297 indicator._once()
298
299 for observer in self._lineiterators[LineIterator.ObsType]:
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\lineiterator.py in _once(self)
295
296 for indicator in self._lineiterators[LineIterator.IndType]:
--> 297 indicator._once()
298
299 for observer in self._lineiterators[LineIterator.ObsType]:
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\lineiterator.py in _once(self)
315 # indicators are each called with its min period
316 self.preonce(0, self._minperiod - 1)
--> 317 self.oncestart(self._minperiod - 1, self._minperiod)
318 self.once(self._minperiod, self.buflen())
319
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\lineiterator.py in oncestart(self, start, end)
325
326 def oncestart(self, start, end):
--> 327 self.once(start, end)
328
329 def once(self, start, end):
~\anaconda3\envs\Backtrader\lib\site-packages\backtrader\indicators\basicops.py in once(self, start, end)
362
363 for i in range(start, end):
--> 364 dst[i] = math.fsum(src[i - period + 1:i + 1]) / period
365
366
IndexError: array assignment index out of range