Is there a tutorial showing how I can use my own pandas dataframe?

[sedna16]

I've checked the docs and there seems to be no way to implement or add my own pandas dataframe.

I needs to do this because I will be using that df in the next()

[kernc]

add my own pandas dataframe

What do you mean? Backtesting.py only works with your data frames! The dataframe needs the OHLC(V) columns as prescribed, and any additional columns are optional. See: #64.

If you need back the df in next(), you can use its .df accessor:

    def next(self):
        df = self.data.df
        ...

[sedna16]

I tried doing it. Here's what I got with the result

Start                     2018-11-14 00:00:00
End                       2020-11-13 00:00:00
Duration                    730 days 00:00:00
Exposure Time [%]                           0
Equity Final [$]                        10000
Equity Peak [$]                         10000
Return [%]                                  0
Buy & Hold Return [%]                 70.2681
Max. Drawdown [%]                          -0
Avg. Drawdown [%]                         NaN
Max. Drawdown Duration                    NaN
Avg. Drawdown Duration                    NaN
# Trades                                    0
Win Rate [%]                              NaN
Best Trade [%]                            NaN
Worst Trade [%]                           NaN
Avg. Trade [%]                            NaN
Max. Trade Duration                       NaN
Avg. Trade Duration                       NaN
Profit Factor                             NaN
Expectancy [%]                            NaN
SQN                                       NaN
Sharpe Ratio                              NaN
Sortino Ratio                             NaN
Calmar Ratio                              NaN
_strategy                            SMACross
_equity_curve                          Equ...
_trades                   Empty DataFrame
...
dtype: object

The colums for dataframe are as follows:
Date (index)
Open
High
Low
Close
Volume
sma_20
sma_50

[sedna16]

Take note: the indicators are pre-added from outside the SMACross class

[kernc]

Sorry, but without code/data, that's really not enough to go on. 👉 Zero trades were made.
Perhaps raise your cash/leverage.

[sedna16]

ok, I'll try to post the code here after work.

[sedna16]

I think I finally got it working (results, no charts yet)

	def next(self):
		# If sma1 crosses above sma2, close any existing
		# short trades, and buy the asset
		if crossover(self.data.df.sma_20, self.data.df.sma_50):
			self.position.close()
			self.buy()

		# Else, if sma1 crosses below sma2, close any existing
		# long trades, and sell the asset
		elif crossover(self.data.df.sma_50, self.data.df.sma_20):
			self.position.close()
			self.sell()`

[kernc]

Note, you should find it far more performant not to convert to df:

if crossover(self.data.sma_20, self.data.sma_50):
    ...

So is there an issue here?

[sedna16]

I'll test it out.

[sedna16]

Note, you should find it far more performant not to convert to df:

if crossover(self.data.sma_20, self.data.sma_50):
    ...

So is there an issue here?

Tested this out, it worked. But somehow the first time I used it, it didn't behaved properly.