how to get correct 15min value by using resample_apply with 1min data

[zha0yangchen]

Expected Behavior

Expected data should same as this high = pd.DataFrame({'high': self.data.High}, index=self.data.index).resample('15min').agg('max').dropna().values[:, 0][-500:]

Actual Behavior

but when i use self.High = resample_apply('15min', None, self.data.High)
and print( self.High[-1], high[-1]), the value of self.high is incorrect, but high[-1] is corrct.

Steps to Reproduce

python code goes here

Additional info

• Backtesting version: 0.?.?
• bokeh.__version__:
• OS:

[BL0987]

I get better results by resampling the dataframe prior to using it in the backtest:

e.g

import pandas as pd
import yfinance as yf

df = yf.download('AAPL', period='5y', interval='1d') # rounding=True

df1 = df.resample('2d').agg({'Open': 'first',
'High': 'max',
'Low': 'min',
'Close': 'last',
'Volume': 'sum'})

Hope it helps

[kernc]

high = pd.DataFrame({'high': self.data.High}, index=self.data.index).resample('15min').agg('max').dropna().values[:, 0][-500:]

You should have compared with label="right":

high = self.data.High.s.resample('15min', label='right').agg('max') ...

or at least that's what resample_apply() does.