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https://github.com/webclinic017/drift.git
synced 2026-07-28 03:08:01 +00:00
Mark Aron Szulyovszky
9d47ee942d
* feat(Project): use 5 minute data, running training in parallel, sped up cusum filter by 10x with numba * fix(WalkForward): inference mini-batch parallelization * fix(WalkForward): don't use the parallel version of any of the functions * feat(CI): download the data required * fix(Project): 5min_crypto folder added * fix(Evaluate): make sure we have numerical stability in returns * feat(Models): use SKLearn models directly to enable composability * feat(Inference): batched inference now working, added forecasting_horizon * fix(Inference): works again * fix(Inference) * chore(Models): remove unused Ensemble model * fix(Labeller): don't just forward shift returns, also take the sum of the data happened until then * Update test.yml
9 lines
308 B
Python
9 lines
308 B
Python
import pandas as pd
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def resample_ohlc(df, period):
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output = pd.DataFrame()
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output['open'] = df.open.resample(period).first()
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output['high'] = df.high.resample(period).max()
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output['low'] = df.low.resample(period).min()
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output['close'] = df.close.resample(period).last()
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return output |