Store fully analyzed dataframe
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@ -227,7 +227,7 @@ class Backtesting:
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pair_data.loc[:, 'buy_tag'] = None # cleanup if buy_tag is exist
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df_analyzed = self.strategy.advise_sell(
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self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
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self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair}).copy()
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# Trim startup period from analyzed dataframe
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df_analyzed = trim_dataframe(df_analyzed, self.timerange,
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startup_candles=self.required_startup)
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@ -245,7 +245,7 @@ class Backtesting:
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# Convert from Pandas to list for performance reasons
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# (Looping Pandas is slow.)
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data[pair] = df_analyzed.values.tolist()
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data[pair] = df_analyzed[headers].values.tolist()
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return data
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def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: SellCheckTuple,
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