@@ -115,17 +115,23 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
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return df
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def trim_dataframe(df: DataFrame, timerange, df_date_col: str = 'date') -> DataFrame:
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def trim_dataframe(df: DataFrame, timerange, df_date_col: str = 'date',
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startup_candles: int = 0) -> DataFrame:
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"""
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Trim dataframe based on given timerange
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:param df: Dataframe to trim
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:param timerange: timerange (use start and end date if available)
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:param: df_date_col: Column in the dataframe to use as Date column
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:param df_date_col: Column in the dataframe to use as Date column
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:param startup_candles: When not 0, is used instead the timerange start date
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:return: trimmed dataframe
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"""
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if timerange.starttype == 'date':
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start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
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df = df.loc[df[df_date_col] >= start, :]
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if startup_candles:
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# Trim candles instead of timeframe in case of given startup_candle count
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df = df.iloc[startup_candles:, :]
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else:
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if timerange.starttype == 'date':
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start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
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df = df.loc[df[df_date_col] >= start, :]
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if timerange.stoptype == 'date':
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stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
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df = df.loc[df[df_date_col] <= stop, :]
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