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I received the following error in the log with HarmonicDivergence.py:
/freqtrade/user_data/strategies/HarmonicDivergence.py:630: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:
df["col"][row_indexer] = value
Use df.loc[row_indexer, "col"] = values instead, to perform the assignment in a single step and ensure this keeps updating the original df.
I received the following error in the log with HarmonicDivergence.py:
/freqtrade/user_data/strategies/HarmonicDivergence.py:630: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:
df["col"][row_indexer] = value
Use
df.loc[row_indexer, "col"] = values
instead, to perform the assignment in a single step and ensure this keeps updating the originaldf
.See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
dataframe["total_bullish_divergences_names"][index-30] = dataframe["total_bullish_divergences_names"][index-30] + indicator_source.upper() + '
'
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