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Properly handle empty dataframes after trimming

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closes #6629
This commit is contained in:
Matthias 2022-04-02 15:36:25 +02:00
parent f742d21690
commit b0fab3ad50
1 changed files with 2 additions and 2 deletions
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4
freqtrade/optimize/backtesting.py
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@ -339,14 +339,14 @@ class Backtesting:
if col in df_analyzed.columns: if col in df_analyzed.columns:
df_analyzed.loc[:, col] = df_analyzed.loc[:, col].replace( df_analyzed.loc[:, col] = df_analyzed.loc[:, col].replace(
[nan], [0 if not tag_col else None]).shift(1) [nan], [0 if not tag_col else None]).shift(1)
else: elif not df_analyzed.empty:
df_analyzed.loc[:, col] = 0 if not tag_col else None df_analyzed.loc[:, col] = 0 if not tag_col else None
df_analyzed = df_analyzed.drop(df_analyzed.head(1).index) df_analyzed = df_analyzed.drop(df_analyzed.head(1).index)
# Convert from Pandas to list for performance reasons # Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.) # (Looping Pandas is slow.)
data[pair] = df_analyzed[headers].values.tolist() data[pair] = df_analyzed[headers].values.tolist() if not df_analyzed.empty else []
return data return data
def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: ExitCheckTuple, def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,