@@ -325,6 +325,7 @@ def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
|
||||
:param column: Column in the original dataframes to use
|
||||
:return: DataFrame with the column renamed to the dict key, and a column
|
||||
named mean, containing the mean of all pairs.
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||||
:raise: ValueError if no data is provided.
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||||
"""
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||||
df_comb = pd.concat([data[pair].set_index('date').rename(
|
||||
{column: pair}, axis=1)[pair] for pair in data], axis=1)
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||||
|
@@ -460,7 +460,12 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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||||
def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
|
||||
trades: pd.DataFrame, timeframe: str, stake_currency: str) -> go.Figure:
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||||
# Combine close-values for all pairs, rename columns to "pair"
|
||||
df_comb = combine_dataframes_with_mean(data, "close")
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||||
try:
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||||
df_comb = combine_dataframes_with_mean(data, "close")
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||||
except ValueError:
|
||||
raise OperationalException(
|
||||
"No data found. Please make sure that data is available for "
|
||||
"the timerange and pairs selected.")
|
||||
|
||||
# Trim trades to available OHLCV data
|
||||
trades = extract_trades_of_period(df_comb, trades, date_index=True)
|
||||
|
Reference in New Issue
Block a user