Merge pull request #9362 from freqtrade/dependabot/pip/develop/pandas-2.1.2

Bump pandas from 2.0.3 to 2.1.2

freqtrade/misc.py

@@ -3,6 +3,7 @@ Various tool function for Freqtrade and scripts
 """
 import gzip
 import logging
+from io import StringIO
 from pathlib import Path
 from typing import Any, Dict, Iterator, List, Mapping, Optional, TextIO, Union
 from urllib.parse import urlparse
@@ -231,7 +232,7 @@ def json_to_dataframe(data: str) -> pd.DataFrame:
     :param data: A JSON string
     :returns: A pandas DataFrame from the JSON string
     """
-    dataframe = pd.read_json(data, orient='split')
+    dataframe = pd.read_json(StringIO(data), orient='split')
     if 'date' in dataframe.columns:
         dataframe['date'] = pd.to_datetime(dataframe['date'], unit='ms', utc=True)
 

freqtrade/optimize/analysis/lookahead.py

@@ -94,8 +94,8 @@ class LookaheadAnalysis(BaseAnalysis):
                     # compare_df now comprises tuples with [1] having either 'self' or 'other'
                     if 'other' in col_name[1]:
                         continue
-                    self_value = compare_df_row[col_idx]
+                    self_value = compare_df_row.iloc[col_idx]
-                    other_value = compare_df_row[col_idx + 1]
+                    other_value = compare_df_row.iloc[col_idx + 1]
 
                     # output differences
                     if self_value != other_value:

freqtrade/optimize/hyperopt_tools.py

@@ -429,14 +429,18 @@ class HyperoptTools:
         trials = trials.drop(columns=['Total profit'])
 
         if print_colorized:
+            trials2 = trials.astype(str)
             for i in range(len(trials)):
                 if trials.loc[i]['is_profit']:
                     for j in range(len(trials.loc[i]) - 3):
-                        trials.iat[i, j] = f"{Fore.GREEN}{str(trials.loc[i][j])}{Fore.RESET}"
+                        trials2.iat[i, j] = f"{Fore.GREEN}{str(trials.iloc[i, j])}{Fore.RESET}"
                 if trials.loc[i]['is_best'] and highlight_best:
                     for j in range(len(trials.loc[i]) - 3):
-                        trials.iat[i, j] = f"{Style.BRIGHT}{str(trials.loc[i][j])}{Style.RESET_ALL}"
+                        trials2.iat[i, j] = (
-
+                            f"{Style.BRIGHT}{str(trials.iloc[i, j])}{Style.RESET_ALL}"
+                        )
+            trials = trials2
+            del trials2
         trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit', 'is_random'])
         if remove_header > 0:
             table = tabulate.tabulate(

freqtrade/optimize/optimize_reports/optimize_reports.py

@@ -219,8 +219,10 @@ def _get_resample_from_period(period: str) -> str:
     raise ValueError(f"Period {period} is not supported.")
 
 
-def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dict[str, Any]]:
+def generate_periodic_breakdown_stats(
-    results = DataFrame.from_records(trade_list)
+        trade_list: Union[List,  DataFrame], period: str) -> List[Dict[str, Any]]:
+
+    results = trade_list if not isinstance(trade_list, list) else DataFrame.from_records(trade_list)
     if len(results) == 0:
         return []
     results['close_date'] = to_datetime(results['close_date'], utc=True)

freqtrade/strategy/interface.py

@@ -1006,7 +1006,7 @@ class IStrategy(ABC, HyperStrategyMixin):
             exit_ = latest.get(SignalType.EXIT_LONG.value, 0) == 1
         exit_tag = latest.get(SignalTagType.EXIT_TAG.value, None)
         # Tags can be None, which does not resolve to False.
-        exit_tag = exit_tag if isinstance(exit_tag, str) else None
+        exit_tag = exit_tag if isinstance(exit_tag, str) and exit_tag != 'nan' else None
 
         logger.debug(f"exit-trigger: {latest['date']} (pair={pair}) "
                      f"enter={enter} exit={exit_}")
@@ -1038,17 +1038,17 @@ class IStrategy(ABC, HyperStrategyMixin):
         exit_short = latest.get(SignalType.EXIT_SHORT.value, 0) == 1
 
         enter_signal: Optional[SignalDirection] = None
-        enter_tag_value: Optional[str] = None
+        enter_tag: Optional[str] = None
         if enter_long == 1 and not any([exit_long, enter_short]):
             enter_signal = SignalDirection.LONG
-            enter_tag_value = latest.get(SignalTagType.ENTER_TAG.value, None)
+            enter_tag = latest.get(SignalTagType.ENTER_TAG.value, None)
         if (self.config.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT
                 and self.can_short
                 and enter_short == 1 and not any([exit_short, enter_long])):
             enter_signal = SignalDirection.SHORT
-            enter_tag_value = latest.get(SignalTagType.ENTER_TAG.value, None)
+            enter_tag = latest.get(SignalTagType.ENTER_TAG.value, None)
 
-        enter_tag_value = enter_tag_value if isinstance(enter_tag_value, str) else None
+        enter_tag = enter_tag if isinstance(enter_tag, str) and enter_tag != 'nan' else None
 
         timeframe_seconds = timeframe_to_seconds(timeframe)
 
@@ -1058,11 +1058,11 @@ class IStrategy(ABC, HyperStrategyMixin):
             timeframe_seconds=timeframe_seconds,
             enter=bool(enter_signal)
         ):
-            return None, enter_tag_value
+            return None, enter_tag
 
         logger.debug(f"entry trigger: {latest['date']} (pair={pair}) "
-                     f"enter={enter_long} enter_tag_value={enter_tag_value}")
+                     f"enter={enter_long} enter_tag_value={enter_tag}")
-        return enter_signal, enter_tag_value
+        return enter_signal, enter_tag
 
     def ignore_expired_candle(
         self,

requirements.txt

@@ -1,5 +1,5 @@
 numpy==1.26.1
-pandas==2.0.3
+pandas==2.1.2
 pandas-ta==0.3.14b
 
 ccxt==4.1.31

tests/data/test_converter.py

@@ -50,8 +50,8 @@ def test_trades_to_ohlcv(trades_history_df, caplog):
     assert 'high' in df.columns
     assert 'low' in df.columns
     assert 'close' in df.columns
-    assert df.loc[:, 'high'][0] == 0.019627
+    assert df.iloc[0, :]['high'] == 0.019627
-    assert df.loc[:, 'low'][0] == 0.019626
+    assert df.iloc[0, :]['low'] == 0.019626
 
 
 def test_ohlcv_fill_up_missing_data(testdatadir, caplog):