Merge pull request #9871 from freqtrade/dependabot/pip/develop/pandas-2.2.1

Bump pandas from 2.1.4 to 2.2.1

freqtrade/data/history/hdf5datahandler.py

@@ -35,7 +35,7 @@ class HDF5DataHandler(IDataHandler):
         self.create_dir_if_needed(filename)
 
         _data.loc[:, self._columns].to_hdf(
-            filename, key, mode='a', complevel=9, complib='blosc',
+            filename, key=key, mode='a', complevel=9, complib='blosc',
             format='table', data_columns=['date']
         )
 
@@ -110,7 +110,7 @@ class HDF5DataHandler(IDataHandler):
         key = self._pair_trades_key(pair)
 
         data.to_hdf(
-            self._pair_trades_filename(self._datadir, pair), key,
+            self._pair_trades_filename(self._datadir, pair), key=key,
             mode='a', complevel=9, complib='blosc',
             format='table', data_columns=['timestamp']
         )

freqtrade/data/history/jsondatahandler.py

@@ -37,7 +37,7 @@ class JsonDataHandler(IDataHandler):
         self.create_dir_if_needed(filename)
         _data = data.copy()
         # Convert date to int
-        _data['date'] = _data['date'].view(np.int64) // 1000 // 1000
+        _data['date'] = _data['date'].astype(np.int64) // 1000 // 1000
 
         # Reset index, select only appropriate columns and save as json
         _data.reset_index(drop=True).loc[:, self._columns].to_json(

freqtrade/optimize/analysis/lookahead_helpers.py

@@ -107,9 +107,9 @@ class LookaheadAnalysisSubFunctions:
                 csv_df = add_or_update_row(csv_df, new_row_data)
 
         # Fill NaN values with a default value (e.g., 0)
-        csv_df['total_signals'] = csv_df['total_signals'].fillna(0)
+        csv_df['total_signals'] = csv_df['total_signals'].astype(int).fillna(0)
-        csv_df['biased_entry_signals'] = csv_df['biased_entry_signals'].fillna(0)
+        csv_df['biased_entry_signals'] = csv_df['biased_entry_signals'].astype(int).fillna(0)
-        csv_df['biased_exit_signals'] = csv_df['biased_exit_signals'].fillna(0)
+        csv_df['biased_exit_signals'] = csv_df['biased_exit_signals'].astype(int).fillna(0)
 
         # Convert columns to integers
         csv_df['total_signals'] = csv_df['total_signals'].astype(int)

freqtrade/optimize/optimize_reports/optimize_reports.py

@@ -215,7 +215,7 @@ def _get_resample_from_period(period: str) -> str:
         # Weekly defaulting to Monday.
         return '1W-MON'
     if period == 'month':
-        return '1M'
+        return '1ME'
     raise ValueError(f"Period {period} is not supported.")
 
 

freqtrade/rpc/rpc.py

@@ -1155,7 +1155,7 @@ class RPC:
         }
         if has_content:
 
-            dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].view(int64) // 1000 // 1000
+            dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].astype(int64) // 1000 // 1000
             # Move signal close to separate column when signal for easy plotting
             for sig_type in signals.keys():
                 if sig_type in dataframe.columns:

requirements.txt

@@ -1,5 +1,5 @@
 numpy==1.26.4
-pandas==2.1.4
+pandas==2.2.1
 pandas-ta==0.3.14b
 
 ccxt==4.2.51

tests/conftest.py

@@ -177,7 +177,7 @@ def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
 def generate_test_data_raw(timeframe: str, size: int, start: str = '2020-07-05'):
     """ Generates data in the ohlcv format used by ccxt """
     df = generate_test_data(timeframe, size, start)
-    df['date'] = df.loc[:, 'date'].view(np.int64) // 1000 // 1000
+    df['date'] = df.loc[:, 'date'].astype(np.int64) // 1000 // 1000
     return list(list(x) for x in zip(*(df[x].values.tolist() for x in df.columns)))
 
 

tests/optimize/test_optimize_reports.py

@@ -498,7 +498,7 @@ def test__get_resample_from_period():
 
     assert _get_resample_from_period('day') == '1d'
     assert _get_resample_from_period('week') == '1W-MON'
-    assert _get_resample_from_period('month') == '1M'
+    assert _get_resample_from_period('month') == '1ME'
     with pytest.raises(ValueError, match=r"Period noooo is not supported."):
         _get_resample_from_period('noooo')
 

tests/strategy/test_interface.py

@@ -1022,22 +1022,22 @@ def test_auto_hyperopt_interface_loadparams(default_conf, mocker, caplog):
 
 
 @pytest.mark.parametrize('function,raises', [
-    ('populate_entry_trend', True),
+    ('populate_entry_trend', False),
     ('advise_entry', False),
-    ('populate_exit_trend', True),
+    ('populate_exit_trend', False),
     ('advise_exit', False),
 ])
-def test_pandas_warning_direct(ohlcv_history, function, raises):
+def test_pandas_warning_direct(ohlcv_history, function, raises, recwarn):
 
     df = _STRATEGY.populate_indicators(ohlcv_history, {'pair': 'ETH/BTC'})
     if raises:
-        with pytest.warns(FutureWarning):
+        assert len(recwarn) == 1
-            # Test for Future warning
+        # https://github.com/pandas-dev/pandas/issues/56503
-            # FutureWarning: Setting an item of incompatible dtype is
+        # Fixed in 2.2.x
-            # deprecated and will raise in a future error of pandas
+        getattr(_STRATEGY, function)(df, {'pair': 'ETH/BTC'})
-            # https://github.com/pandas-dev/pandas/issues/56503
-            getattr(_STRATEGY, function)(df, {'pair': 'ETH/BTC'})
     else:
+        assert len(recwarn) == 0
+
         getattr(_STRATEGY, function)(df, {'pair': 'ETH/BTC'})