Sk-update-pandas-3

doubleml/data/panel_data.py

@@ -394,7 +394,11 @@ def _set_time_var(self):
         if hasattr(self, "_data") and self.t_col in self.data.columns:
             t_values = self.data.loc[:, self.t_col]
             expected_dtypes = (np.integer, np.floating, np.datetime64)
-            if not any(np.issubdtype(t_values.dtype, dt) for dt in expected_dtypes):
+            try:
+                valid_type = any(np.issubdtype(t_values.dtype, dt) for dt in expected_dtypes)
+            except TypeError:
+                valid_type = False
+            if not valid_type:
                 raise ValueError(f"Invalid data type for time variable: expected one of {expected_dtypes}.")
             else:
                 self._t = t_values

doubleml/did/utils/_plot.py

@@ -25,7 +25,10 @@ def add_jitter(data, x_col, is_datetime=None, jitter_value=None):
         is_datetime = pd.api.types.is_datetime64_any_dtype(data[x_col])
 
     # Initialize jittered_x with original values
-    data["jittered_x"] = data[x_col]
+    if is_datetime:
+        data["jittered_x"] = data[x_col]
+    else:
+        data["jittered_x"] = data[x_col].astype(float)
 
     for x_val in data[x_col].unique():
         mask = data[x_col] == x_val

doubleml/did/utils/tests/test_add_jitter.py

@@ -1,5 +1,6 @@
 from datetime import datetime, timedelta
 
+import numpy as np
 import pandas as pd
 import pytest
 
@@ -41,7 +42,7 @@ def test_add_jitter_numeric_no_duplicates(numeric_df_no_duplicates):
     """Test that no jitter is added when there are no duplicates."""
     result = add_jitter(numeric_df_no_duplicates, "x")
     # No jitter should be added when there are no duplicates
-    pd.testing.assert_series_equal(result["jittered_x"], result["x"], check_names=False)
+    np.testing.assert_allclose(result["jittered_x"], result["x"])
 
 
 @pytest.mark.ci
@@ -121,7 +122,7 @@ def test_add_jitter_explicit_datetime_flag():
     df = pd.DataFrame({"x": ["2023-01-01", "2023-01-01", "2023-01-02"], "y": [10, 15, 20]})
 
     # Without specifying is_datetime, it would treat as strings
-    with pytest.raises(TypeError):
+    with pytest.raises(ValueError):
         _ = add_jitter(df, "x")
 
     # With is_datetime=True, it should convert and jitter as datetimes

doubleml/irm/tests/test_apo_exceptions.py

@@ -25,7 +25,7 @@ def test_apo_exception_data():
     msg = (
         r"The data must be of DoubleMLData or DoubleMLClusterData or DoubleMLDIDData or DoubleMLSSMData or "
         r"DoubleMLRDDData type\. Empty DataFrame\nColumns: \[\]\nIndex: \[\] of type "
-        r"<class 'pandas\.core\.frame\.DataFrame'> was passed\."
+        r"<class 'pandas\..*DataFrame'> was passed\."
     )
     with pytest.raises(TypeError, match=msg):
         _ = DoubleMLAPO(pd.DataFrame(), ml_g, ml_m, treatment_level=0)

doubleml/irm/tests/test_ssm_exceptions.py

@@ -35,7 +35,7 @@ def test_ssm_exception_data():
     msg = (
         r"The data must be of DoubleMLData or DoubleMLClusterData or DoubleMLDIDData or DoubleMLSSMData or "
         r"DoubleMLRDDData type\. Empty DataFrame\nColumns: \[\]\nIndex: \[\] of type "
-        r"<class 'pandas\.core\.frame\.DataFrame'> was passed\."
+        r"<class 'pandas\..*DataFrame'> was passed\."
     )
     with pytest.raises(TypeError, match=msg):
         _ = DoubleMLSSM(pd.DataFrame(), ml_g, ml_pi, ml_m)

doubleml/plm/tests/test_lplr_exceptions.py

@@ -23,7 +23,7 @@
 
 @pytest.mark.ci
 def test_lplr_exception_data():
-    msg = r"The data must be of DoubleMLData.* type\.[\s\S]* of type " r"<class 'pandas\.core\.frame\.DataFrame'> was passed\."
+    msg = r"The data must be of DoubleMLData.*type\."
     with pytest.raises(TypeError, match=msg):
         _ = DoubleMLLPLR(pd.DataFrame(), ml_M, ml_t, ml_m)
 

doubleml/plm/tests/test_plpr_exceptions.py

@@ -61,7 +61,7 @@
 
 @pytest.mark.ci
 def test_plpr_exception_data():
-    msg = "The data must be of DoubleMLPanelData type. <class 'pandas.core.frame.DataFrame'> was passed."
+    msg = r"The data must be of DoubleMLPanelData type. <class 'pandas\..*DataFrame'> was passed."
     with pytest.raises(TypeError, match=msg):
         _ = dml.DoubleMLPLPR(pd.DataFrame(), ml_l, ml_m)
     # not a panel data object

doubleml/utils/tests/test_policytree.py

@@ -98,8 +98,8 @@ def test_doubleml_exception_policytree():
     with pytest.raises(TypeError, match=msg):
         dml_policytree_predict.predict(features=1)
     msg = (
-        r"The features must have the keys Index\(\[\'a\', \'b\', \'c\'\], dtype\=\'object\'\). "
-        r"Features with keys Index\(\[\'d\'\], dtype=\'object\'\) were passed."
+        r"The features must have the keys Index\(\[\'a\', \'b\', \'c\'\], dtype=.*?\)\. "
+        r"Features with keys Index\(\[\'d\'\], dtype=.*?\) were passed\."
     )
     with pytest.raises(KeyError, match=msg):
         dml_policytree_predict.predict(features=pd.DataFrame({"d": [3, 4]}))