CI: Adjust tests for release of numpy 1.25

pandas/compat/numpy/__init__.py

@@ -9,6 +9,7 @@
 np_version_under1p22 = _nlv < Version("1.22")
 np_version_gte1p24 = _nlv >= Version("1.24")
 np_version_gte1p24p3 = _nlv >= Version("1.24.3")
+np_version_gte1p25 = _nlv >= Version("1.25")
 is_numpy_dev = _nlv.dev is not None
 _min_numpy_ver = "1.21.6"
 

pandas/tests/apply/test_frame_apply_relabeling.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from pandas.compat import is_numpy_dev
+from pandas.compat.numpy import np_version_gte1p25
 
 import pandas as pd
 import pandas._testing as tm
@@ -45,7 +45,7 @@ def test_agg_relabel_multi_columns_multi_methods():
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.xfail(is_numpy_dev, reason="name of min now equals name of np.min")
+@pytest.mark.xfail(np_version_gte1p25, reason="name of min now equals name of np.min")
 def test_agg_relabel_partial_functions():
     # GH 26513, test on partial, functools or more complex cases
     df = pd.DataFrame({"A": [1, 2, 1, 2], "B": [1, 2, 3, 4], "C": [3, 4, 5, 6]})

pandas/tests/dtypes/test_missing.py

@@ -9,7 +9,7 @@
 
 from pandas._libs import missing as libmissing
 from pandas._libs.tslibs import iNaT
-from pandas.compat import is_numpy_dev
+from pandas.compat.numpy import np_version_gte1p25
 
 from pandas.core.dtypes.common import (
     is_float,
@@ -468,7 +468,7 @@ def test_array_equivalent_series(val):
     cm = (
         # stacklevel is chosen to make sense when called from .equals
         tm.assert_produces_warning(FutureWarning, match=msg, check_stacklevel=False)
-        if isinstance(val, str) and not is_numpy_dev
+        if isinstance(val, str) and not np_version_gte1p25
         else nullcontext()
     )
     with cm:

pandas/tests/frame/methods/test_compare.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from pandas.compat import is_numpy_dev
+from pandas.compat.numpy import np_version_gte1p25
 
 import pandas as pd
 import pandas._testing as tm
@@ -269,7 +269,7 @@ def test_compare_ea_and_np_dtype(val1, val2):
         # GH#18463 TODO: is this really the desired behavior?
         expected.loc[1, ("a", "self")] = np.nan
 
-    if val1 is pd.NA and is_numpy_dev:
+    if val1 is pd.NA and np_version_gte1p25:
         # can't compare with numpy array if it contains pd.NA
         with pytest.raises(TypeError, match="boolean value of NA is ambiguous"):
             result = df1.compare(df2, keep_shape=True)

pandas/tests/frame/test_unary.py

@@ -3,7 +3,7 @@
 import numpy as np
 import pytest
 
-from pandas.compat import is_numpy_dev
+from pandas.compat.numpy import np_version_gte1p25
 
 import pandas as pd
 import pandas._testing as tm
@@ -130,7 +130,7 @@ def test_pos_object(self, df):
     )
     def test_pos_object_raises(self, df):
         # GH#21380
-        if is_numpy_dev:
+        if np_version_gte1p25:
             with pytest.raises(
                 TypeError, match=r"^bad operand type for unary \+: \'str\'$"
             ):

pandas/tests/series/methods/test_describe.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from pandas.compat import is_numpy_dev
+from pandas.compat.numpy import np_version_gte1p25
 
 from pandas.core.dtypes.common import (
     is_complex_dtype,
@@ -166,7 +166,7 @@ def test_numeric_result_dtype(self, any_numeric_dtype):
             dtype = "complex128" if is_complex_dtype(any_numeric_dtype) else None
 
         ser = Series([0, 1], dtype=any_numeric_dtype)
-        if dtype == "complex128" and is_numpy_dev:
+        if dtype == "complex128" and np_version_gte1p25:
             with pytest.raises(
                 TypeError, match=r"^a must be an array of real numbers$"
             ):

pandas/tests/series/methods/test_equals.py

@@ -5,7 +5,7 @@
 import pytest
 
 from pandas._libs.missing import is_matching_na
-from pandas.compat import is_numpy_dev
+from pandas.compat.numpy import np_version_gte1p25
 
 from pandas.core.dtypes.common import is_float
 
@@ -51,7 +51,7 @@ def test_equals_list_array(val):
 
     cm = (
         tm.assert_produces_warning(FutureWarning, check_stacklevel=False)
-        if isinstance(val, str) and not is_numpy_dev
+        if isinstance(val, str) and not np_version_gte1p25
         else nullcontext()
     )
     with cm: