CLN: use fixture for ordered

Author: topper-123

pandas/conftest.py

@@ -126,6 +126,12 @@ def observed(request):
     return request.param
 
 
+@pytest.fixture(params=[True, False, None])
+def ordered(request):
+    """Boolean 'ordered' parameter for Categorical."""
+    return request.param
+
+
 _all_arithmetic_operators = ['__add__', '__radd__',
                              '__sub__', '__rsub__',
                              '__mul__', '__rmul__',

pandas/tests/arrays/categorical/conftest.py

@@ -5,9 +5,3 @@
 def allow_fill(request):
     """Boolean 'allow_fill' parameter for Categorical.take"""
     return request.param
-
-
-@pytest.fixture(params=[True, False])
-def ordered(request):
-    """Boolean 'ordered' parameter for Categorical."""
-    return request.param

pandas/tests/dtypes/test_dtypes.py

@@ -20,11 +20,6 @@
 import pandas.util.testing as tm
 
 
-@pytest.fixture(params=[True, False, None])
-def ordered(request):
-    return request.param
-
-
 class Base(object):
 
     def setup_method(self, method):

pandas/tests/series/test_analytics.py

@@ -1408,14 +1408,13 @@ def test_value_counts_with_nan(self):
          pytest.param("datetime64[D]",
                       marks=pytest.mark.xfail(reason="GH#7996"))]
     )
-    @pytest.mark.parametrize("is_ordered", [True, False])
-    def test_drop_duplicates_categorical_non_bool(self, dtype, is_ordered):
+    def test_drop_duplicates_categorical_non_bool(self, dtype, ordered):
         cat_array = np.array([1, 2, 3, 4, 5], dtype=np.dtype(dtype))
 
         # Test case 1
         input1 = np.array([1, 2, 3, 3], dtype=np.dtype(dtype))
         tc1 = Series(Categorical(input1, categories=cat_array,
-                                 ordered=is_ordered))
+                                 ordered=ordered))
 
         expected = Series([False, False, False, True])
         tm.assert_series_equal(tc1.duplicated(), expected)
@@ -1442,7 +1441,7 @@ def test_drop_duplicates_categorical_non_bool(self, dtype, is_ordered):
         # Test case 2
         input2 = np.array([1, 2, 3, 5, 3, 2, 4], dtype=np.dtype(dtype))
         tc2 = Series(Categorical(
-            input2, categories=cat_array, ordered=is_ordered)
+            input2, categories=cat_array, ordered=ordered)
         )
 
         expected = Series([False, False, False, False, True, True, False])
@@ -1467,10 +1466,9 @@ def test_drop_duplicates_categorical_non_bool(self, dtype, is_ordered):
         sc.drop_duplicates(keep=False, inplace=True)
         tm.assert_series_equal(sc, tc2[~expected])
 
-    @pytest.mark.parametrize("is_ordered", [True, False])
-    def test_drop_duplicates_categorical_bool(self, is_ordered):
+    def test_drop_duplicates_categorical_bool(self, ordered):
         tc = Series(Categorical([True, False, True, False],
-                                categories=[True, False], ordered=is_ordered))
+                                categories=[True, False], ordered=ordered))
 
         expected = Series([False, False, True, True])
         tm.assert_series_equal(tc.duplicated(), expected)