Remove test_argsort_nan_loc

Author: makbigc

pandas/tests/extension/test_categorical.py

@@ -68,12 +68,6 @@ def data_missing_for_sorting():
                        ordered=True)
 
 
-@pytest.fixture
-def data_multiple_nan():
-    return Categorical(['E', 'D', None, 'A', None,
-                        None, 'F', 'C', None, 'B'], ordered=True)
-
-
 @pytest.fixture
 def na_value():
     return np.nan

pandas/tests/extension/test_datetime.py

@@ -45,15 +45,6 @@ def data_missing_for_sorting(dtype):
                          dtype=dtype)
 
 
-@pytest.fixture
-def data_multiple_nan(dtype):
-    idx = pd.date_range(start='2000-01-01', end='2000-01-06')
-    return DatetimeArray(np.array([idx[4], idx[3], 'NaT', idx[0], 'NaT',
-                                   'NaT', idx[5], idx[2], 'NaT', idx[1]],
-                                  dtype='datetime64[ns]'),
-                         dtype=dtype)
-
-
 @pytest.fixture
 def data_for_grouping(dtype):
     """

pandas/tests/extension/test_integer.py

@@ -57,12 +57,6 @@ def data_for_sorting(dtype):
     return integer_array([1, 2, 0], dtype=dtype)
 
 
-@pytest.fixture
-def data_multiple_nan(dtype):
-    return integer_array([5, 4, np.nan, 1, np.nan,
-                          np.nan, 6, 3, np.nan, 2], dtype=dtype)
-
-
 @pytest.fixture
 def data_missing_for_sorting(dtype):
     return integer_array([1, np.nan, 0], dtype=dtype)

pandas/tests/extension/test_interval.py

@@ -57,13 +57,6 @@ def data_missing_for_sorting():
     return IntervalArray.from_tuples([(1, 2), None, (0, 1)])
 
 
-@pytest.fixture
-def data_multiple_nan():
-    return IntervalArray.from_tuples([(5, 6), (4, 5), None, (1, 2),
-                                      None, None, (6, 7), (3, 4),
-                                      None, (2, 3)])
-
-
 @pytest.fixture
 def na_value():
     return np.nan

pandas/tests/extension/test_numpy.py

@@ -101,23 +101,6 @@ def data_missing_for_sorting(allow_in_pandas, dtype):
     )
 
 
-@pytest.fixture
-def data_multiple_nan(allow_in_pandas, dtype):
-    """Length-10 array with a known sort order.
-
-    This should be three items [B, NA, A] with
-    A < B and NA missing.
-    """
-    if dtype.numpy_dtype == 'object':
-        return PandasArray(
-            np.array([(5,), (4,), np.nan, (1,), np.nan,
-                      np.nan, (6,), (3,), np.nan, (2,)])
-        )
-    return PandasArray(
-        np.array([5, 4, np.nan, 1, np.nan, np.nan, 6, 3, np.nan, 2])
-    )
-
-
 @pytest.fixture
 def data_for_grouping(allow_in_pandas, dtype):
     """Data for factorization, grouping, and unique tests.

pandas/tests/extension/test_period.py

@@ -40,12 +40,6 @@ def data_missing_for_sorting(dtype):
     return PeriodArray([2018, iNaT, 2017], freq=dtype.freq)
 
 
-@pytest.fixture
-def data_multiple_nan(dtype):
-    return PeriodArray([2005, 2004, iNaT, 2001, iNaT, iNaT,
-                        2006, 2003, iNaT, 2002], freq=dtype.freq)
-
-
 @pytest.fixture
 def data_for_grouping(dtype):
     B = 2018

pandas/tests/extension/test_sparse.py

@@ -65,12 +65,6 @@ def data_missing_for_sorting(request):
     return SparseArray([2, np.nan, 1], fill_value=request.param)
 
 
-@pytest.fixture(params=[0, np.nan])
-def data_multiple_nan(request):
-    return SparseArray([5, 4, np.nan, 1, np.nan,
-                        np.nan, 6, 3, np.nan, 2], fill_value=request.param)
-
-
 @pytest.fixture
 def na_value():
     return np.nan