Move test to test_unique and add whats new

doc/source/whatsnew/v0.21.1.txt

@@ -61,6 +61,7 @@ Bug Fixes
 - Bug in :class:`DatetimeIndex` subtracting datetimelike from DatetimeIndex could fail to overflow (:issue:`18020`)
 - Bug in ``pd.Series.rolling.skew()`` and ``rolling.kurt()`` with all equal values has floating issue (:issue:`18044`)
 - Bug in ``pd.DataFrameGroupBy.count()`` when counting over a datetimelike column (:issue:`13393`)
+- Bug in ``pd.Categorical.unique()`` returning read-only array when all categories were ``NaN`` (:issue:`18051`)
 
 Conversion
 ^^^^^^^^^^

pandas/tests/test_categorical.py

@@ -1227,10 +1227,6 @@ def test_set_categories(self):
         exp_categories = Index(["a", "b", "c", "d"])
         tm.assert_index_equal(cat.categories, exp_categories)
 
-        # all-nan categories GH 18051
-        cat_nan = Categorical([np.nan])
-        assert cat_nan.unique()._codes.flags.writeable
-
         # internals...
         c = Categorical([1, 2, 3, 4, 1], categories=[1, 2, 3, 4], ordered=True)
         tm.assert_numpy_array_equal(c._codes, np.array([0, 1, 2, 3, 0],
@@ -1679,6 +1675,10 @@ def test_unique(self):
         exp_cat = Categorical(["b", np.nan, "a"], categories=["b", "a"])
         tm.assert_categorical_equal(res, exp_cat)
 
+        # GH 18051 unique()._codes should be writeable
+        cat_nan = Categorical([np.nan])
+        assert cat_nan.unique()._codes.flags.writeable
+
     def test_unique_ordered(self):
         # keep categories order when ordered=True
         cat = Categorical(['b', 'a', 'b'], categories=['a', 'b'], ordered=True)