Update normalize value_counts test

Author: kotamatsuoka

pandas/tests/extension/base/methods.py

@@ -30,12 +30,13 @@ def test_value_counts(self, all_data, dropna):
 
     def test_value_counts_with_normalize(self, data):
         data = data[:10].unique()
+        values = np.array(data[~data.isna()])
 
         result = (
             pd.Series(data, dtype=data.dtype).value_counts(normalize=True).sort_index()
         )
 
-        expected = pd.Series([1 / len(data)] * len(data), index=result.index)
+        expected = pd.Series([1 / len(values)] * len(values), index=result.index)
         self.assert_series_equal(result, expected)
 
     def test_count(self, data_missing):

pandas/tests/extension/test_boolean.py

@@ -230,10 +230,6 @@ def test_searchsorted(self, data_for_sorting, as_series):
     def test_value_counts(self, all_data, dropna):
         return super().test_value_counts(all_data, dropna)
 
-    @pytest.mark.skip(reason="uses nullable integer")
-    def test_value_counts_with_normalize(self, data):
-        return super().test_value_counts_with_normalize(data)
-
 
 class TestCasting(base.BaseCastingTests):
     pass

pandas/tests/extension/test_integer.py

@@ -224,10 +224,6 @@ def test_value_counts(self, all_data, dropna):
 
         self.assert_series_equal(result, expected)
 
-    @pytest.mark.xfail(reason="not working with nan")
-    def test_value_counts_with_normalize(self, data):
-        super().test_value_counts_with_normalize(data)
-
 
 class TestCasting(base.BaseCastingTests):
     pass

pandas/tests/extension/test_sparse.py

@@ -229,10 +229,6 @@ def test_fillna_frame(self, data_missing):
 
 
 class TestMethods(BaseSparseTests, base.BaseMethodsTests):
-    @pytest.mark.xfail(reason="not working with nan")
-    def test_value_counts_with_normalize(self):
-        super().test_value_counts_with_normalize(data)
-
     def test_combine_le(self, data_repeated):
         # We return a Series[SparseArray].__le__ returns a
         # Series[Sparse[bool]]