fix test_categorical.py

Author: reidy-p

pandas/tests/test_categorical.py

@@ -4496,121 +4496,6 @@ def test_numpy_reshape(self):
             tm.assert_raises_regex(ValueError, msg, np.reshape,
                                    cat, cat.shape, order='F')
 
-<<<<<<< HEAD
-    def test_na_actions(self):
-
-        cat = Categorical([1, 2, 3, np.nan], categories=[1, 2, 3])
-        vals = ["a", "b", np.nan, "d"]
-        df = DataFrame({"cats": cat, "vals": vals})
-        cat2 = Categorical([1, 2, 3, 3], categories=[1, 2, 3])
-        vals2 = ["a", "b", "b", "d"]
-        df_exp_fill = DataFrame({"cats": cat2, "vals": vals2})
-        cat3 = Categorical([1, 2, 3], categories=[1, 2, 3])
-        vals3 = ["a", "b", np.nan]
-        df_exp_drop_cats = DataFrame({"cats": cat3, "vals": vals3})
-        cat4 = Categorical([1, 2], categories=[1, 2, 3])
-        vals4 = ["a", "b"]
-        df_exp_drop_all = DataFrame({"cats": cat4, "vals": vals4})
-
-        # fillna
-        res = df.fillna(value={"cats": 3, "vals": "b"})
-        tm.assert_frame_equal(res, df_exp_fill)
-
-        def f():
-            df.fillna(value={"cats": 4, "vals": "c"})
-
-        pytest.raises(ValueError, f)
-
-        res = df.fillna(method='pad')
-        tm.assert_frame_equal(res, df_exp_fill)
-
-        res = df.dropna(subset=["cats"])
-        tm.assert_frame_equal(res, df_exp_drop_cats)
-
-        res = df.dropna()
-        tm.assert_frame_equal(res, df_exp_drop_all)
-
-        # make sure that fillna takes missing values into account
-        c = Categorical([np.nan, "b", np.nan], categories=["a", "b"])
-        df = DataFrame({"cats": c, "vals": [1, 2, 3]})
-
-        cat_exp = Categorical(["a", "b", "a"], categories=["a", "b"])
-        df_exp = DataFrame({"cats": cat_exp, "vals": [1, 2, 3]})
-
-        res = df.fillna("a")
-        tm.assert_frame_equal(res, df_exp)
-
-        # GH 14021
-        # np.nan should always be a is a valid filler
-        cat = Categorical([np.nan, 2, np.nan])
-        val = Categorical([np.nan, np.nan, np.nan])
-        df = DataFrame({"cats": cat, "vals": val})
-        res = df.fillna(df.median())
-        v_exp = [np.nan, np.nan, np.nan]
-        df_exp = DataFrame({"cats": [2, 2, 2], "vals": v_exp},
-                           dtype='category')
-        tm.assert_frame_equal(res, df_exp)
-
-        result = df.cats.fillna(np.nan)
-        tm.assert_series_equal(result, df.cats)
-        result = df.vals.fillna(np.nan)
-        tm.assert_series_equal(result, df.vals)
-
-        idx = DatetimeIndex(['2011-01-01 09:00', '2016-01-01 23:45',
-                             '2011-01-01 09:00', NaT, NaT])
-        df = DataFrame({'a': Categorical(idx)})
-        tm.assert_frame_equal(df.fillna(value=NaT), df)
-
-        idx = PeriodIndex(
-            ['2011-01', '2011-01', '2011-01', NaT, NaT], freq='M')
-        df = DataFrame({'a': Categorical(idx)})
-        tm.assert_frame_equal(df.fillna(value=NaT), df)
-
-        idx = TimedeltaIndex(['1 days', '2 days', '1 days', NaT, NaT])
-        df = DataFrame({'a': Categorical(idx)})
-        tm.assert_frame_equal(df.fillna(value=NaT), df)
-
-    @pytest.mark.parametrize('fill_value, expected_output', [
-        ('a', ['a', 'a', 'b', 'a', 'a']),
-        ({1: 'a', 3: 'b', 4: 'b'}, ['a', 'a', 'b', 'b', 'b']),
-        ({1: 'a'}, ['a', 'a', 'b', np.nan, np.nan]),
-        ({1: 'a', 3: 'b'}, ['a', 'a', 'b', 'b', np.nan]),
-        (pd.Series('a'), ['a', np.nan, 'b', np.nan, np.nan]),
-        (pd.Series('a', index=[1]), ['a', 'a', 'b', np.nan, np.nan]),
-        (pd.Series({1: 'a', 3: 'b'}), ['a', 'a', 'b', 'b', np.nan]),
-        (pd.Series(['a', 'b'], index=[3, 4]), ['a', np.nan, 'b', 'a', 'b'])
-    ])
-    def test_fillna_series_categorical(self, fill_value, expected_output):
-        # GH 17033
-        # Test fillna for a Categorical series
-        data = ['a', np.nan, 'b', np.nan, np.nan]
-        s = pd.Series(pd.Categorical(data, categories=['a', 'b']))
-        exp = pd.Series(pd.Categorical(expected_output, categories=['a', 'b']))
-        tm.assert_series_equal(s.fillna(fill_value), exp)
-
-    def test_fillna_series_categorical_errormsg(self):
-        data = ['a', np.nan, 'b', np.nan, np.nan]
-        s = pd.Series(pd.Categorical(data, categories=['a', 'b']))
-
-        with tm.assert_raises_regex(ValueError,
-                                    "fill value must be in categories"):
-            s.fillna('d')
-
-        with tm.assert_raises_regex(ValueError,
-                                    "fill value must be in categories"):
-            s.fillna(pd.Series('d'))
-
-        with tm.assert_raises_regex(ValueError,
-                                    "fill value must be in categories"):
-            s.fillna({1: 'd', 3: 'a'})
-
-        with tm.assert_raises_regex(TypeError,
-                                    '"value" parameter must be a scalar or '
-                                    'dict, but you passed a "list"'):
-            s.fillna(['a', 'b'])
-
-=======
->>>>>>> move tests and add whatsnew
     def test_astype_to_other(self):
 
         s = self.cat['value_group']