Python pandas.core.dtypes.concat.union_categoricals() Examples

The following are 30 code examples of pandas.core.dtypes.concat.union_categoricals(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.core.dtypes.concat , or try the search function .
Example #1
Source File: test_union_categoricals.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def test_union_categorical_unwrap(self):
        # GH 14173
        c1 = Categorical(['a', 'b'])
        c2 = pd.Series(['b', 'c'], dtype='category')
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)

        c2 = CategoricalIndex(c2)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        c1 = Series(c1)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        with pytest.raises(TypeError):
            union_categoricals([c1, ['a', 'b', 'c']])
Example #2
Source File: test_union_categoricals.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_union_categorical_unwrap(self):
        # GH 14173
        c1 = Categorical(['a', 'b'])
        c2 = pd.Series(['b', 'c'], dtype='category')
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)

        c2 = CategoricalIndex(c2)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        c1 = Series(c1)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        with pytest.raises(TypeError):
            union_categoricals([c1, ['a', 'b', 'c']])
Example #3
Source File: test_union_categoricals.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_union_categorical_unwrap(self):
        # GH 14173
        c1 = Categorical(['a', 'b'])
        c2 = pd.Series(['b', 'c'], dtype='category')
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)

        c2 = CategoricalIndex(c2)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        c1 = Series(c1)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        with pytest.raises(TypeError):
            union_categoricals([c1, ['a', 'b', 'c']])
Example #4
Source File: test_union_categoricals.py    From coffeegrindsize with MIT License 6 votes vote down vote up 
def test_union_categorical_unwrap(self):
        # GH 14173
        c1 = Categorical(['a', 'b'])
        c2 = pd.Series(['b', 'c'], dtype='category')
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)

        c2 = CategoricalIndex(c2)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        c1 = Series(c1)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        with pytest.raises(TypeError):
            union_categoricals([c1, ['a', 'b', 'c']])
Example #5
Source File: test_union_categoricals.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_union_categorical_unwrap(self):
        # GH 14173
        c1 = Categorical(['a', 'b'])
        c2 = pd.Series(['b', 'c'], dtype='category')
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)

        c2 = CategoricalIndex(c2)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        c1 = Series(c1)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        with pytest.raises(TypeError):
            union_categoricals([c1, ['a', 'b', 'c']])
Example #6
Source File: test_union_categoricals.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def test_union_categoricals_ordered(self):
        c1 = Categorical([1, 2, 3], ordered=True)
        c2 = Categorical([1, 2, 3], ordered=False)

        msg = 'Categorical.ordered must be the same'
        with tm.assert_raises_regex(TypeError, msg):
            union_categoricals([c1, c2])

        res = union_categoricals([c1, c1])
        exp = Categorical([1, 2, 3, 1, 2, 3], ordered=True)
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical([1, 2, 3, np.nan], ordered=True)
        c2 = Categorical([3, 2], categories=[1, 2, 3], ordered=True)

        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, np.nan, 3, 2], ordered=True)
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical([1, 2, 3], ordered=True)
        c2 = Categorical([1, 2, 3], categories=[3, 2, 1], ordered=True)

        msg = "to union ordered Categoricals, all categories must be the same"
        with tm.assert_raises_regex(TypeError, msg):
            union_categoricals([c1, c2])
Example #7
Source File: test_union_categoricals.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def test_union_categorical_unwrap(self):
        # GH 14173
        c1 = Categorical(['a', 'b'])
        c2 = pd.Series(['b', 'c'], dtype='category')
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)

        c2 = CategoricalIndex(c2)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        c1 = Series(c1)
        result = union_categoricals([c1, c2])
        tm.assert_categorical_equal(result, expected)

        with pytest.raises(TypeError):
            union_categoricals([c1, ['a', 'b', 'c']])
Example #8
Source File: test_union_categoricals.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_union_categorical_same_categories_different_order(self):
        # https://github.com/pandas-dev/pandas/issues/19096
        c1 = Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
        c2 = Categorical(['a', 'b', 'c'], categories=['b', 'a', 'c'])
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'c', 'a', 'b', 'c'],
                               categories=['a', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)
Example #9
Source File: test_union_categoricals.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_union_categoricals_nan(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([1, 2, np.nan]),
                                  pd.Categorical([3, 2, np.nan])])
        exp = Categorical([1, 2, np.nan, 3, 2, np.nan])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical(['A', 'B']),
                                  pd.Categorical(['B', 'B', np.nan])])
        exp = Categorical(['A', 'B', 'B', 'B', np.nan])
        tm.assert_categorical_equal(res, exp)

        val1 = [pd.Timestamp('2011-01-01'), pd.Timestamp('2011-03-01'),
                pd.NaT]
        val2 = [pd.NaT, pd.Timestamp('2011-01-01'),
                pd.Timestamp('2011-02-01')]

        res = union_categoricals([pd.Categorical(val1), pd.Categorical(val2)])
        exp = Categorical(val1 + val2,
                          categories=[pd.Timestamp('2011-01-01'),
                                      pd.Timestamp('2011-03-01'),
                                      pd.Timestamp('2011-02-01')])
        tm.assert_categorical_equal(res, exp)

        # all NaN
        res = union_categoricals([pd.Categorical(np.array([np.nan, np.nan],
                                                          dtype=object)),
                                  pd.Categorical(['X'])])
        exp = Categorical([np.nan, np.nan, 'X'])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical([np.nan, np.nan]),
                                  pd.Categorical([np.nan, np.nan])])
        exp = Categorical([np.nan, np.nan, np.nan, np.nan])
        tm.assert_categorical_equal(res, exp)
Example #10
Source File: test_union_categoricals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_union_categoricals_nan(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([1, 2, np.nan]),
                                  pd.Categorical([3, 2, np.nan])])
        exp = Categorical([1, 2, np.nan, 3, 2, np.nan])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical(['A', 'B']),
                                  pd.Categorical(['B', 'B', np.nan])])
        exp = Categorical(['A', 'B', 'B', 'B', np.nan])
        tm.assert_categorical_equal(res, exp)

        val1 = [pd.Timestamp('2011-01-01'), pd.Timestamp('2011-03-01'),
                pd.NaT]
        val2 = [pd.NaT, pd.Timestamp('2011-01-01'),
                pd.Timestamp('2011-02-01')]

        res = union_categoricals([pd.Categorical(val1), pd.Categorical(val2)])
        exp = Categorical(val1 + val2,
                          categories=[pd.Timestamp('2011-01-01'),
                                      pd.Timestamp('2011-03-01'),
                                      pd.Timestamp('2011-02-01')])
        tm.assert_categorical_equal(res, exp)

        # all NaN
        res = union_categoricals([pd.Categorical([np.nan, np.nan]),
                                  pd.Categorical(['X'])])
        exp = Categorical([np.nan, np.nan, 'X'])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical([np.nan, np.nan]),
                                  pd.Categorical([np.nan, np.nan])])
        exp = Categorical([np.nan, np.nan, np.nan, np.nan])
        tm.assert_categorical_equal(res, exp)
Example #11
Source File: test_union_categoricals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_union_categoricals_empty(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([]),
                                  pd.Categorical([])])
        exp = Categorical([])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([Categorical([]),
                                  Categorical(['1'])])
        exp = Categorical(['1'])
        tm.assert_categorical_equal(res, exp)
Example #12
Source File: test_union_categoricals.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_union_categorical_same_category(self):
        # check fastpath
        c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4])
        c2 = Categorical([3, 2, 1, np.nan], categories=[1, 2, 3, 4])
        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, 4, 3, 2, 1, np.nan],
                          categories=[1, 2, 3, 4])
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical(['z', 'z', 'z'], categories=['x', 'y', 'z'])
        c2 = Categorical(['x', 'x', 'x'], categories=['x', 'y', 'z'])
        res = union_categoricals([c1, c2])
        exp = Categorical(['z', 'z', 'z', 'x', 'x', 'x'],
                          categories=['x', 'y', 'z'])
        tm.assert_categorical_equal(res, exp)
Example #13
Source File: parsers.py    From modin with Apache License 2.0 5 votes vote down vote up 
def find_common_type_cat(types):
    if all(isinstance(t, pandas.CategoricalDtype) for t in types):
        if all(t.ordered for t in types):
            return pandas.CategoricalDtype(
                np.sort(np.unique([c for t in types for c in t.categories])[0]),
                ordered=True,
            )
        return union_categoricals(
            [pandas.Categorical([], dtype=t) for t in types],
            sort_categories=all(t.ordered for t in types),
        ).dtype
    else:
        return find_common_type(types)
Example #14
Source File: test_union_categoricals.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_union_categoricals_nan(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([1, 2, np.nan]),
                                  pd.Categorical([3, 2, np.nan])])
        exp = Categorical([1, 2, np.nan, 3, 2, np.nan])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical(['A', 'B']),
                                  pd.Categorical(['B', 'B', np.nan])])
        exp = Categorical(['A', 'B', 'B', 'B', np.nan])
        tm.assert_categorical_equal(res, exp)

        val1 = [pd.Timestamp('2011-01-01'), pd.Timestamp('2011-03-01'),
                pd.NaT]
        val2 = [pd.NaT, pd.Timestamp('2011-01-01'),
                pd.Timestamp('2011-02-01')]

        res = union_categoricals([pd.Categorical(val1), pd.Categorical(val2)])
        exp = Categorical(val1 + val2,
                          categories=[pd.Timestamp('2011-01-01'),
                                      pd.Timestamp('2011-03-01'),
                                      pd.Timestamp('2011-02-01')])
        tm.assert_categorical_equal(res, exp)

        # all NaN
        res = union_categoricals([pd.Categorical(np.array([np.nan, np.nan],
                                                          dtype=object)),
                                  pd.Categorical(['X'])])
        exp = Categorical([np.nan, np.nan, 'X'])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical([np.nan, np.nan]),
                                  pd.Categorical([np.nan, np.nan])])
        exp = Categorical([np.nan, np.nan, np.nan, np.nan])
        tm.assert_categorical_equal(res, exp)
Example #15
Source File: test_union_categoricals.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_union_categoricals_empty(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([]),
                                  pd.Categorical([])])
        exp = Categorical([])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([Categorical([]),
                                  Categorical(['1'])])
        exp = Categorical(['1'])
        tm.assert_categorical_equal(res, exp)
Example #16
Source File: test_union_categoricals.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_union_categorical_same_category(self):
        # check fastpath
        c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4])
        c2 = Categorical([3, 2, 1, np.nan], categories=[1, 2, 3, 4])
        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, 4, 3, 2, 1, np.nan],
                          categories=[1, 2, 3, 4])
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical(['z', 'z', 'z'], categories=['x', 'y', 'z'])
        c2 = Categorical(['x', 'x', 'x'], categories=['x', 'y', 'z'])
        res = union_categoricals([c1, c2])
        exp = Categorical(['z', 'z', 'z', 'x', 'x', 'x'],
                          categories=['x', 'y', 'z'])
        tm.assert_categorical_equal(res, exp)
Example #17
Source File: test_union_categoricals.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_union_categorical_same_categories_different_order(self):
        # https://github.com/pandas-dev/pandas/issues/19096
        c1 = Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
        c2 = Categorical(['a', 'b', 'c'], categories=['b', 'a', 'c'])
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'c', 'a', 'b', 'c'],
                               categories=['a', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)
Example #18
Source File: test_union_categoricals.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_union_categoricals_nan(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([1, 2, np.nan]),
                                  pd.Categorical([3, 2, np.nan])])
        exp = Categorical([1, 2, np.nan, 3, 2, np.nan])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical(['A', 'B']),
                                  pd.Categorical(['B', 'B', np.nan])])
        exp = Categorical(['A', 'B', 'B', 'B', np.nan])
        tm.assert_categorical_equal(res, exp)

        val1 = [pd.Timestamp('2011-01-01'), pd.Timestamp('2011-03-01'),
                pd.NaT]
        val2 = [pd.NaT, pd.Timestamp('2011-01-01'),
                pd.Timestamp('2011-02-01')]

        res = union_categoricals([pd.Categorical(val1), pd.Categorical(val2)])
        exp = Categorical(val1 + val2,
                          categories=[pd.Timestamp('2011-01-01'),
                                      pd.Timestamp('2011-03-01'),
                                      pd.Timestamp('2011-02-01')])
        tm.assert_categorical_equal(res, exp)

        # all NaN
        res = union_categoricals([pd.Categorical(np.array([np.nan, np.nan],
                                                          dtype=object)),
                                  pd.Categorical(['X'])])
        exp = Categorical([np.nan, np.nan, 'X'])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical([np.nan, np.nan]),
                                  pd.Categorical([np.nan, np.nan])])
        exp = Categorical([np.nan, np.nan, np.nan, np.nan])
        tm.assert_categorical_equal(res, exp)
Example #19
Source File: test_union_categoricals.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_union_categoricals_empty(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([]),
                                  pd.Categorical([])])
        exp = Categorical([])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([Categorical([]),
                                  Categorical(['1'])])
        exp = Categorical(['1'])
        tm.assert_categorical_equal(res, exp)
Example #20
Source File: test_union_categoricals.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_union_categorical_same_category(self):
        # check fastpath
        c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4])
        c2 = Categorical([3, 2, 1, np.nan], categories=[1, 2, 3, 4])
        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, 4, 3, 2, 1, np.nan],
                          categories=[1, 2, 3, 4])
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical(['z', 'z', 'z'], categories=['x', 'y', 'z'])
        c2 = Categorical(['x', 'x', 'x'], categories=['x', 'y', 'z'])
        res = union_categoricals([c1, c2])
        exp = Categorical(['z', 'z', 'z', 'x', 'x', 'x'],
                          categories=['x', 'y', 'z'])
        tm.assert_categorical_equal(res, exp)
Example #21
Source File: test_union_categoricals.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_union_categorical_same_categories_different_order(self):
        # https://github.com/pandas-dev/pandas/issues/19096
        c1 = Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
        c2 = Categorical(['a', 'b', 'c'], categories=['b', 'a', 'c'])
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'c', 'a', 'b', 'c'],
                               categories=['a', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)
Example #22
Source File: test_union_categoricals.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_union_categoricals_empty(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([]),
                                  pd.Categorical([])])
        exp = Categorical([])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([Categorical([]),
                                  Categorical(['1'])])
        exp = Categorical(['1'])
        tm.assert_categorical_equal(res, exp)
Example #23
Source File: test_union_categoricals.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_union_categoricals_empty(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([]),
                                  pd.Categorical([])])
        exp = Categorical([])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([Categorical([]),
                                  Categorical(['1'])])
        exp = Categorical(['1'])
        tm.assert_categorical_equal(res, exp)
Example #24
Source File: test_union_categoricals.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_union_categorical_same_category(self):
        # check fastpath
        c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4])
        c2 = Categorical([3, 2, 1, np.nan], categories=[1, 2, 3, 4])
        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, 4, 3, 2, 1, np.nan],
                          categories=[1, 2, 3, 4])
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical(['z', 'z', 'z'], categories=['x', 'y', 'z'])
        c2 = Categorical(['x', 'x', 'x'], categories=['x', 'y', 'z'])
        res = union_categoricals([c1, c2])
        exp = Categorical(['z', 'z', 'z', 'x', 'x', 'x'],
                          categories=['x', 'y', 'z'])
        tm.assert_categorical_equal(res, exp)
Example #25
Source File: test_union_categoricals.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_union_categorical_same_categories_different_order(self):
        # https://github.com/pandas-dev/pandas/issues/19096
        c1 = Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
        c2 = Categorical(['a', 'b', 'c'], categories=['b', 'a', 'c'])
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'c', 'a', 'b', 'c'],
                               categories=['a', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)
Example #26
Source File: test_union_categoricals.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_union_categoricals_nan(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([1, 2, np.nan]),
                                  pd.Categorical([3, 2, np.nan])])
        exp = Categorical([1, 2, np.nan, 3, 2, np.nan])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical(['A', 'B']),
                                  pd.Categorical(['B', 'B', np.nan])])
        exp = Categorical(['A', 'B', 'B', 'B', np.nan])
        tm.assert_categorical_equal(res, exp)

        val1 = [pd.Timestamp('2011-01-01'), pd.Timestamp('2011-03-01'),
                pd.NaT]
        val2 = [pd.NaT, pd.Timestamp('2011-01-01'),
                pd.Timestamp('2011-02-01')]

        res = union_categoricals([pd.Categorical(val1), pd.Categorical(val2)])
        exp = Categorical(val1 + val2,
                          categories=[pd.Timestamp('2011-01-01'),
                                      pd.Timestamp('2011-03-01'),
                                      pd.Timestamp('2011-02-01')])
        tm.assert_categorical_equal(res, exp)

        # all NaN
        res = union_categoricals([pd.Categorical(np.array([np.nan, np.nan],
                                                          dtype=object)),
                                  pd.Categorical(['X'])])
        exp = Categorical([np.nan, np.nan, 'X'])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([pd.Categorical([np.nan, np.nan]),
                                  pd.Categorical([np.nan, np.nan])])
        exp = Categorical([np.nan, np.nan, np.nan, np.nan])
        tm.assert_categorical_equal(res, exp)
Example #27
Source File: test_union_categoricals.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_union_categoricals_empty(self):
        # GH 13759
        res = union_categoricals([pd.Categorical([]),
                                  pd.Categorical([])])
        exp = Categorical([])
        tm.assert_categorical_equal(res, exp)

        res = union_categoricals([Categorical([]),
                                  Categorical(['1'])])
        exp = Categorical(['1'])
        tm.assert_categorical_equal(res, exp)
Example #28
Source File: test_union_categoricals.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_union_categorical_same_category(self):
        # check fastpath
        c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4])
        c2 = Categorical([3, 2, 1, np.nan], categories=[1, 2, 3, 4])
        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, 4, 3, 2, 1, np.nan],
                          categories=[1, 2, 3, 4])
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical(['z', 'z', 'z'], categories=['x', 'y', 'z'])
        c2 = Categorical(['x', 'x', 'x'], categories=['x', 'y', 'z'])
        res = union_categoricals([c1, c2])
        exp = Categorical(['z', 'z', 'z', 'x', 'x', 'x'],
                          categories=['x', 'y', 'z'])
        tm.assert_categorical_equal(res, exp)
Example #29
Source File: test_union_categoricals.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_union_categorical_same_categories_different_order(self):
        # https://github.com/pandas-dev/pandas/issues/19096
        c1 = Categorical(['a', 'b', 'c'], categories=['a', 'b', 'c'])
        c2 = Categorical(['a', 'b', 'c'], categories=['b', 'a', 'c'])
        result = union_categoricals([c1, c2])
        expected = Categorical(['a', 'b', 'c', 'a', 'b', 'c'],
                               categories=['a', 'b', 'c'])
        tm.assert_categorical_equal(result, expected)
Example #30
Source File: test_union_categoricals.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_union_categorical_same_category(self):
        # check fastpath
        c1 = Categorical([1, 2, 3, 4], categories=[1, 2, 3, 4])
        c2 = Categorical([3, 2, 1, np.nan], categories=[1, 2, 3, 4])
        res = union_categoricals([c1, c2])
        exp = Categorical([1, 2, 3, 4, 3, 2, 1, np.nan],
                          categories=[1, 2, 3, 4])
        tm.assert_categorical_equal(res, exp)

        c1 = Categorical(['z', 'z', 'z'], categories=['x', 'y', 'z'])
        c2 = Categorical(['x', 'x', 'x'], categories=['x', 'y', 'z'])
        res = union_categoricals([c1, c2])
        exp = Categorical(['z', 'z', 'z', 'x', 'x', 'x'],
                          categories=['x', 'y', 'z'])
        tm.assert_categorical_equal(res, exp)