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tmnhat2001
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Add test_drop_duplicates for Categorical dtypes
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‎pandas/tests/test_categorical.py

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Original file line numberDiff line numberDiff line change
@@ -797,6 +797,149 @@ def test_set_categories_inplace(self):
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cat.set_categories(['a', 'b', 'c', 'd'], inplace=True)
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tm.assert_index_equal(cat.categories, pd.Index(['a', 'b', 'c', 'd']))
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@pytest.mark.parametrize(
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"input1, input2, cat_array",
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[
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(
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np.array([1, 2, 3, 3], dtype=np.dtype('int_')),
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np.array([1, 2, 3, 5, 3, 2, 4], dtype=np.dtype('int_')),
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np.array([1, 2, 3, 4, 5], dtype=np.dtype('int_'))
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),
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(
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np.array([1, 2, 3, 3], dtype=np.dtype('uint')),
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np.array([1, 2, 3, 5, 3, 2, 4], dtype=np.dtype('uint')),
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np.array([1, 2, 3, 4, 5], dtype=np.dtype('uint'))
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),
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(
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np.array([1, 2, 3, 3], dtype=np.dtype('float_')),
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np.array([1, 2, 3, 5, 3, 2, 4], dtype=np.dtype('float_')),
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np.array([1, 2, 3, 4, 5], dtype=np.dtype('float_'))
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),
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(
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np.array(
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[1, 2, 3, 3], dtype=np.dtype('unicode_')
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),
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np.array(
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[1, 2, 3, 5, 3, 2, 4], dtype=np.dtype('unicode_')
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),
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np.array(
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[1, 2, 3, 4, 5], dtype=np.dtype('unicode_')
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)
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),
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(
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np.array(
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[
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'2017-01-01 10:00:00', '2017-02-01 10:00:00',
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'2017-03-01 10:00:00', '2017-03-01 10:00:00'
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],
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dtype='datetime64'
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),
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np.array(
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[
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'2017-01-01 10:00:00', '2017-02-01 10:00:00',
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'2017-03-01 10:00:00', '2017-05-01 10:00:00',
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'2017-03-01 10:00:00', '2017-02-01 10:00:00',
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'2017-04-01 10:00:00'
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],
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dtype='datetime64'
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),
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np.array(
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[
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'2017-01-01 10:00:00', '2017-02-01 10:00:00',
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'2017-03-01 10:00:00', '2017-04-01 10:00:00',
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'2017-05-01 10:00:00'
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],
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dtype='datetime64'
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)
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),
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(
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pd.to_timedelta(['1 days', '2 days', '3 days', '3 days'],
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unit="D"),
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pd.to_timedelta(['1 days', '2 days', '3 days', '5 days',
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'3 days', '2 days', '4 days'], unit="D"),
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pd.timedelta_range("1 days", periods=5, freq="D")
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)
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]
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)
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@pytest.mark.parametrize("is_ordered", [True, False])
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def test_drop_duplicates_non_bool(self, input1, input2,
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cat_array, is_ordered):
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# Test case 1
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tc1 = Series(Categorical(input1, categories=cat_array,
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ordered=is_ordered))
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expected = Series([False, False, False, True])
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tm.assert_series_equal(tc1.duplicated(), expected)
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tm.assert_series_equal(tc1.drop_duplicates(), tc1[~expected])
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sc = tc1.copy()
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sc.drop_duplicates(inplace=True)
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tm.assert_series_equal(sc, tc1[~expected])
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expected = Series([False, False, True, False])
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tm.assert_series_equal(tc1.duplicated(keep='last'), expected)
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tm.assert_series_equal(tc1.drop_duplicates(keep='last'),
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tc1[~expected])
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sc = tc1.copy()
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sc.drop_duplicates(keep='last', inplace=True)
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tm.assert_series_equal(sc, tc1[~expected])
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expected = Series([False, False, True, True])
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tm.assert_series_equal(tc1.duplicated(keep=False), expected)
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tm.assert_series_equal(tc1.drop_duplicates(keep=False), tc1[~expected])
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sc = tc1.copy()
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sc.drop_duplicates(keep=False, inplace=True)
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tm.assert_series_equal(sc, tc1[~expected])
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# Test case 2
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tc2 = Series(Categorical(input2, categories=cat_array,
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ordered=is_ordered))
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expected = Series([False, False, False, False, True, True, False])
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tm.assert_series_equal(tc2.duplicated(), expected)
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tm.assert_series_equal(tc2.drop_duplicates(), tc2[~expected])
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sc = tc2.copy()
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sc.drop_duplicates(inplace=True)
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tm.assert_series_equal(sc, tc2[~expected])
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expected = Series([False, True, True, False, False, False, False])
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tm.assert_series_equal(tc2.duplicated(keep='last'), expected)
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tm.assert_series_equal(tc2.drop_duplicates(keep='last'),
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tc2[~expected])
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sc = tc2.copy()
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sc.drop_duplicates(keep='last', inplace=True)
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tm.assert_series_equal(sc, tc2[~expected])
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expected = Series([False, True, True, False, True, True, False])
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tm.assert_series_equal(tc2.duplicated(keep=False), expected)
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tm.assert_series_equal(tc2.drop_duplicates(keep=False), tc2[~expected])
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sc = tc2.copy()
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sc.drop_duplicates(keep=False, inplace=True)
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tm.assert_series_equal(sc, tc2[~expected])
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@pytest.mark.parametrize("is_ordered", [True, False])
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def test_drop_duplicates_bool(self, is_ordered):
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tc = Series(Categorical([True, False, True, False],
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categories=[True, False], ordered=is_ordered))
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expected = Series([False, False, True, True])
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tm.assert_series_equal(tc.duplicated(), expected)
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tm.assert_series_equal(tc.drop_duplicates(), tc[~expected])
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sc = tc.copy()
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sc.drop_duplicates(inplace=True)
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tm.assert_series_equal(sc, tc[~expected])
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expected = Series([True, True, False, False])
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tm.assert_series_equal(tc.duplicated(keep='last'), expected)
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tm.assert_series_equal(tc.drop_duplicates(keep='last'), tc[~expected])
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sc = tc.copy()
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sc.drop_duplicates(keep='last', inplace=True)
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tm.assert_series_equal(sc, tc[~expected])
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expected = Series([True, True, True, True])
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tm.assert_series_equal(tc.duplicated(keep=False), expected)
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tm.assert_series_equal(tc.drop_duplicates(keep=False), tc[~expected])
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sc = tc.copy()
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sc.drop_duplicates(keep=False, inplace=True)
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tm.assert_series_equal(sc, tc[~expected])
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def test_describe(self):
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# string type
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desc = self.factor.describe()

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