Exemple #1
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    def test_repr_truncation(self):
        max_len = 20
        with option_context("display.max_colwidth", max_len):
            df = DataFrame({
                'A':
                np.random.randn(10),
                'B': [
                    tm.rands(np.random.randint(max_len - 1, max_len + 1))
                    for i in range(10)
                ]
            })
            r = repr(df)
            r = r[r.find('\n') + 1:]

            _strlen = fmt._strlen_func()

            for line, value in zip(r.split('\n'), df['B']):
                if _strlen(value) + 1 > max_len:
                    self.assert_('...' in line)
                else:
                    self.assert_('...' not in line)

        with option_context("display.max_colwidth", 999999):
            self.assert_('...' not in repr(df))

        with option_context("display.max_colwidth", max_len + 2):
            self.assert_('...' not in repr(df))
Exemple #2
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    def test_wide_repr_multiindex_cols(self):
        with option_context('mode.sim_interactive', True):
            col = lambda l, k: [tm.rands(k) for _ in xrange(l)]
            midx = pandas.MultiIndex.from_arrays(
                [np.array(col(10, 5)),
                 np.array(col(10, 5))])
            mcols = pandas.MultiIndex.from_arrays(
                [np.array(col(20, 3)),
                 np.array(col(20, 3))])
            df = DataFrame([col(20, 25) for _ in range(10)],
                           index=midx,
                           columns=mcols)
            df.index.names = ['Level 0', 'Level 1']
            set_option('display.expand_frame_repr', False)
            rep_str = repr(df)
            set_option('display.expand_frame_repr', True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

        with option_context('display.line_width', 120):
            wider_repr = repr(df)
            self.assert_(len(wider_repr) < len(wide_repr))
            self.assert_(len(wide_repr.splitlines()) == 14 * 10 - 1)

        reset_option('display.expand_frame_repr')
Exemple #3
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    def test_repr_truncation(self):
        max_len = 20
        with option_context("display.max_colwidth", max_len):
            df = DataFrame(
                {
                    "A": np.random.randn(10),
                    "B": [tm.rands(np.random.randint(max_len - 1, max_len + 1)) for i in range(10)],
                }
            )
            r = repr(df)
            r = r[r.find("\n") + 1 :]

            _strlen = fmt._strlen_func()

            for line, value in zip(r.split("\n"), df["B"]):
                if _strlen(value) + 1 > max_len:
                    self.assert_("..." in line)
                else:
                    self.assert_("..." not in line)

        with option_context("display.max_colwidth", 999999):
            self.assert_("..." not in repr(df))

        with option_context("display.max_colwidth", max_len + 2):
            self.assert_("..." not in repr(df))
Exemple #4
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def test_notnull():
    assert notnull(1.)
    assert not notnull(None)
    assert not notnull(np.NaN)

    with cf.option_context("mode.use_inf_as_null", False):
        assert notnull(np.inf)
        assert notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.all()

    with cf.option_context("mode.use_inf_as_null", True):
        assert not notnull(np.inf)
        assert not notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.sum() == 2

    with cf.option_context("mode.use_inf_as_null", False):
        float_series = Series(np.random.randn(5))
        obj_series = Series(np.random.randn(5), dtype=object)
        assert (isinstance(notnull(float_series), Series))
        assert (isinstance(notnull(obj_series), Series))
Exemple #5
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def test_notnull():
    assert notnull(1.)
    assert not notnull(None)
    assert not notnull(np.NaN)

    with cf.option_context("mode.use_inf_as_null", False):
        assert notnull(np.inf)
        assert notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.all()

    with cf.option_context("mode.use_inf_as_null", True):
        assert not notnull(np.inf)
        assert not notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.sum() == 2

    with cf.option_context("mode.use_inf_as_null", False):
        for s in [tm.makeFloatSeries(), tm.makeStringSeries(),
                  tm.makeObjectSeries(), tm.makeTimeSeries(),
                  tm.makePeriodSeries()]:
            assert (isinstance(isnull(s), Series))
Exemple #6
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def test_notnull():
    assert notnull(1.)
    assert not notnull(None)
    assert not notnull(np.NaN)

    with cf.option_context("mode.use_inf_as_null", False):
        assert notnull(np.inf)
        assert notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.all()

    with cf.option_context("mode.use_inf_as_null", True):
        assert not notnull(np.inf)
        assert not notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.sum() == 2

    with cf.option_context("mode.use_inf_as_null", False):
        for s in [tm.makeFloatSeries(),tm.makeStringSeries(),
                  tm.makeObjectSeries(),tm.makeTimeSeries(),tm.makePeriodSeries()]:
            assert(isinstance(isnull(s), Series))
Exemple #7
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def test_notnull():
    assert notnull(1.)
    assert not notnull(None)
    assert not notnull(np.NaN)

    with cf.option_context("mode.use_inf_as_null", False):
        assert notnull(np.inf)
        assert notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.all()

    with cf.option_context("mode.use_inf_as_null", True):
        assert not notnull(np.inf)
        assert not notnull(-np.inf)

        arr = np.array([1.5, np.inf, 3.5, -np.inf])
        result = notnull(arr)
        assert result.sum() == 2

    with cf.option_context("mode.use_inf_as_null", False):
        float_series = Series(np.random.randn(5))
        obj_series = Series(np.random.randn(5), dtype=object)
        assert(isinstance(notnull(float_series), Series))
        assert(isinstance(notnull(obj_series), Series))
Exemple #8
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    def test_repr_chop_threshold(self):
        df = DataFrame([[0.1, 0.5],[0.5, -0.1]])
        pd.reset_option("display.chop_threshold") # default None
        self.assertEqual(repr(df), '     0    1\n0  0.1  0.5\n1  0.5 -0.1')

        with option_context("display.chop_threshold", 0.2 ):
            self.assertEqual(repr(df), '     0    1\n0  0.0  0.5\n1  0.5  0.0')

        with option_context("display.chop_threshold", 0.6 ):
            self.assertEqual(repr(df), '   0  1\n0  0  0\n1  0  0')

        with option_context("display.chop_threshold", None ):
            self.assertEqual(repr(df),  '     0    1\n0  0.1  0.5\n1  0.5 -0.1')
Exemple #9
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    def test_repr_chop_threshold(self):
        df = DataFrame([[0.1, 0.5], [0.5, -0.1]])
        pd.reset_option("display.chop_threshold")  # default None
        self.assertEqual(repr(df), '     0    1\n0  0.1  0.5\n1  0.5 -0.1')

        with option_context("display.chop_threshold", 0.2):
            self.assertEqual(repr(df), '     0    1\n0  0.0  0.5\n1  0.5  0.0')

        with option_context("display.chop_threshold", 0.6):
            self.assertEqual(repr(df), '   0  1\n0  0  0\n1  0  0')

        with option_context("display.chop_threshold", None):
            self.assertEqual(repr(df), '     0    1\n0  0.1  0.5\n1  0.5 -0.1')
Exemple #10
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    def test_wide_repr_unicode(self):
        with option_context('mode.sim_interactive', True):
            col = lambda l, k: [tm.randu(k) for _ in xrange(l)]
            df = DataFrame([col(20, 25) for _ in range(10)])
            set_option('display.expand_frame_repr', False)
            rep_str = repr(df)
            set_option('display.expand_frame_repr', True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

            with option_context('display.line_width', 120):
                wider_repr = repr(df)
                self.assert_(len(wider_repr) < len(wide_repr))

        reset_option('display.expand_frame_repr')
Exemple #11
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    def test_wide_repr_unicode(self):
        with option_context('mode.sim_interactive', True):
            col = lambda l, k: [tm.randu(k) for _ in xrange(l)]
            df = DataFrame([col(20, 25) for _ in range(10)])
            set_option('display.expand_frame_repr', False)
            rep_str = repr(df)
            set_option('display.expand_frame_repr', True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

            with option_context('display.line_width', 120):
                wider_repr = repr(df)
                self.assert_(len(wider_repr) < len(wide_repr))

        reset_option('display.expand_frame_repr')
Exemple #12
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    def test_wide_repr(self):
        with option_context("mode.sim_interactive", True):
            col = lambda l, k: [tm.rands(k) for _ in xrange(l)]
            df = DataFrame([col(20, 25) for _ in range(10)])
            set_option("print.expand_frame_repr", False)
            rep_str = repr(df)
            set_option("print.expand_frame_repr", True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

            with option_context("print.line_width", 120):
                wider_repr = repr(df)
                self.assert_(len(wider_repr) < len(wide_repr))

        reset_option("print.expand_frame_repr")
Exemple #13
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    def test_wide_repr_wide_long_columns(self):
        with option_context('mode.sim_interactive', True):
            df = DataFrame({'a': ['a'*30, 'b'*30], 'b': ['c'*70, 'd'*80]})

            result = repr(df)
            self.assertTrue('ccccc' in result)
            self.assertTrue('ddddd' in result)
Exemple #14
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    def test_unicode_print(self):
        if PY3:
            _rep = repr
        else:
            _rep = unicode  # noqa

        c = Categorical(['aaaaa', 'bb', 'cccc'] * 20)
        expected = u"""\
[aaaaa, bb, cccc, aaaaa, bb, ..., bb, cccc, aaaaa, bb, cccc]
Length: 60
Categories (3, object): [aaaaa, bb, cccc]"""

        assert _rep(c) == expected

        c = Categorical([u'ああああ', u'いいいいい', u'ううううううう'] * 20)
        expected = u"""\
[ああああ, いいいいい, ううううううう, ああああ, いいいいい, ..., いいいいい, ううううううう, ああああ, いいいいい, ううううううう]
Length: 60
Categories (3, object): [ああああ, いいいいい, ううううううう]"""  # noqa

        assert _rep(c) == expected

        # unicode option should not affect to Categorical, as it doesn't care
        # the repr width
        with option_context('display.unicode.east_asian_width', True):

            c = Categorical([u'ああああ', u'いいいいい', u'ううううううう'] * 20)
            expected = u"""[ああああ, いいいいい, ううううううう, ああああ, いいいいい, ..., いいいいい, ううううううう, ああああ, いいいいい, ううううううう]
Length: 60
Categories (3, object): [ああああ, いいいいい, ううううううう]"""  # noqa

            assert _rep(c) == expected
Exemple #15
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    def test_unicode_print(self):
        if PY3:
            _rep = repr
        else:
            _rep = unicode  # noqa

        c = Categorical(['aaaaa', 'bb', 'cccc'] * 20)
        expected = u"""\
[aaaaa, bb, cccc, aaaaa, bb, ..., bb, cccc, aaaaa, bb, cccc]
Length: 60
Categories (3, object): [aaaaa, bb, cccc]"""

        assert _rep(c) == expected

        c = Categorical([u'ああああ', u'いいいいい', u'ううううううう'] * 20)
        expected = u"""\
[ああああ, いいいいい, ううううううう, ああああ, いいいいい, ..., いいいいい, ううううううう, ああああ, いいいいい, ううううううう]
Length: 60
Categories (3, object): [ああああ, いいいいい, ううううううう]"""  # noqa

        assert _rep(c) == expected

        # unicode option should not affect to Categorical, as it doesn't care
        # the repr width
        with option_context('display.unicode.east_asian_width', True):

            c = Categorical([u'ああああ', u'いいいいい', u'ううううううう'] * 20)
            expected = u"""[ああああ, いいいいい, ううううううう, ああああ, いいいいい, ..., いいいいい, ううううううう, ああああ, いいいいい, ううううううう]
Length: 60
Categories (3, object): [ああああ, いいいいい, ううううううう]"""  # noqa

            assert _rep(c) == expected
Exemple #16
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    def test_wide_repr_wide_long_columns(self):
        with option_context("mode.sim_interactive", True):
            df = DataFrame({"a": ["a" * 30, "b" * 30], "b": ["c" * 70, "d" * 80]})

            result = repr(df)
            self.assertTrue("ccccc" in result)
            self.assertTrue("ddddd" in result)
Exemple #17
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    def test_transform_mixed_type(self):
        index = MultiIndex.from_arrays([[0, 0, 0, 1, 1, 1], [1, 2, 3, 1, 2,
                                                             3]])
        df = DataFrame(
            {
                'd': [1., 1., 1., 2., 2., 2.],
                'c': np.tile(['a', 'b', 'c'], 2),
                'v': np.arange(1., 7.)
            },
            index=index)

        def f(group):
            group['g'] = group['d'] * 2
            return group[:1]

        grouped = df.groupby('c')
        result = grouped.apply(f)

        assert result['d'].dtype == np.float64

        # this is by definition a mutating operation!
        with option_context('mode.chained_assignment', None):
            for key, group in grouped:
                res = f(group)
                assert_frame_equal(res, result.loc[key])
Exemple #18
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    def test_print_none_width(self):
        # GH10087
        a = Series(Categorical([1, 2, 3, 4]))
        exp = u("0    1\n1    2\n2    3\n3    4\n" +
                "dtype: category\nCategories (4, int64): [1, 2, 3, 4]")

        with option_context("display.width", None):
            assert exp == repr(a)
Exemple #19
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    def test_print_none_width(self):
        # GH10087
        a = Series(Categorical([1, 2, 3, 4]))
        exp = u("0    1\n1    2\n2    3\n3    4\n" +
                "dtype: category\nCategories (4, int64): [1, 2, 3, 4]")

        with option_context("display.width", None):
            assert exp == repr(a)
Exemple #20
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    def test_repr_obeys_max_seq_limit(self):
        import pandas.core.common as com

        # unlimited
        reset_option("display.max_seq_items")
        self.assertTrue(len(com.pprint_thing(range(1000))) > 2000)

        with option_context("display.max_seq_items", 5):
            self.assertTrue(len(com.pprint_thing(range(1000))) < 100)
Exemple #21
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def test_notnull():
    assert notnull(1.)
    assert not notnull(None)
    assert not notnull(np.NaN)

    with cf.option_context("mode.use_inf_as_null",False):
        assert notnull(np.inf)
        assert notnull(-np.inf)

    with cf.option_context("mode.use_inf_as_null",True):
        assert not notnull(np.inf)
        assert not notnull(-np.inf)

    with cf.option_context("mode.use_inf_as_null",False):
        float_series = Series(np.random.randn(5))
        obj_series = Series(np.random.randn(5), dtype=object)
        assert(isinstance(notnull(float_series), Series))
        assert(isinstance(notnull(obj_series), Series))
Exemple #22
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    def test_matplotlib_formatters(self):
        units = pytest.importorskip("matplotlib.units")
        assert Timestamp in units.registry

        ctx = cf.option_context("plotting.matplotlib.register_converters",
                                False)
        with ctx:
            assert Timestamp not in units.registry

        assert Timestamp in units.registry
Exemple #23
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    def test_wide_repr_multiindex_cols(self):
        with option_context("mode.sim_interactive", True):
            col = lambda l, k: [tm.rands(k) for _ in xrange(l)]
            midx = pandas.MultiIndex.from_arrays([np.array(col(10, 5)), np.array(col(10, 5))])
            mcols = pandas.MultiIndex.from_arrays([np.array(col(20, 3)), np.array(col(20, 3))])
            df = DataFrame([col(20, 25) for _ in range(10)], index=midx, columns=mcols)
            df.index.names = ["Level 0", "Level 1"]
            set_option("display.expand_frame_repr", False)
            rep_str = repr(df)
            set_option("display.expand_frame_repr", True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

        with option_context("display.line_width", 120):
            wider_repr = repr(df)
            self.assert_(len(wider_repr) < len(wide_repr))
            self.assert_(len(wide_repr.splitlines()) == 14 * 10 - 1)

        reset_option("display.expand_frame_repr")
Exemple #24
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    def test_matplotlib_formatters(self):
        units = pytest.importorskip("matplotlib.units")
        assert Timestamp in units.registry

        ctx = cf.option_context("plotting.matplotlib.register_converters",
                                False)
        with ctx:
            assert Timestamp not in units.registry

        assert Timestamp in units.registry
Exemple #25
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    def test_wide_repr_wide_long_columns(self):
        with option_context('mode.sim_interactive', True):
            df = DataFrame({
                'a': ['a' * 30, 'b' * 30],
                'b': ['c' * 70, 'd' * 80]
            })

            result = repr(df)
            self.assertTrue('ccccc' in result)
            self.assertTrue('ddddd' in result)
Exemple #26
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    def test_wide_repr_multiindex(self):
        with option_context("mode.sim_interactive", True):
            col = lambda l, k: [tm.rands(k) for _ in xrange(l)]
            midx = pandas.MultiIndex.from_arrays([np.array(col(10, 5)), np.array(col(10, 5))])
            df = DataFrame([col(20, 25) for _ in range(10)], index=midx)
            df.index.names = ["Level 0", "Level 1"]
            set_option("print.expand_frame_repr", False)
            rep_str = repr(df)
            set_option("print.expand_frame_repr", True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

            with option_context("print.line_width", 120):
                wider_repr = repr(df)
                self.assert_(len(wider_repr) < len(wide_repr))

            for line in wide_repr.splitlines()[1::13]:
                self.assert_("Level 0 Level 1" in line)

        reset_option("print.expand_frame_repr")
Exemple #27
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    def test_sparse_frame(self):
        # GH 13110
        df = pd.DataFrame({'A': [True, False, True, False, True],
                           'B': [True, False, True, False, True],
                           'C': [0, 0, 3, 0, 5],
                           'D': [np.nan, np.nan, np.nan, 1, 2]})
        sparse = df.to_sparse()
        self.assertEqual(repr(sparse), repr(df))

        with option_context("display.max_rows", 3):
            self.assertEqual(repr(sparse), repr(df))
Exemple #28
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    def test_wide_repr_named(self):
        with option_context('mode.sim_interactive', True):
            col = lambda l, k: [tm.rands(k) for _ in xrange(l)]
            df = DataFrame([col(20, 25) for _ in range(10)])
            df.index.name = 'DataFrame Index'
            set_option('display.expand_frame_repr', False)

            rep_str = repr(df)
            set_option('display.expand_frame_repr', True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

            with option_context('display.line_width', 120):
                wider_repr = repr(df)
                self.assert_(len(wider_repr) < len(wide_repr))

            for line in wide_repr.splitlines()[1::13]:
                self.assert_('DataFrame Index' in line)

        reset_option('display.expand_frame_repr')
Exemple #29
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    def test_sparse_frame(self):
        # GH 13110
        df = pd.DataFrame({'A': [True, False, True, False, True],
                           'B': [True, False, True, False, True],
                           'C': [0, 0, 3, 0, 5],
                           'D': [np.nan, np.nan, np.nan, 1, 2]})
        sparse = df.to_sparse()
        assert repr(sparse) == repr(df)

        with option_context("display.max_rows", 3):
            assert repr(sparse) == repr(df)
Exemple #30
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    def test_wide_repr_named(self):
        with option_context('mode.sim_interactive', True):
            col = lambda l, k: [tm.rands(k) for _ in xrange(l)]
            df = DataFrame([col(20, 25) for _ in range(10)])
            df.index.name = 'DataFrame Index'
            set_option('display.expand_frame_repr', False)

            rep_str = repr(df)
            set_option('display.expand_frame_repr', True)
            wide_repr = repr(df)
            self.assert_(rep_str != wide_repr)

            with option_context('display.line_width', 120):
                wider_repr = repr(df)
                self.assert_(len(wider_repr) < len(wide_repr))

            for line in wide_repr.splitlines()[1::13]:
                self.assert_('DataFrame Index' in line)

        reset_option('display.expand_frame_repr')
Exemple #31
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    def test_sparsea_max_row_truncated(self):
        s = pd.Series([1, np.nan, np.nan, 3, np.nan]).to_sparse()
        dfm = self.dtype_format_for_platform

        with option_context("display.max_rows", 3):
            # GH 10560
            result = repr(s)
            exp = ("0    1.0\n    ... \n4    NaN\n"
                   "Length: 5, dtype: Sparse[float64, nan]\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dfm))
            assert result == exp
Exemple #32
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    def test_sparsea_max_row_truncated(self):
        s = pd.Series([1, np.nan, np.nan, 3, np.nan]).to_sparse()
        dfm = self.dtype_format_for_platform

        with option_context("display.max_rows", 3):
            # GH 10560
            result = repr(s)
            exp = ("0    1.0\n    ... \n4    NaN\n"
                   "Length: 5, dtype: Sparse[float64, nan]\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dfm))
            assert result == exp
Exemple #33
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    def test_ambiguous_width(self):
        adj = fmt.EastAsianTextAdjustment()
        assert adj.len(u'¡¡ab') == 4

        with cf.option_context('display.unicode.ambiguous_as_wide', True):
            adj = fmt.EastAsianTextAdjustment()
            assert adj.len(u'¡¡ab') == 6

        data = [[u'あ', 'b', 'c'], ['dd', u'ええ', 'ff'],
                ['ggg', u'¡¡ab', u'いいい']]
        expected = u'あ  dd    ggg \nb   ええ  ¡¡ab\nc   ff    いいい'
        adjoined = adj.adjoin(2, *data)
        assert adjoined == expected
Exemple #34
0
    def test_ambiguous_width(self):
        adj = fmt.EastAsianTextAdjustment()
        assert adj.len(u'¡¡ab') == 4

        with cf.option_context('display.unicode.ambiguous_as_wide', True):
            adj = fmt.EastAsianTextAdjustment()
            assert adj.len(u'¡¡ab') == 6

        data = [[u'あ', 'b', 'c'], ['dd', u'ええ', 'ff'],
                ['ggg', u'¡¡ab', u'いいい']]
        expected = u'あ  dd    ggg \nb   ええ  ¡¡ab\nc   ff    いいい'
        adjoined = adj.adjoin(2, *data)
        assert adjoined == expected
Exemple #35
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    def test_sparse_max_row(self):
        s = pd.Series([1, np.nan, np.nan, 3, np.nan]).to_sparse()
        result = repr(s)
        dfm = self.dtype_format_for_platform
        exp = ("0    1.0\n1    NaN\n2    NaN\n3    3.0\n"
               "4    NaN\ndtype: float64\nBlockIndex\n"
               "Block locations: array([0, 3]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dfm))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            # GH 10560
            result = repr(s)
            exp = ("0    1.0\n    ... \n4    NaN\n"
                   "Length: 5, dtype: float64\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dfm))
            self.assertEqual(result, exp)
Exemple #36
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    def test_sparse_max_row(self):
        s = pd.Series([1, np.nan, np.nan, 3, np.nan]).to_sparse()
        result = repr(s)
        dfm = self.dtype_format_for_platform
        exp = ("0    1.0\n1    NaN\n2    NaN\n3    3.0\n"
               "4    NaN\ndtype: float64\nBlockIndex\n"
               "Block locations: array([0, 3]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dfm))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            # GH 10560
            result = repr(s)
            exp = ("0    1.0\n    ... \n4    NaN\n"
                   "dtype: float64\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dfm))
            self.assertEqual(result, exp)
Exemple #37
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    def test_sparse_int(self):
        # GH 13110
        s = pd.SparseSeries([0, 1, 0, 0, 1, 0], fill_value=False)

        result = repr(s)
        dtype = '' if use_32bit_repr else ', dtype=int32'
        exp = ("0    0\n1    1\n2    0\n3    0\n4    1\n"
               "5    0\ndtype: int64\nBlockIndex\n"
               "Block locations: array([1, 4]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dtype))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            result = repr(s)
            exp = ("0    0\n    ..\n5    0\n"
                   "dtype: int64\nBlockIndex\n"
                   "Block locations: array([1, 4]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dtype))
            self.assertEqual(result, exp)
Exemple #38
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    def test_sparse_int(self):
        # GH 13110
        s = pd.SparseSeries([0, 1, 0, 0, 1, 0], fill_value=False)

        result = repr(s)
        dtype = '' if use_32bit_repr else ', dtype=int32'
        exp = ("0    0\n1    1\n2    0\n3    0\n4    1\n"
               "5    0\ndtype: int64\nBlockIndex\n"
               "Block locations: array([1, 4]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dtype))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            result = repr(s)
            exp = ("0    0\n    ..\n5    0\n"
                   "dtype: int64\nBlockIndex\n"
                   "Block locations: array([1, 4]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dtype))
            self.assertEqual(result, exp)
Exemple #39
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    def test_sparse_bool(self):
        # GH 13110
        s = pd.SparseSeries([True, False, False, True, False, False],
                            fill_value=False)
        result = repr(s)
        dtype = '' if use_32bit_repr else ', dtype=int32'
        exp = ("0     True\n1    False\n2    False\n"
               "3     True\n4    False\n5    False\n"
               "dtype: bool\nBlockIndex\n"
               "Block locations: array([0, 3]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dtype))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            result = repr(s)
            exp = ("0     True\n     ...  \n5    False\n"
                   "Length: 6, dtype: bool\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dtype))
            self.assertEqual(result, exp)
Exemple #40
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    def test_sparse_bool(self):
        # GH 13110
        s = pd.SparseSeries([True, False, False, True, False, False],
                            fill_value=False)
        result = repr(s)
        dtype = '' if use_32bit_repr else ', dtype=int32'
        exp = ("0     True\n1    False\n2    False\n"
               "3     True\n4    False\n5    False\n"
               "dtype: bool\nBlockIndex\n"
               "Block locations: array([0, 3]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dtype))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            result = repr(s)
            exp = ("0     True\n     ...  \n5    False\n"
                   "dtype: bool\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dtype))
            self.assertEqual(result, exp)
Exemple #41
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    def test_transform_mixed_type(self):
        index = MultiIndex.from_arrays([[0, 0, 0, 1, 1, 1], [1, 2, 3, 1, 2, 3]
                                        ])
        df = DataFrame({'d': [1., 1., 1., 2., 2., 2.],
                        'c': np.tile(['a', 'b', 'c'], 2),
                        'v': np.arange(1., 7.)}, index=index)

        def f(group):
            group['g'] = group['d'] * 2
            return group[:1]

        grouped = df.groupby('c')
        result = grouped.apply(f)

        assert result['d'].dtype == np.float64

        # this is by definition a mutating operation!
        with option_context('mode.chained_assignment', None):
            for key, group in grouped:
                res = f(group)
                assert_frame_equal(res, result.loc[key])
Exemple #42
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    def test_sparse_mi_max_row(self):
        idx = pd.MultiIndex.from_tuples([('A', 0), ('A', 1), ('B', 0),
                                         ('C', 0), ('C', 1), ('C', 2)])
        s = pd.Series([1, np.nan, np.nan, 3, np.nan, np.nan],
                      index=idx).to_sparse()
        result = repr(s)
        dfm = self.dtype_format_for_platform
        exp = ("A  0    1.0\n   1    NaN\nB  0    NaN\n"
               "C  0    3.0\n   1    NaN\n   2    NaN\n"
               "dtype: float64\nBlockIndex\n"
               "Block locations: array([0, 3]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dfm))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            # GH 13144
            result = repr(s)
            exp = ("A  0    1.0\n       ... \nC  2    NaN\n"
                   "dtype: float64\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dfm))
            self.assertEqual(result, exp)
Exemple #43
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    def test_sparse_mi_max_row(self):
        idx = pd.MultiIndex.from_tuples([('A', 0), ('A', 1), ('B', 0),
                                         ('C', 0), ('C', 1), ('C', 2)])
        s = pd.Series([1, np.nan, np.nan, 3, np.nan, np.nan],
                      index=idx).to_sparse()
        result = repr(s)
        dfm = self.dtype_format_for_platform
        exp = ("A  0    1.0\n   1    NaN\nB  0    NaN\n"
               "C  0    3.0\n   1    NaN\n   2    NaN\n"
               "dtype: float64\nBlockIndex\n"
               "Block locations: array([0, 3]{0})\n"
               "Block lengths: array([1, 1]{0})".format(dfm))
        self.assertEqual(result, exp)

        with option_context("display.max_rows", 3):
            # GH 13144
            result = repr(s)
            exp = ("A  0    1.0\n       ... \nC  2    NaN\n"
                   "dtype: float64\nBlockIndex\n"
                   "Block locations: array([0, 3]{0})\n"
                   "Block lengths: array([1, 1]{0})".format(dfm))
            self.assertEqual(result, exp)
Exemple #44
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    def test_option_no_warning(self):
        pytest.importorskip("matplotlib.pyplot")
        ctx = cf.option_context("plotting.matplotlib.register_converters",
                                False)
        plt = pytest.importorskip("matplotlib.pyplot")
        s = Series(range(12), index=date_range('2017', periods=12))
        _, ax = plt.subplots()

        converter._WARN = True
        # Test without registering first, no warning
        with ctx:
            with tm.assert_produces_warning(None) as w:
                ax.plot(s.index, s.values)

        assert len(w) == 0

        # Now test with registering
        converter._WARN = True
        register_matplotlib_converters()
        with ctx:
            with tm.assert_produces_warning(None) as w:
                ax.plot(s.index, s.values)

        assert len(w) == 0
Exemple #45
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    def test_option_no_warning(self):
        pytest.importorskip("matplotlib.pyplot")
        ctx = cf.option_context("plotting.matplotlib.register_converters",
                                False)
        plt = pytest.importorskip("matplotlib.pyplot")
        s = Series(range(12), index=date_range('2017', periods=12))
        _, ax = plt.subplots()

        converter._WARN = True
        # Test without registering first, no warning
        with ctx:
            with tm.assert_produces_warning(None) as w:
                ax.plot(s.index, s.values)

        assert len(w) == 0

        # Now test with registering
        converter._WARN = True
        register_matplotlib_converters()
        with ctx:
            with tm.assert_produces_warning(None) as w:
                ax.plot(s.index, s.values)

        assert len(w) == 0
Exemple #46
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 def test_repr_summary(self):
     with cf.option_context('display.max_seq_items', 10):
         r = repr(pd.Index(np.arange(1000)))
         self.assertTrue(len(r) < 200)
         self.assertTrue("..." in r)
Exemple #47
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    def test_string_categorical_index_repr(self):
        # short
        idx = pd.CategoricalIndex(['a', 'bb', 'ccc'])
        if PY3:
            expected = u"""CategoricalIndex(['a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')"""
            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'a', u'bb', u'ccc'], categories=[u'a', u'bb', u'ccc'], ordered=False, dtype='category')"""
            self.assertEqual(unicode(idx), expected)

        # multiple lines
        idx = pd.CategoricalIndex(['a', 'bb', 'ccc'] * 10)
        if PY3:
            expected = u"""CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
                  'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb',
                  'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
                 categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')"""

            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb',
                  u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a',
                  u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc',
                  u'a', u'bb', u'ccc', u'a', u'bb', u'ccc'],
                 categories=[u'a', u'bb', u'ccc'], ordered=False, dtype='category')"""

            self.assertEqual(unicode(idx), expected)

        # truncated
        idx = pd.CategoricalIndex(['a', 'bb', 'ccc'] * 100)
        if PY3:
            expected = u"""CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
                  ...
                  'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
                 categories=['a', 'bb', 'ccc'], ordered=False, dtype='category', length=300)"""

            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb',
                  u'ccc', u'a',
                  ...
                  u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a',
                  u'bb', u'ccc'],
                 categories=[u'a', u'bb', u'ccc'], ordered=False, dtype='category', length=300)"""

            self.assertEqual(unicode(idx), expected)

        # larger categories
        idx = pd.CategoricalIndex(list('abcdefghijklmmo'))
        if PY3:
            expected = u"""CategoricalIndex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l',
                  'm', 'm', 'o'],
                 categories=['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', ...], ordered=False, dtype='category')"""

            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'a', u'b', u'c', u'd', u'e', u'f', u'g', u'h', u'i', u'j',
                  u'k', u'l', u'm', u'm', u'o'],
                 categories=[u'a', u'b', u'c', u'd', u'e', u'f', u'g', u'h', ...], ordered=False, dtype='category')"""

            self.assertEqual(unicode(idx), expected)

        # short
        idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'])
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""
            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう'], categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""
            self.assertEqual(unicode(idx), expected)

        # multiple lines
        idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 10)
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ',
                  'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""

            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい',
                  u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう',
                  u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""

            self.assertEqual(unicode(idx), expected)

        # truncated
        idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 100)
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ',
                  ...
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)"""

            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい',
                  u'ううう', u'あ',
                  ...
                  u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category', length=300)"""

            self.assertEqual(unicode(idx), expected)

        # larger categories
        idx = pd.CategoricalIndex(list(u'あいうえおかきくけこさしすせそ'))
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し',
                  'す', 'せ', 'そ'],
                 categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')"""

            self.assertEqual(repr(idx), expected)
        else:
            expected = u"""CategoricalIndex([u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く', u'け', u'こ',
                  u'さ', u'し', u'す', u'せ', u'そ'],
                 categories=[u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く', ...], ordered=False, dtype='category')"""

            self.assertEqual(unicode(idx), expected)

        # Emable Unicode option -----------------------------------------
        with cf.option_context('display.unicode.east_asian_width', True):

            # short
            idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'])
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""
                self.assertEqual(repr(idx), expected)
            else:
                expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう'], categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""
                self.assertEqual(unicode(idx), expected)

            # multiple lines
            idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 10)
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',
                  'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""

                self.assertEqual(repr(idx), expected)
            else:
                expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""

                self.assertEqual(unicode(idx), expected)

            # truncated
            idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 100)
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ',
                  ...
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',
                  'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)"""

                self.assertEqual(repr(idx), expected)
            else:
                expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ',
                  ...
                  u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい',
                  u'ううう', u'あ', u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category', length=300)"""

                self.assertEqual(unicode(idx), expected)

            # larger categories
            idx = pd.CategoricalIndex(list(u'あいうえおかきくけこさしすせそ'))
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ',
                  'さ', 'し', 'す', 'せ', 'そ'],
                 categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')"""

                self.assertEqual(repr(idx), expected)
            else:
                expected = u"""CategoricalIndex([u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く',
                  u'け', u'こ', u'さ', u'し', u'す', u'せ', u'そ'],
                 categories=[u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く', ...], ordered=False, dtype='category')"""

                self.assertEqual(unicode(idx), expected)
Exemple #48
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    def test_wide_repr_wide_columns(self):
        with option_context('mode.sim_interactive', True):
            df = DataFrame(randn(5, 3), columns=['a' * 90, 'b' * 90, 'c' * 90])
            rep_str = repr(df)

            self.assert_(len(rep_str.splitlines()) == 20)
Exemple #49
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 def test_repr_no_backslash(self):
     with option_context('mode.sim_interactive', True):
         df = DataFrame(np.random.randn(10, 4))
         self.assertTrue('\\' not in repr(df))
Exemple #50
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    def test_to_string_utf8_columns(self):
        n = u"\u05d0".encode('utf-8')

        with option_context('display.max_rows', 1):
            df = pd.DataFrame([1, 2], columns=[n])
            repr(df)
Exemple #51
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 def test_repr_no_backslash(self):
     with option_context('mode.sim_interactive', True):
         df = DataFrame(np.random.randn(10, 4))
         self.assertTrue('\\' not in repr(df))
Exemple #52
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    def test_to_string_utf8_columns(self):
        n = u"\u05d0".encode('utf-8')

        with option_context('display.max_rows', 1):
            df = pd.DataFrame([1, 2], columns=[n])
            repr(df)
Exemple #53
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    def test_wide_repr_wide_columns(self):
        with option_context('mode.sim_interactive', True):
            df = DataFrame(randn(5, 3), columns=['a' * 90, 'b' * 90, 'c' * 90])
            rep_str = repr(df)

            self.assert_(len(rep_str.splitlines()) == 20)
Exemple #54
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    def test_string_categorical_index_repr(self):
        # short
        idx = pd.CategoricalIndex(['a', 'bb', 'ccc'])
        if PY3:
            expected = u"""CategoricalIndex(['a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')"""  # noqa
            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'a', u'bb', u'ccc'], categories=[u'a', u'bb', u'ccc'], ordered=False, dtype='category')"""  # noqa
            assert unicode(idx) == expected

        # multiple lines
        idx = pd.CategoricalIndex(['a', 'bb', 'ccc'] * 10)
        if PY3:
            expected = u"""CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
                  'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb',
                  'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
                 categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')"""  # noqa

            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb',
                  u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a',
                  u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc',
                  u'a', u'bb', u'ccc', u'a', u'bb', u'ccc'],
                 categories=[u'a', u'bb', u'ccc'], ordered=False, dtype='category')"""  # noqa

            assert unicode(idx) == expected

        # truncated
        idx = pd.CategoricalIndex(['a', 'bb', 'ccc'] * 100)
        if PY3:
            expected = u"""CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
                  ...
                  'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
                 categories=['a', 'bb', 'ccc'], ordered=False, dtype='category', length=300)"""  # noqa

            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a', u'bb',
                  u'ccc', u'a',
                  ...
                  u'ccc', u'a', u'bb', u'ccc', u'a', u'bb', u'ccc', u'a',
                  u'bb', u'ccc'],
                 categories=[u'a', u'bb', u'ccc'], ordered=False, dtype='category', length=300)"""  # noqa

            assert unicode(idx) == expected

        # larger categories
        idx = pd.CategoricalIndex(list('abcdefghijklmmo'))
        if PY3:
            expected = u"""CategoricalIndex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l',
                  'm', 'm', 'o'],
                 categories=['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', ...], ordered=False, dtype='category')"""  # noqa

            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'a', u'b', u'c', u'd', u'e', u'f', u'g', u'h', u'i', u'j',
                  u'k', u'l', u'm', u'm', u'o'],
                 categories=[u'a', u'b', u'c', u'd', u'e', u'f', u'g', u'h', ...], ordered=False, dtype='category')"""  # noqa

            assert unicode(idx) == expected

        # short
        idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'])
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""  # noqa
            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう'], categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""  # noqa
            assert unicode(idx) == expected

        # multiple lines
        idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 10)
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ',
                  'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""  # noqa

            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい',
                  u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう',
                  u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""  # noqa

            assert unicode(idx) == expected

        # truncated
        idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 100)
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ',
                  ...
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)"""  # noqa

            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい',
                  u'ううう', u'あ',
                  ...
                  u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category', length=300)"""  # noqa

            assert unicode(idx) == expected

        # larger categories
        idx = pd.CategoricalIndex(list(u'あいうえおかきくけこさしすせそ'))
        if PY3:
            expected = u"""CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し',
                  'す', 'せ', 'そ'],
                 categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')"""  # noqa

            assert repr(idx) == expected
        else:
            expected = u"""CategoricalIndex([u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く', u'け', u'こ',
                  u'さ', u'し', u'す', u'せ', u'そ'],
                 categories=[u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く', ...], ordered=False, dtype='category')"""  # noqa

            assert unicode(idx) == expected

        # Emable Unicode option -----------------------------------------
        with cf.option_context('display.unicode.east_asian_width', True):

            # short
            idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'])
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""  # noqa
                assert repr(idx) == expected
            else:
                expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう'], categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""  # noqa
                assert unicode(idx) == expected

            # multiple lines
            idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 10)
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',
                  'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')"""  # noqa

                assert repr(idx) == expected
            else:
                expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ', u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category')"""  # noqa

                assert unicode(idx) == expected

            # truncated
            idx = pd.CategoricalIndex([u'あ', u'いい', u'ううう'] * 100)
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
                  'ううう', 'あ',
                  ...
                  'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',
                  'あ', 'いい', 'ううう'],
                 categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category', length=300)"""  # noqa

                assert repr(idx) == expected
            else:
                expected = u"""CategoricalIndex([u'あ', u'いい', u'ううう', u'あ', u'いい', u'ううう', u'あ',
                  u'いい', u'ううう', u'あ',
                  ...
                  u'ううう', u'あ', u'いい', u'ううう', u'あ', u'いい',
                  u'ううう', u'あ', u'いい', u'ううう'],
                 categories=[u'あ', u'いい', u'ううう'], ordered=False, dtype='category', length=300)"""  # noqa

                assert unicode(idx) == expected

            # larger categories
            idx = pd.CategoricalIndex(list(u'あいうえおかきくけこさしすせそ'))
            if PY3:
                expected = u"""CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ',
                  'さ', 'し', 'す', 'せ', 'そ'],
                 categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')"""  # noqa

                assert repr(idx) == expected
            else:
                expected = u"""CategoricalIndex([u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く',
                  u'け', u'こ', u'さ', u'し', u'す', u'せ', u'そ'],
                 categories=[u'あ', u'い', u'う', u'え', u'お', u'か', u'き', u'く', ...], ordered=False, dtype='category')"""  # noqa

                assert unicode(idx) == expected
Exemple #55
0
 def test_repr_summary(self):
     with cf.option_context('display.max_seq_items', 10):
         r = repr(pd.Index(np.arange(1000)))
         self.assertTrue(len(r) < 200)
         self.assertTrue("..." in r)