Пример #1
0
class IndexAppend(object):

    goal_time = 0.2

    def setup(self):

        N = 10000
        self.range_idx = RangeIndex(0, 100)
        self.int_idx = self.range_idx.astype(int)
        self.obj_idx = self.int_idx.astype(str)
        self.range_idxs = []
        self.int_idxs = []
        self.object_idxs = []
        for i in range(1, N):
            r_idx = RangeIndex(i * 100, (i + 1) * 100)
            self.range_idxs.append(r_idx)
            i_idx = r_idx.astype(int)
            self.int_idxs.append(i_idx)
            o_idx = i_idx.astype(str)
            self.object_idxs.append(o_idx)

    def time_append_range_list(self):
        self.range_idx.append(self.range_idxs)

    def time_append_int_list(self):
        self.int_idx.append(self.int_idxs)

    def time_append_obj_list(self):
        self.obj_idx.append(self.object_idxs)
Пример #2
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 def test_copy(self):
     i = RangeIndex(5, name='Foo')
     i_copy = i.copy()
     assert i_copy is not i
     assert i_copy.identical(i)
     assert i_copy._range == range(0, 5, 1)
     assert i_copy.name == 'Foo'
Пример #3
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    def test_constructor_range(self):

        self.assertRaises(TypeError, lambda: RangeIndex(range(1, 5, 2)))

        result = RangeIndex.from_range(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        self.assertTrue(result.equals(expected))

        result = RangeIndex.from_range(range(5, 6))
        expected = RangeIndex(5, 6, 1)
        self.assertTrue(result.equals(expected))

        # an invalid range
        result = RangeIndex.from_range(range(5, 1))
        expected = RangeIndex(0, 0, 1)
        self.assertTrue(result.equals(expected))

        result = RangeIndex.from_range(range(5))
        expected = RangeIndex(0, 5, 1)
        self.assertTrue(result.equals(expected))

        result = Index(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        self.assertTrue(result.equals(expected))

        self.assertRaises(TypeError,
                          lambda: Index(range(1, 5, 2), dtype='float64'))
Пример #4
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    def test_constructor_range(self):

        pytest.raises(TypeError, lambda: RangeIndex(range(1, 5, 2)))

        result = RangeIndex.from_range(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        tm.assert_index_equal(result, expected, exact=True)

        result = RangeIndex.from_range(range(5, 6))
        expected = RangeIndex(5, 6, 1)
        tm.assert_index_equal(result, expected, exact=True)

        # an invalid range
        result = RangeIndex.from_range(range(5, 1))
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected, exact=True)

        result = RangeIndex.from_range(range(5))
        expected = RangeIndex(0, 5, 1)
        tm.assert_index_equal(result, expected, exact=True)

        result = Index(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        tm.assert_index_equal(result, expected, exact=True)

        pytest.raises(TypeError,
                      lambda: Index(range(1, 5, 2), dtype='float64'))
Пример #5
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 def test_copy(self):
     i = RangeIndex(5, name='Foo')
     i_copy = i.copy()
     self.assertTrue(i_copy is not i)
     self.assertTrue(i_copy.identical(i))
     self.assertEqual(i_copy._start, 0)
     self.assertEqual(i_copy._stop, 5)
     self.assertEqual(i_copy._step, 1)
     self.assertEqual(i_copy.name, 'Foo')
Пример #6
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    def test_nbytes(self):

        # memory savings vs int index
        i = RangeIndex(0, 1000)
        self.assertTrue(i.nbytes < i.astype(int).nbytes / 10)

        # constant memory usage
        i2 = RangeIndex(0, 10)
        self.assertEqual(i.nbytes, i2.nbytes)
Пример #7
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 def test_copy(self):
     i = RangeIndex(5, name='Foo')
     i_copy = i.copy()
     assert i_copy is not i
     assert i_copy.identical(i)
     assert i_copy._start == 0
     assert i_copy._stop == 5
     assert i_copy._step == 1
     assert i_copy.name == 'Foo'
Пример #8
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    def test_nbytes(self):

        # memory savings vs int index
        i = RangeIndex(0, 1000)
        assert i.nbytes < i.astype(int).nbytes / 10

        # constant memory usage
        i2 = RangeIndex(0, 10)
        assert i.nbytes == i2.nbytes
Пример #9
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    def test_view(self):
        i = RangeIndex(0, name='Foo')
        i_view = i.view()
        assert i_view.name == 'Foo'

        i_view = i.view('i8')
        tm.assert_numpy_array_equal(i.values, i_view)

        i_view = i.view(RangeIndex)
        tm.assert_index_equal(i, i_view)
Пример #10
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    def test_view(self):
        super(TestRangeIndex, self).test_view()

        i = RangeIndex(0, name='Foo')
        i_view = i.view()
        self.assertEqual(i_view.name, 'Foo')

        i_view = i.view('i8')
        tm.assert_numpy_array_equal(i.values, i_view)

        i_view = i.view(RangeIndex)
        tm.assert_index_equal(i, i_view)
Пример #11
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    def test_view(self, indices):
        super(TestRangeIndex, self).test_view(indices)

        i = RangeIndex(0, name='Foo')
        i_view = i.view()
        assert i_view.name == 'Foo'

        i_view = i.view('i8')
        tm.assert_numpy_array_equal(i.values, i_view)

        i_view = i.view(RangeIndex)
        tm.assert_index_equal(i, i_view)
Пример #12
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    def test_constructor_corner(self):
        arr = np.array([1, 2, 3, 4], dtype=object)
        index = RangeIndex(1, 5)
        self.assertEqual(index.values.dtype, np.int64)
        self.assertTrue(index.equals(arr))

        # non-int raise Exception
        self.assertRaises(TypeError, RangeIndex, '1', '10', '1')
        self.assertRaises(TypeError, RangeIndex, 1.1, 10.2, 1.3)

        # invalid passed type
        self.assertRaises(TypeError, lambda: RangeIndex(1, 5, dtype='float64'))
Пример #13
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    def test_constructor_same(self):

        # pass thru w and w/o copy
        index = RangeIndex(1, 5, 2)
        result = RangeIndex(index, copy=False)
        assert result.identical(index)

        result = RangeIndex(index, copy=True)
        tm.assert_index_equal(result, index, exact=True)

        result = RangeIndex(index)
        tm.assert_index_equal(result, index, exact=True)

        pytest.raises(TypeError,
                      lambda: RangeIndex(index, dtype='float64'))
Пример #14
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    def test_delete(self):

        idx = RangeIndex(5, name='Foo')
        expected = idx[1:].astype(int)
        result = idx.delete(0)
        self.assertTrue(result.equals(expected))
        self.assertEqual(result.name, expected.name)

        expected = idx[:-1].astype(int)
        result = idx.delete(-1)
        self.assertTrue(result.equals(expected))
        self.assertEqual(result.name, expected.name)

        with tm.assertRaises((IndexError, ValueError)):
            # either depending on numpy version
            result = idx.delete(len(idx))
Пример #15
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    def setup(self):

        N = 10000
        self.range_idx = RangeIndex(0, 100)
        self.int_idx = self.range_idx.astype(int)
        self.obj_idx = self.int_idx.astype(str)
        self.range_idxs = []
        self.int_idxs = []
        self.object_idxs = []
        for i in range(1, N):
            r_idx = RangeIndex(i * 100, (i + 1) * 100)
            self.range_idxs.append(r_idx)
            i_idx = r_idx.astype(int)
            self.int_idxs.append(i_idx)
            o_idx = i_idx.astype(str)
            self.object_idxs.append(o_idx)
Пример #16
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    def test_delete(self):

        idx = RangeIndex(5, name='Foo')
        expected = idx[1:].astype(int)
        result = idx.delete(0)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

        expected = idx[:-1].astype(int)
        result = idx.delete(-1)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

        with pytest.raises((IndexError, ValueError)):
            # either depending on numpy version
            result = idx.delete(len(idx))
Пример #17
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    def test_constructor_name(self):
        # GH12288
        orig = RangeIndex(10)
        orig.name = 'original'

        copy = RangeIndex(orig)
        copy.name = 'copy'

        self.assertTrue(orig.name, 'original')
        self.assertTrue(copy.name, 'copy')

        new = Index(copy)
        self.assertTrue(new.name, 'copy')

        new.name = 'new'
        self.assertTrue(orig.name, 'original')
        self.assertTrue(new.name, 'copy')
        self.assertTrue(new.name, 'new')
Пример #18
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    def test_constructor_name(self):
        # GH12288
        orig = RangeIndex(10)
        orig.name = 'original'

        copy = RangeIndex(orig)
        copy.name = 'copy'

        assert orig.name == 'original'
        assert copy.name == 'copy'

        new = Index(copy)
        assert new.name == 'copy'

        new.name = 'new'
        assert orig.name == 'original'
        assert copy.name == 'copy'
        assert new.name == 'new'
Пример #19
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def to_parquet(df, path, engine='auto', compression='snappy', **kwargs):
    """
    Write a DataFrame to the parquet format.

    Parameters
    ----------
    df : DataFrame
    path : string
        File path
    engine : {'auto', 'pyarrow', 'fastparquet'}, default 'auto'
        Parquet reader library to use. If 'auto', then the option
        'io.parquet.engine' is used. If 'auto', then the first
        library to be installed is used.
    compression : str, optional, default 'snappy'
        compression method, includes {'gzip', 'snappy', 'brotli'}
    kwargs
        Additional keyword arguments passed to the engine
    """

    impl = get_engine(engine)

    if not isinstance(df, DataFrame):
        raise ValueError("to_parquet only support IO with DataFrames")

    valid_types = {'string', 'unicode'}

    # validate index
    # --------------

    # validate that we have only a default index
    # raise on anything else as we don't serialize the index

    if not isinstance(df.index, Int64Index):
        raise ValueError("parquet does not support serializing {} "
                         "for the index; you can .reset_index()"
                         "to make the index into column(s)".format(
                             type(df.index)))

    if not df.index.equals(RangeIndex.from_range(range(len(df)))):
        raise ValueError("parquet does not support serializing a "
                         "non-default index for the index; you "
                         "can .reset_index() to make the index "
                         "into column(s)")

    if df.index.name is not None:
        raise ValueError("parquet does not serialize index meta-data on a "
                         "default index")

    # validate columns
    # ----------------

    # must have value column names (strings only)
    if df.columns.inferred_type not in valid_types:
        raise ValueError("parquet must have string column names")

    return impl.write(df, path, compression=compression, **kwargs)
Пример #20
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class Range:

    def setup(self):
        self.idx_inc = RangeIndex(start=0, stop=10**7, step=3)
        self.idx_dec = RangeIndex(start=10**7, stop=-1, step=-3)

    def time_max(self):
        self.idx_inc.max()

    def time_max_trivial(self):
        self.idx_dec.max()

    def time_min(self):
        self.idx_dec.min()

    def time_min_trivial(self):
        self.idx_inc.min()
Пример #21
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def to_feather(df, path):
    """
    Write a DataFrame to the feather-format

    Parameters
    ----------
    df : DataFrame
    path : string
        File path

    """
    path = _stringify_path(path)
    if not isinstance(df, DataFrame):
        raise ValueError("feather only support IO with DataFrames")

    feather = _try_import()
    valid_types = {'string', 'unicode'}

    # validate index
    # --------------

    # validate that we have only a default index
    # raise on anything else as we don't serialize the index

    if not isinstance(df.index, Int64Index):
        raise ValueError("feather does not support serializing {} "
                         "for the index; you can .reset_index()"
                         "to make the index into column(s)".format(
                             type(df.index)))

    if not df.index.equals(RangeIndex.from_range(range(len(df)))):
        raise ValueError("feather does not support serializing a "
                         "non-default index for the index; you "
                         "can .reset_index() to make the index "
                         "into column(s)")

    if df.index.name is not None:
        raise ValueError("feather does not serialize index meta-data on a "
                         "default index")

    # validate columns
    # ----------------

    # must have value column names (strings only)
    if df.columns.inferred_type not in valid_types:
        raise ValueError("feather must have string column names")

    feather.write_dataframe(df, path)
Пример #22
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    def test_intersection(self):
        # intersect with Int64Index
        other = Index(np.arange(1, 6))
        result = self.index.intersection(other)
        expected = Index(np.sort(np.intersect1d(self.index.values,
                                                other.values)))
        tm.assert_index_equal(result, expected)

        result = other.intersection(self.index)
        expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
                                                           other.values))))
        tm.assert_index_equal(result, expected)

        # intersect with increasing RangeIndex
        other = RangeIndex(1, 6)
        result = self.index.intersection(other)
        expected = Index(np.sort(np.intersect1d(self.index.values,
                                                other.values)))
        tm.assert_index_equal(result, expected)

        # intersect with decreasing RangeIndex
        other = RangeIndex(5, 0, -1)
        result = self.index.intersection(other)
        expected = Index(np.sort(np.intersect1d(self.index.values,
                                                other.values)))
        tm.assert_index_equal(result, expected)

        index = RangeIndex(5)

        # intersect of non-overlapping indices
        other = RangeIndex(5, 10, 1)
        result = index.intersection(other)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        other = RangeIndex(-1, -5, -1)
        result = index.intersection(other)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        # intersection of empty indices
        other = RangeIndex(0, 0, 1)
        result = index.intersection(other)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        result = other.intersection(index)
        tm.assert_index_equal(result, expected)

        # intersection of non-overlapping values based on start value and gcd
        index = RangeIndex(1, 10, 2)
        other = RangeIndex(0, 10, 4)
        result = index.intersection(other)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)
Пример #23
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    def test_max_min(self, start, stop, step):
        # GH17607
        idx = RangeIndex(start, stop, step)
        expected = idx._int64index.max()
        result = idx.max()
        assert result == expected

        expected = idx._int64index.min()
        result = idx.min()
        assert result == expected

        # empty
        idx = RangeIndex(start, stop, -step)
        assert isna(idx.max())
        assert isna(idx.min())
Пример #24
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    def test_constructor_same(self):

        # pass thru w and w/o copy
        index = RangeIndex(1, 5, 2)
        result = RangeIndex(index, copy=False)
        self.assertTrue(result.identical(index))

        result = RangeIndex(index, copy=True)
        self.assertTrue(result.equals(index))

        result = RangeIndex(index)
        self.assertTrue(result.equals(index))

        self.assertRaises(TypeError,
                          lambda: RangeIndex(index, dtype='float64'))
Пример #25
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    def test_max_min_range(self, start, stop, step):
        # GH#17607
        idx = RangeIndex(start, stop, step)
        expected = idx._int64index.max()
        result = idx.max()
        assert result == expected

        # skipna should be irrelevant since RangeIndex should never have NAs
        result2 = idx.max(skipna=False)
        assert result2 == expected

        expected = idx._int64index.min()
        result = idx.min()
        assert result == expected

        # skipna should be irrelevant since RangeIndex should never have NAs
        result2 = idx.min(skipna=False)
        assert result2 == expected

        # empty
        idx = RangeIndex(start, stop, -step)
        assert isna(idx.max())
        assert isna(idx.min())
Пример #26
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def create_data():
    """ create the pickle data """
    data = {
        "A": [0.0, 1.0, 2.0, 3.0, np.nan],
        "B": [0, 1, 0, 1, 0],
        "C": ["foo1", "foo2", "foo3", "foo4", "foo5"],
        "D": date_range("1/1/2009", periods=5),
        "E": [0.0, 1, Timestamp("20100101"), "foo", 2.0],
    }

    scalars = dict(timestamp=Timestamp("20130101"), period=Period("2012", "M"))

    index = dict(
        int=Index(np.arange(10)),
        date=date_range("20130101", periods=10),
        period=period_range("2013-01-01", freq="M", periods=10),
        float=Index(np.arange(10, dtype=np.float64)),
        uint=Index(np.arange(10, dtype=np.uint64)),
        timedelta=timedelta_range("00:00:00", freq="30T", periods=10),
    )

    index["range"] = RangeIndex(10)

    if _loose_version >= LooseVersion("0.21"):
        from pandas import interval_range

        index["interval"] = interval_range(0, periods=10)

    mi = dict(
        reg2=MultiIndex.from_tuples(
            tuple(
                zip(
                    *[
                        ["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"],
                        ["one", "two", "one", "two", "one", "two", "one", "two"],
                    ]
                )
            ),
            names=["first", "second"],
        )
    )

    series = dict(
        float=Series(data["A"]),
        int=Series(data["B"]),
        mixed=Series(data["E"]),
        ts=Series(
            np.arange(10).astype(np.int64), index=date_range("20130101", periods=10)
        ),
        mi=Series(
            np.arange(5).astype(np.float64),
            index=MultiIndex.from_tuples(
                tuple(zip(*[[1, 1, 2, 2, 2], [3, 4, 3, 4, 5]])), names=["one", "two"]
            ),
        ),
        dup=Series(np.arange(5).astype(np.float64), index=["A", "B", "C", "D", "A"]),
        cat=Series(Categorical(["foo", "bar", "baz"])),
        dt=Series(date_range("20130101", periods=5)),
        dt_tz=Series(date_range("20130101", periods=5, tz="US/Eastern")),
        period=Series([Period("2000Q1")] * 5),
    )

    mixed_dup_df = DataFrame(data)
    mixed_dup_df.columns = list("ABCDA")
    frame = dict(
        float=DataFrame({"A": series["float"], "B": series["float"] + 1}),
        int=DataFrame({"A": series["int"], "B": series["int"] + 1}),
        mixed=DataFrame({k: data[k] for k in ["A", "B", "C", "D"]}),
        mi=DataFrame(
            {"A": np.arange(5).astype(np.float64), "B": np.arange(5).astype(np.int64)},
            index=MultiIndex.from_tuples(
                tuple(
                    zip(
                        *[
                            ["bar", "bar", "baz", "baz", "baz"],
                            ["one", "two", "one", "two", "three"],
                        ]
                    )
                ),
                names=["first", "second"],
            ),
        ),
        dup=DataFrame(
            np.arange(15).reshape(5, 3).astype(np.float64), columns=["A", "B", "A"]
        ),
        cat_onecol=DataFrame({"A": Categorical(["foo", "bar"])}),
        cat_and_float=DataFrame(
            {
                "A": Categorical(["foo", "bar", "baz"]),
                "B": np.arange(3).astype(np.int64),
            }
        ),
        mixed_dup=mixed_dup_df,
        dt_mixed_tzs=DataFrame(
            {
                "A": Timestamp("20130102", tz="US/Eastern"),
                "B": Timestamp("20130603", tz="CET"),
            },
            index=range(5),
        ),
        dt_mixed2_tzs=DataFrame(
            {
                "A": Timestamp("20130102", tz="US/Eastern"),
                "B": Timestamp("20130603", tz="CET"),
                "C": Timestamp("20130603", tz="UTC"),
            },
            index=range(5),
        ),
    )

    cat = dict(
        int8=Categorical(list("abcdefg")),
        int16=Categorical(np.arange(1000)),
        int32=Categorical(np.arange(10000)),
    )

    timestamp = dict(
        normal=Timestamp("2011-01-01"),
        nat=NaT,
        tz=Timestamp("2011-01-01", tz="US/Eastern"),
    )

    timestamp["freq"] = Timestamp("2011-01-01", freq="D")
    timestamp["both"] = Timestamp("2011-01-01", tz="Asia/Tokyo", freq="M")

    off = {
        "DateOffset": DateOffset(years=1),
        "DateOffset_h_ns": DateOffset(hour=6, nanoseconds=5824),
        "BusinessDay": BusinessDay(offset=timedelta(seconds=9)),
        "BusinessHour": BusinessHour(normalize=True, n=6, end="15:14"),
        "CustomBusinessDay": CustomBusinessDay(weekmask="Mon Fri"),
        "SemiMonthBegin": SemiMonthBegin(day_of_month=9),
        "SemiMonthEnd": SemiMonthEnd(day_of_month=24),
        "MonthBegin": MonthBegin(1),
        "MonthEnd": MonthEnd(1),
        "QuarterBegin": QuarterBegin(1),
        "QuarterEnd": QuarterEnd(1),
        "Day": Day(1),
        "YearBegin": YearBegin(1),
        "YearEnd": YearEnd(1),
        "Week": Week(1),
        "Week_Tues": Week(2, normalize=False, weekday=1),
        "WeekOfMonth": WeekOfMonth(week=3, weekday=4),
        "LastWeekOfMonth": LastWeekOfMonth(n=1, weekday=3),
        "FY5253": FY5253(n=2, weekday=6, startingMonth=7, variation="last"),
        "Easter": Easter(),
        "Hour": Hour(1),
        "Minute": Minute(1),
    }

    return dict(
        series=series,
        frame=frame,
        index=index,
        scalars=scalars,
        mi=mi,
        sp_series=dict(float=_create_sp_series(), ts=_create_sp_tsseries()),
        sp_frame=dict(float=_create_sp_frame()),
        cat=cat,
        timestamp=timestamp,
        offsets=off,
    )
Пример #27
0
    def test_from_records_sequencelike(self):
        df = DataFrame(
            {
                "A": np.array(np.random.randn(6), dtype=np.float64),
                "A1": np.array(np.random.randn(6), dtype=np.float64),
                "B": np.array(np.arange(6), dtype=np.int64),
                "C": ["foo"] * 6,
                "D": np.array([True, False] * 3, dtype=bool),
                "E": np.array(np.random.randn(6), dtype=np.float32),
                "E1": np.array(np.random.randn(6), dtype=np.float32),
                "F": np.array(np.arange(6), dtype=np.int32),
            }
        )

        # this is actually tricky to create the recordlike arrays and
        # have the dtypes be intact
        blocks = df._to_dict_of_blocks()
        tuples = []
        columns = []
        dtypes = []
        for dtype, b in blocks.items():
            columns.extend(b.columns)
            dtypes.extend([(c, np.dtype(dtype).descr[0][1]) for c in b.columns])
        for i in range(len(df.index)):
            tup = []
            for _, b in blocks.items():
                tup.extend(b.iloc[i].values)
            tuples.append(tuple(tup))

        recarray = np.array(tuples, dtype=dtypes).view(np.recarray)
        recarray2 = df.to_records()
        lists = [list(x) for x in tuples]

        # tuples (lose the dtype info)
        result = DataFrame.from_records(tuples, columns=columns).reindex(
            columns=df.columns
        )

        # created recarray and with to_records recarray (have dtype info)
        result2 = DataFrame.from_records(recarray, columns=columns).reindex(
            columns=df.columns
        )
        result3 = DataFrame.from_records(recarray2, columns=columns).reindex(
            columns=df.columns
        )

        # list of tupels (no dtype info)
        result4 = DataFrame.from_records(lists, columns=columns).reindex(
            columns=df.columns
        )

        tm.assert_frame_equal(result, df, check_dtype=False)
        tm.assert_frame_equal(result2, df)
        tm.assert_frame_equal(result3, df)
        tm.assert_frame_equal(result4, df, check_dtype=False)

        # tuples is in the order of the columns
        result = DataFrame.from_records(tuples)
        tm.assert_index_equal(result.columns, RangeIndex(8))

        # test exclude parameter & we are casting the results here (as we don't
        # have dtype info to recover)
        columns_to_test = [columns.index("C"), columns.index("E1")]

        exclude = list(set(range(8)) - set(columns_to_test))
        result = DataFrame.from_records(tuples, exclude=exclude)
        result.columns = [columns[i] for i in sorted(columns_to_test)]
        tm.assert_series_equal(result["C"], df["C"])
        tm.assert_series_equal(result["E1"], df["E1"].astype("float64"))
def create_data():
    """create the pickle data"""
    data = {
        "A": [0.0, 1.0, 2.0, 3.0, np.nan],
        "B": [0, 1, 0, 1, 0],
        "C": ["foo1", "foo2", "foo3", "foo4", "foo5"],
        "D": date_range("1/1/2009", periods=5),
        "E": [0.0, 1, Timestamp("20100101"), "foo", 2.0],
    }

    scalars = {
        "timestamp": Timestamp("20130101"),
        "period": Period("2012", "M")
    }

    index = {
        "int": Index(np.arange(10)),
        "date": date_range("20130101", periods=10),
        "period": period_range("2013-01-01", freq="M", periods=10),
        "float": Index(np.arange(10, dtype=np.float64)),
        "uint": Index(np.arange(10, dtype=np.uint64)),
        "timedelta": timedelta_range("00:00:00", freq="30T", periods=10),
    }

    index["range"] = RangeIndex(10)

    index["interval"] = interval_range(0, periods=10)

    mi = {
        "reg2":
        MultiIndex.from_tuples(
            tuple(
                zip(*[
                    ["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"],
                    ["one", "two", "one", "two", "one", "two", "one", "two"],
                ])),
            names=["first", "second"],
        )
    }

    series = {
        "float":
        Series(data["A"]),
        "int":
        Series(data["B"]),
        "mixed":
        Series(data["E"]),
        "ts":
        Series(np.arange(10).astype(np.int64),
               index=date_range("20130101", periods=10)),
        "mi":
        Series(
            np.arange(5).astype(np.float64),
            index=MultiIndex.from_tuples(tuple(
                zip(*[[1, 1, 2, 2, 2], [3, 4, 3, 4, 5]])),
                                         names=["one", "two"]),
        ),
        "dup":
        Series(np.arange(5).astype(np.float64),
               index=["A", "B", "C", "D", "A"]),
        "cat":
        Series(Categorical(["foo", "bar", "baz"])),
        "dt":
        Series(date_range("20130101", periods=5)),
        "dt_tz":
        Series(date_range("20130101", periods=5, tz="US/Eastern")),
        "period":
        Series([Period("2000Q1")] * 5),
    }

    mixed_dup_df = DataFrame(data)
    mixed_dup_df.columns = list("ABCDA")
    frame = {
        "float":
        DataFrame({
            "A": series["float"],
            "B": series["float"] + 1
        }),
        "int":
        DataFrame({
            "A": series["int"],
            "B": series["int"] + 1
        }),
        "mixed":
        DataFrame({k: data[k]
                   for k in ["A", "B", "C", "D"]}),
        "mi":
        DataFrame(
            {
                "A": np.arange(5).astype(np.float64),
                "B": np.arange(5).astype(np.int64)
            },
            index=MultiIndex.from_tuples(
                tuple(
                    zip(*[
                        ["bar", "bar", "baz", "baz", "baz"],
                        ["one", "two", "one", "two", "three"],
                    ])),
                names=["first", "second"],
            ),
        ),
        "dup":
        DataFrame(np.arange(15).reshape(5, 3).astype(np.float64),
                  columns=["A", "B", "A"]),
        "cat_onecol":
        DataFrame({"A": Categorical(["foo", "bar"])}),
        "cat_and_float":
        DataFrame({
            "A": Categorical(["foo", "bar", "baz"]),
            "B": np.arange(3).astype(np.int64),
        }),
        "mixed_dup":
        mixed_dup_df,
        "dt_mixed_tzs":
        DataFrame(
            {
                "A": Timestamp("20130102", tz="US/Eastern"),
                "B": Timestamp("20130603", tz="CET"),
            },
            index=range(5),
        ),
        "dt_mixed2_tzs":
        DataFrame(
            {
                "A": Timestamp("20130102", tz="US/Eastern"),
                "B": Timestamp("20130603", tz="CET"),
                "C": Timestamp("20130603", tz="UTC"),
            },
            index=range(5),
        ),
    }

    cat = {
        "int8": Categorical(list("abcdefg")),
        "int16": Categorical(np.arange(1000)),
        "int32": Categorical(np.arange(10000)),
    }

    timestamp = {
        "normal": Timestamp("2011-01-01"),
        "nat": NaT,
        "tz": Timestamp("2011-01-01", tz="US/Eastern"),
    }

    timestamp["freq"] = Timestamp("2011-01-01", freq="D")
    timestamp["both"] = Timestamp("2011-01-01", tz="Asia/Tokyo", freq="M")

    off = {
        "DateOffset": DateOffset(years=1),
        "DateOffset_h_ns": DateOffset(hour=6, nanoseconds=5824),
        "BusinessDay": BusinessDay(offset=timedelta(seconds=9)),
        "BusinessHour": BusinessHour(normalize=True, n=6, end="15:14"),
        "CustomBusinessDay": CustomBusinessDay(weekmask="Mon Fri"),
        "SemiMonthBegin": SemiMonthBegin(day_of_month=9),
        "SemiMonthEnd": SemiMonthEnd(day_of_month=24),
        "MonthBegin": MonthBegin(1),
        "MonthEnd": MonthEnd(1),
        "QuarterBegin": QuarterBegin(1),
        "QuarterEnd": QuarterEnd(1),
        "Day": Day(1),
        "YearBegin": YearBegin(1),
        "YearEnd": YearEnd(1),
        "Week": Week(1),
        "Week_Tues": Week(2, normalize=False, weekday=1),
        "WeekOfMonth": WeekOfMonth(week=3, weekday=4),
        "LastWeekOfMonth": LastWeekOfMonth(n=1, weekday=3),
        "FY5253": FY5253(n=2, weekday=6, startingMonth=7, variation="last"),
        "Easter": Easter(),
        "Hour": Hour(1),
        "Minute": Minute(1),
    }

    return {
        "series": series,
        "frame": frame,
        "index": index,
        "scalars": scalars,
        "mi": mi,
        "sp_series": {
            "float": _create_sp_series(),
            "ts": _create_sp_tsseries()
        },
        "sp_frame": {
            "float": _create_sp_frame()
        },
        "cat": cat,
        "timestamp": timestamp,
        "offsets": off,
    }
Пример #29
0
    def test_intersection(self, sort):
        # intersect with Int64Index
        other = Index(np.arange(1, 6))
        result = self.index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(self.index.values,
                                                other.values)))
        tm.assert_index_equal(result, expected)

        result = other.intersection(self.index, sort=sort)
        expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
                                                           other.values))))
        tm.assert_index_equal(result, expected)

        # intersect with increasing RangeIndex
        other = RangeIndex(1, 6)
        result = self.index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(self.index.values,
                                                other.values)))
        tm.assert_index_equal(result, expected)

        # intersect with decreasing RangeIndex
        other = RangeIndex(5, 0, -1)
        result = self.index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(self.index.values,
                                                other.values)))
        tm.assert_index_equal(result, expected)

        # reversed (GH 17296)
        result = other.intersection(self.index, sort=sort)
        tm.assert_index_equal(result, expected)

        # GH 17296: intersect two decreasing RangeIndexes
        first = RangeIndex(10, -2, -2)
        other = RangeIndex(5, -4, -1)
        expected = first.astype(int).intersection(other.astype(int), sort=sort)
        result = first.intersection(other, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        # reversed
        result = other.intersection(first, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        index = RangeIndex(5)

        # intersect of non-overlapping indices
        other = RangeIndex(5, 10, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        other = RangeIndex(-1, -5, -1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        # intersection of empty indices
        other = RangeIndex(0, 0, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        result = other.intersection(index, sort=sort)
        tm.assert_index_equal(result, expected)

        # intersection of non-overlapping values based on start value and gcd
        index = RangeIndex(1, 10, 2)
        other = RangeIndex(0, 10, 4)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)
 def test_constructor_invalid_args_wrong_type(self, args):
     msg = f"Wrong type {type(args)} for value {args}"
     with pytest.raises(TypeError, match=msg):
         RangeIndex(args)
Пример #31
0
    def test_numeric_compat2(self):
        # validate that we are handling the RangeIndex overrides to numeric ops
        # and returning RangeIndex where possible

        idx = RangeIndex(0, 10, 2)

        result = idx * 2
        expected = RangeIndex(0, 20, 4)
        tm.assert_index_equal(result, expected, exact=True)

        result = idx + 2
        expected = RangeIndex(2, 12, 2)
        tm.assert_index_equal(result, expected, exact=True)

        result = idx - 2
        expected = RangeIndex(-2, 8, 2)
        tm.assert_index_equal(result, expected, exact=True)

        result = idx / 2
        expected = RangeIndex(0, 5, 1).astype("float64")
        tm.assert_index_equal(result, expected, exact=True)

        result = idx / 4
        expected = RangeIndex(0, 10, 2) / 4
        tm.assert_index_equal(result, expected, exact=True)

        result = idx // 1
        expected = idx
        tm.assert_index_equal(result, expected, exact=True)

        # __mul__
        result = idx * idx
        expected = Index(idx.values * idx.values)
        tm.assert_index_equal(result, expected, exact=True)

        # __pow__
        idx = RangeIndex(0, 1000, 2)
        result = idx ** 2
        expected = idx._int64index ** 2
        tm.assert_index_equal(Index(result.values), expected, exact=True)

        # __floordiv__
        cases_exact = [
            (RangeIndex(0, 1000, 2), 2, RangeIndex(0, 500, 1)),
            (RangeIndex(-99, -201, -3), -3, RangeIndex(33, 67, 1)),
            (RangeIndex(0, 1000, 1), 2, RangeIndex(0, 1000, 1)._int64index // 2),
            (
                RangeIndex(0, 100, 1),
                2.0,
                RangeIndex(0, 100, 1)._int64index // 2.0,
            ),
            (RangeIndex(0), 50, RangeIndex(0)),
            (RangeIndex(2, 4, 2), 3, RangeIndex(0, 1, 1)),
            (RangeIndex(-5, -10, -6), 4, RangeIndex(-2, -1, 1)),
            (RangeIndex(-100, -200, 3), 2, RangeIndex(0)),
        ]
        for idx, div, expected in cases_exact:
            tm.assert_index_equal(idx // div, expected, exact=True)
Пример #32
0
def makeRangeIndex(k=10, name=None, **kwargs):
    return RangeIndex(0, k, 1, name=name, **kwargs)
Пример #33
0
def ichimoku(high, low, close, tenkan=None, kijun=None, senkou=None, offset=None, **kwargs):
    """Indicator: Ichimoku Kinkō Hyō (Ichimoku)"""
    high = verify_series(high)
    low = verify_series(low)
    close = verify_series(close)
    tenkan = int(tenkan) if tenkan and tenkan > 0 else 9
    kijun = int(kijun) if kijun and kijun > 0 else 26
    senkou = int(senkou) if senkou and senkou > 0 else 52
    offset = get_offset(offset)

    # Calculate Result
    tenkan_sen = midprice(high=high, low=low, length=tenkan)
    kijun_sen = midprice(high=high, low=low, length=kijun)
    span_a = 0.5 * (tenkan_sen + kijun_sen)
    span_b = midprice(high=high, low=low, length=senkou)

    # Copy Span A and B values before their shift
    _span_a = span_a[-kijun:].copy()
    _span_b = span_b[-kijun:].copy()

    span_a = span_a.shift(kijun)
    span_b = span_b.shift(kijun)
    chikou_span = close.shift(-kijun)

    # Offset
    if offset != 0:
        tenkan_sen = tenkan_sen.shift(offset)
        kijun_sen = kijun_sen.shift(offset)
        span_a = span_a.shift(offset)
        span_b = span_b.shift(offset)
        chikou_span = chikou_span.shift(offset)

    # Handle fills
    if 'fillna' in kwargs:
        span_a.fillna(kwargs['fillna'], inplace=True)
        span_b.fillna(kwargs['fillna'], inplace=True)
        chikou_span.fillna(kwargs['fillna'], inplace=True)
    if 'fill_method' in kwargs:
        span_a.fillna(method=kwargs['fill_method'], inplace=True)
        span_b.fillna(method=kwargs['fill_method'], inplace=True)
        chikou_span.fillna(method=kwargs['fill_method'], inplace=True)

    # Name and Categorize it
    span_a.name = f"ISA_{tenkan}"
    span_b.name = f"ISB_{kijun}"
    tenkan_sen.name = f"ITS_{tenkan}"
    kijun_sen.name = f"IKS_{kijun}"
    chikou_span.name = f"ICS_{kijun}"

    chikou_span.category = kijun_sen.category = tenkan_sen.category = 'trend'
    span_b.category = span_a.category = chikou_span

    # Prepare Ichimoku DataFrame
    data = {span_a.name: span_a, span_b.name: span_b, tenkan_sen.name: tenkan_sen, kijun_sen.name: kijun_sen, chikou_span.name: chikou_span}
    ichimokudf = DataFrame(data)
    ichimokudf.name = f"ICHIMOKU_{tenkan}_{kijun}_{senkou}"
    ichimokudf.category = 'overlap'

    # Prepare Span DataFrame
    last = close.index[-1]
    if close.index.dtype == 'int64':
        ext_index = RangeIndex(start=last + 1, stop=last + kijun + 1)
        spandf = DataFrame(index=ext_index, columns=[span_a.name, span_b.name])
        _span_a.index = _span_b.index = ext_index
    else:
        df_freq = close.index.value_counts().mode()[0]
        tdelta = Timedelta(df_freq, unit='d')
        new_dt = date_range(start=last + tdelta, periods=kijun, freq='B')
        spandf = DataFrame(index=new_dt, columns=[span_a.name, span_b.name])
        _span_a.index = _span_b.index = new_dt

    spandf[span_a.name] = _span_a
    spandf[span_b.name] = _span_b
    spandf.name = f"ICHISPAN_{tenkan}_{kijun}"
    spandf.category = 'overlap'

    return ichimokudf, spandf
Пример #34
0
    def test_slice_integer(self):

        # same as above, but for Integer based indexes
        # these coerce to a like integer
        # oob indicates if we are out of bounds
        # of positional indexing
        for index, oob in [
            (Int64Index(range(5)), False),
            (RangeIndex(5), False),
            (Int64Index(range(5)) + 10, True),
        ]:

            # s is an in-range index
            s = Series(range(5), index=index)

            # getitem
            for l in [slice(3.0, 4), slice(3, 4.0), slice(3.0, 4.0)]:

                for idxr in [lambda x: x.loc]:

                    result = idxr(s)[l]

                    # these are all label indexing
                    # except getitem which is positional
                    # empty
                    if oob:
                        indexer = slice(0, 0)
                    else:
                        indexer = slice(3, 5)
                    self.check(result, s, indexer, False)

                # positional indexing
                msg = (
                    "cannot do slice indexing "
                    fr"on {type(index).__name__} with these indexers \[(3|4)\.0\] of "
                    "type float"
                )
                with pytest.raises(TypeError, match=msg):
                    s[l]

            # getitem out-of-bounds
            for l in [slice(-6, 6), slice(-6.0, 6.0)]:

                for idxr in [lambda x: x.loc]:
                    result = idxr(s)[l]

                    # these are all label indexing
                    # except getitem which is positional
                    # empty
                    if oob:
                        indexer = slice(0, 0)
                    else:
                        indexer = slice(-6, 6)
                    self.check(result, s, indexer, False)

            # positional indexing
            msg = (
                "cannot do slice indexing "
                fr"on {type(index).__name__} with these indexers \[-6\.0\] of "
                "type float"
            )
            with pytest.raises(TypeError, match=msg):
                s[slice(-6.0, 6.0)]

            # getitem odd floats
            for l, res1 in [
                (slice(2.5, 4), slice(3, 5)),
                (slice(2, 3.5), slice(2, 4)),
                (slice(2.5, 3.5), slice(3, 4)),
            ]:

                for idxr in [lambda x: x.loc]:

                    result = idxr(s)[l]
                    if oob:
                        res = slice(0, 0)
                    else:
                        res = res1

                    self.check(result, s, res, False)

                # positional indexing
                msg = (
                    "cannot do slice indexing "
                    fr"on {type(index).__name__} with these indexers \[(2|3)\.5\] of "
                    "type float"
                )
                with pytest.raises(TypeError, match=msg):
                    s[l]

            # setitem
            for l in [slice(3.0, 4), slice(3, 4.0), slice(3.0, 4.0)]:

                for idxr in [lambda x: x.loc]:
                    sc = s.copy()
                    idxr(sc)[l] = 0
                    result = idxr(sc)[l].values.ravel()
                    assert (result == 0).all()

                # positional indexing
                msg = (
                    "cannot do slice indexing "
                    fr"on {type(index).__name__} with these indexers \[(3|4)\.0\] of "
                    "type float"
                )
                with pytest.raises(TypeError, match=msg):
                    s[l] = 0
Пример #35
0
 def test_slice_keep_name(self):
     idx = RangeIndex(1, 2, name="asdf")
     assert idx.name == idx[1:].name
Пример #36
0
 def test_take_preserve_name(self):
     index = RangeIndex(1, 5, name="foo")
     taken = index.take([3, 0, 1])
     assert index.name == taken.name
Пример #37
0
 def create_index(self):
     return RangeIndex(start=0, stop=20, step=2)
Пример #38
0
 def test_get_indexer_pad(self):
     target = RangeIndex(10)
     indexer = self.index.get_indexer(target, method='pad')
     expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
     tm.assert_numpy_array_equal(indexer, expected)
Пример #39
0
 def test_get_indexer_decreasing(self, stop):
     # GH 28678
     index = RangeIndex(7, stop, -3)
     result = index.get_indexer(range(9))
     expected = np.array([-1, 2, -1, -1, 1, -1, -1, 0, -1], dtype=np.intp)
     tm.assert_numpy_array_equal(result, expected)
Пример #40
0
 def setup(self):
     self.idx_inc = RangeIndex(start=0, stop=10**7, step=3)
     self.idx_dec = RangeIndex(start=10**7, stop=-1, step=-3)
Пример #41
0
 def setup(self):
     self.idx_inc = RangeIndex(start=0, stop=10**7, step=3)
     self.idx_dec = RangeIndex(start=10**7, stop=-1, step=-3)
Пример #42
0
class TestRangeIndex(Numeric):
    _holder = RangeIndex
    _compat_props = ['shape', 'ndim', 'size']

    def setup_method(self, method):
        self.indices = dict(index=RangeIndex(0, 20, 2, name='foo'),
                            index_dec=RangeIndex(18, -1, -2, name='bar'))
        self.setup_indices()

    def create_index(self):
        return RangeIndex(5)

    def test_can_hold_identifiers(self):
        idx = self.create_index()
        key = idx[0]
        assert idx._can_hold_identifiers_and_holds_name(key) is False

    def test_too_many_names(self):
        with pytest.raises(ValueError, match="^Length"):
            self.index.names = ["roger", "harold"]

    @pytest.mark.parametrize('name', [None, 'foo'])
    @pytest.mark.parametrize('args, kwargs, start, stop, step',
                             [((5, ), dict(), 0, 5, 1),
                              ((1, 5), dict(), 1, 5, 1),
                              ((1, 5, 2), dict(), 1, 5, 2),
                              ((0, ), dict(), 0, 0, 1),
                              ((0, 0), dict(), 0, 0, 1),
                              (tuple(), dict(start=0), 0, 0, 1),
                              (tuple(), dict(stop=0), 0, 0, 1)])
    def test_constructor(self, args, kwargs, start, stop, step, name):
        result = RangeIndex(*args, name=name, **kwargs)
        expected = Index(np.arange(start, stop, step, dtype=np.int64),
                         name=name)
        assert isinstance(result, RangeIndex)
        assert result._start == start
        assert result._stop == stop
        assert result._step == step
        assert result.name is name
        tm.assert_index_equal(result, expected)

    def test_constructor_invalid_args(self):
        msg = "RangeIndex\\(\\.\\.\\.\\) must be called with integers"
        with pytest.raises(TypeError, match=msg):
            RangeIndex()

        with pytest.raises(TypeError, match=msg):
            RangeIndex(name='Foo')

        # invalid args
        for i in [
                Index(['a', 'b']),
                Series(['a', 'b']),
                np.array(['a', 'b']), [], 'foo',
                datetime(2000, 1, 1, 0, 0),
                np.arange(0, 10),
                np.array([1]), [1]
        ]:
            with pytest.raises(TypeError):
                RangeIndex(i)

        # we don't allow on a bare Index
        msg = (r'Index\(\.\.\.\) must be called with a collection of some '
               r'kind, 0 was passed')
        with pytest.raises(TypeError, match=msg):
            Index(0, 1000)

    def test_constructor_same(self):

        # pass thru w and w/o copy
        index = RangeIndex(1, 5, 2)
        result = RangeIndex(index, copy=False)
        assert result.identical(index)

        result = RangeIndex(index, copy=True)
        tm.assert_index_equal(result, index, exact=True)

        result = RangeIndex(index)
        tm.assert_index_equal(result, index, exact=True)

        with pytest.raises(TypeError):
            RangeIndex(index, dtype='float64')

    def test_constructor_range(self):

        with pytest.raises(TypeError):
            RangeIndex(range(1, 5, 2))

        result = RangeIndex.from_range(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        tm.assert_index_equal(result, expected, exact=True)

        result = RangeIndex.from_range(range(5, 6))
        expected = RangeIndex(5, 6, 1)
        tm.assert_index_equal(result, expected, exact=True)

        # an invalid range
        result = RangeIndex.from_range(range(5, 1))
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected, exact=True)

        result = RangeIndex.from_range(range(5))
        expected = RangeIndex(0, 5, 1)
        tm.assert_index_equal(result, expected, exact=True)

        result = Index(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        tm.assert_index_equal(result, expected, exact=True)

        with pytest.raises(TypeError):
            Index(range(1, 5, 2), dtype='float64')

    def test_constructor_name(self):
        # GH12288
        orig = RangeIndex(10)
        orig.name = 'original'

        copy = RangeIndex(orig)
        copy.name = 'copy'

        assert orig.name == 'original'
        assert copy.name == 'copy'

        new = Index(copy)
        assert new.name == 'copy'

        new.name = 'new'
        assert orig.name == 'original'
        assert copy.name == 'copy'
        assert new.name == 'new'

    def test_constructor_corner(self):
        arr = np.array([1, 2, 3, 4], dtype=object)
        index = RangeIndex(1, 5)
        assert index.values.dtype == np.int64
        tm.assert_index_equal(index, Index(arr))

        # non-int raise Exception
        with pytest.raises(TypeError):
            RangeIndex('1', '10', '1')
        with pytest.raises(TypeError):
            RangeIndex(1.1, 10.2, 1.3)

        # invalid passed type
        with pytest.raises(TypeError):
            RangeIndex(1, 5, dtype='float64')

    @pytest.mark.parametrize('index, start, stop, step',
                             [(RangeIndex(5), 0, 5, 1),
                              (RangeIndex(0, 5), 0, 5, 1),
                              (RangeIndex(5, step=2), 0, 5, 2),
                              (RangeIndex(1, 5, 2), 1, 5, 2)])
    def test_start_stop_step_attrs(self, index, start, stop, step):
        # GH 25710
        assert index.start == start
        assert index.stop == stop
        assert index.step == step

    def test_copy(self):
        i = RangeIndex(5, name='Foo')
        i_copy = i.copy()
        assert i_copy is not i
        assert i_copy.identical(i)
        assert i_copy._start == 0
        assert i_copy._stop == 5
        assert i_copy._step == 1
        assert i_copy.name == 'Foo'

    def test_repr(self):
        i = RangeIndex(5, name='Foo')
        result = repr(i)
        expected = "RangeIndex(start=0, stop=5, step=1, name='Foo')"
        assert result == expected

        result = eval(result)
        tm.assert_index_equal(result, i, exact=True)

        i = RangeIndex(5, 0, -1)
        result = repr(i)
        expected = "RangeIndex(start=5, stop=0, step=-1)"
        assert result == expected

        result = eval(result)
        tm.assert_index_equal(result, i, exact=True)

    def test_insert(self):

        idx = RangeIndex(5, name='Foo')
        result = idx[1:4]

        # test 0th element
        tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]))

        # GH 18295 (test missing)
        expected = Float64Index([0, np.nan, 1, 2, 3, 4])
        for na in (np.nan, pd.NaT, None):
            result = RangeIndex(5).insert(1, na)
            tm.assert_index_equal(result, expected)

    def test_delete(self):

        idx = RangeIndex(5, name='Foo')
        expected = idx[1:].astype(int)
        result = idx.delete(0)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

        expected = idx[:-1].astype(int)
        result = idx.delete(-1)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

        with pytest.raises((IndexError, ValueError)):
            # either depending on numpy version
            result = idx.delete(len(idx))

    def test_view(self):
        i = RangeIndex(0, name='Foo')
        i_view = i.view()
        assert i_view.name == 'Foo'

        i_view = i.view('i8')
        tm.assert_numpy_array_equal(i.values, i_view)

        i_view = i.view(RangeIndex)
        tm.assert_index_equal(i, i_view)

    def test_dtype(self):
        assert self.index.dtype == np.int64

    def test_is_monotonic(self):
        assert self.index.is_monotonic is True
        assert self.index.is_monotonic_increasing is True
        assert self.index.is_monotonic_decreasing is False
        assert self.index._is_strictly_monotonic_increasing is True
        assert self.index._is_strictly_monotonic_decreasing is False

        index = RangeIndex(4, 0, -1)
        assert index.is_monotonic is False
        assert index._is_strictly_monotonic_increasing is False
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_decreasing is True

        index = RangeIndex(1, 2)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is True

        index = RangeIndex(2, 1)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is True

        index = RangeIndex(1, 1)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is True

    def test_equals_range(self):
        equiv_pairs = [(RangeIndex(0, 9, 2), RangeIndex(0, 10, 2)),
                       (RangeIndex(0), RangeIndex(1, -1, 3)),
                       (RangeIndex(1, 2, 3), RangeIndex(1, 3, 4)),
                       (RangeIndex(0, -9, -2), RangeIndex(0, -10, -2))]
        for left, right in equiv_pairs:
            assert left.equals(right)
            assert right.equals(left)

    def test_logical_compat(self):
        idx = self.create_index()
        assert idx.all() == idx.values.all()
        assert idx.any() == idx.values.any()

    def test_identical(self):
        i = Index(self.index.copy())
        assert i.identical(self.index)

        # we don't allow object dtype for RangeIndex
        if isinstance(self.index, RangeIndex):
            return

        same_values_different_type = Index(i, dtype=object)
        assert not i.identical(same_values_different_type)

        i = self.index.copy(dtype=object)
        i = i.rename('foo')
        same_values = Index(i, dtype=object)
        assert same_values.identical(self.index.copy(dtype=object))

        assert not i.identical(self.index)
        assert Index(same_values, name='foo', dtype=object).identical(i)

        assert not self.index.copy(dtype=object).identical(
            self.index.copy(dtype='int64'))

    def test_get_indexer(self):
        target = RangeIndex(10)
        indexer = self.index.get_indexer(target)
        expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

    def test_get_indexer_pad(self):
        target = RangeIndex(10)
        indexer = self.index.get_indexer(target, method='pad')
        expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

    def test_get_indexer_backfill(self):
        target = RangeIndex(10)
        indexer = self.index.get_indexer(target, method='backfill')
        expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

    def test_join_outer(self):
        # join with Int64Index
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = self.index.join(other,
                                          how='outer',
                                          return_indexers=True)
        noidx_res = self.index.join(other, how='outer')
        tm.assert_index_equal(res, noidx_res)

        eres = Int64Index([
            0, 2, 4, 6, 8, 10, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
            25
        ])
        elidx = np.array(
            [0, 1, 2, 3, 4, 5, 6, 7, -1, 8, -1, 9, -1, -1, -1, -1, -1, -1, -1],
            dtype=np.intp)
        eridx = np.array(
            [-1, -1, -1, -1, -1, -1, -1, -1, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0],
            dtype=np.intp)

        assert isinstance(res, Int64Index)
        assert not isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

        # join with RangeIndex
        other = RangeIndex(25, 14, -1)

        res, lidx, ridx = self.index.join(other,
                                          how='outer',
                                          return_indexers=True)
        noidx_res = self.index.join(other, how='outer')
        tm.assert_index_equal(res, noidx_res)

        assert isinstance(res, Int64Index)
        assert not isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_inner(self):
        # Join with non-RangeIndex
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = self.index.join(other,
                                          how='inner',
                                          return_indexers=True)

        # no guarantee of sortedness, so sort for comparison purposes
        ind = res.argsort()
        res = res.take(ind)
        lidx = lidx.take(ind)
        ridx = ridx.take(ind)

        eres = Int64Index([16, 18])
        elidx = np.array([8, 9], dtype=np.intp)
        eridx = np.array([9, 7], dtype=np.intp)

        assert isinstance(res, Int64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

        # Join two RangeIndex
        other = RangeIndex(25, 14, -1)

        res, lidx, ridx = self.index.join(other,
                                          how='inner',
                                          return_indexers=True)

        assert isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_left(self):
        # Join with Int64Index
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = self.index.join(other,
                                          how='left',
                                          return_indexers=True)
        eres = self.index
        eridx = np.array([-1, -1, -1, -1, -1, -1, -1, -1, 9, 7], dtype=np.intp)

        assert isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        assert lidx is None
        tm.assert_numpy_array_equal(ridx, eridx)

        # Join withRangeIndex
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = self.index.join(other,
                                          how='left',
                                          return_indexers=True)

        assert isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        assert lidx is None
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_right(self):
        # Join with Int64Index
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = self.index.join(other,
                                          how='right',
                                          return_indexers=True)
        eres = other
        elidx = np.array([-1, -1, -1, -1, -1, -1, -1, 9, -1, 8, -1],
                         dtype=np.intp)

        assert isinstance(other, Int64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        assert ridx is None

        # Join withRangeIndex
        other = RangeIndex(25, 14, -1)

        res, lidx, ridx = self.index.join(other,
                                          how='right',
                                          return_indexers=True)
        eres = other

        assert isinstance(other, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        assert ridx is None

    def test_join_non_int_index(self):
        other = Index([3, 6, 7, 8, 10], dtype=object)

        outer = self.index.join(other, how='outer')
        outer2 = other.join(self.index, how='outer')
        expected = Index([0, 2, 3, 4, 6, 7, 8, 10, 12, 14, 16, 18])
        tm.assert_index_equal(outer, outer2)
        tm.assert_index_equal(outer, expected)

        inner = self.index.join(other, how='inner')
        inner2 = other.join(self.index, how='inner')
        expected = Index([6, 8, 10])
        tm.assert_index_equal(inner, inner2)
        tm.assert_index_equal(inner, expected)

        left = self.index.join(other, how='left')
        tm.assert_index_equal(left, self.index.astype(object))

        left2 = other.join(self.index, how='left')
        tm.assert_index_equal(left2, other)

        right = self.index.join(other, how='right')
        tm.assert_index_equal(right, other)

        right2 = other.join(self.index, how='right')
        tm.assert_index_equal(right2, self.index.astype(object))

    def test_join_non_unique(self):
        other = Index([4, 4, 3, 3])

        res, lidx, ridx = self.index.join(other, return_indexers=True)

        eres = Int64Index([0, 2, 4, 4, 6, 8, 10, 12, 14, 16, 18])
        elidx = np.array([0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9], dtype=np.intp)
        eridx = np.array([-1, -1, 0, 1, -1, -1, -1, -1, -1, -1, -1],
                         dtype=np.intp)

        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_self(self):
        kinds = 'outer', 'inner', 'left', 'right'
        for kind in kinds:
            joined = self.index.join(self.index, how=kind)
            assert self.index is joined

    @pytest.mark.parametrize("sort", [None, False])
    def test_intersection(self, sort):
        # intersect with Int64Index
        other = Index(np.arange(1, 6))
        result = self.index.intersection(other, sort=sort)
        expected = Index(
            np.sort(np.intersect1d(self.index.values, other.values)))
        tm.assert_index_equal(result, expected)

        result = other.intersection(self.index, sort=sort)
        expected = Index(
            np.sort(np.asarray(np.intersect1d(self.index.values,
                                              other.values))))
        tm.assert_index_equal(result, expected)

        # intersect with increasing RangeIndex
        other = RangeIndex(1, 6)
        result = self.index.intersection(other, sort=sort)
        expected = Index(
            np.sort(np.intersect1d(self.index.values, other.values)))
        tm.assert_index_equal(result, expected)

        # intersect with decreasing RangeIndex
        other = RangeIndex(5, 0, -1)
        result = self.index.intersection(other, sort=sort)
        expected = Index(
            np.sort(np.intersect1d(self.index.values, other.values)))
        tm.assert_index_equal(result, expected)

        # reversed (GH 17296)
        result = other.intersection(self.index, sort=sort)
        tm.assert_index_equal(result, expected)

        # GH 17296: intersect two decreasing RangeIndexes
        first = RangeIndex(10, -2, -2)
        other = RangeIndex(5, -4, -1)
        expected = first.astype(int).intersection(other.astype(int), sort=sort)
        result = first.intersection(other, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        # reversed
        result = other.intersection(first, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        index = RangeIndex(5)

        # intersect of non-overlapping indices
        other = RangeIndex(5, 10, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        other = RangeIndex(-1, -5, -1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        # intersection of empty indices
        other = RangeIndex(0, 0, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        result = other.intersection(index, sort=sort)
        tm.assert_index_equal(result, expected)

        # intersection of non-overlapping values based on start value and gcd
        index = RangeIndex(1, 10, 2)
        other = RangeIndex(0, 10, 4)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

    def test_union_noncomparable(self):
        from datetime import datetime, timedelta
        # corner case, non-Int64Index
        now = datetime.now()
        other = Index([now + timedelta(i) for i in range(4)], dtype=object)
        result = self.index.union(other)
        expected = Index(np.concatenate((self.index, other)))
        tm.assert_index_equal(result, expected)

        result = other.union(self.index)
        expected = Index(np.concatenate((other, self.index)))
        tm.assert_index_equal(result, expected)

    def test_union(self):
        RI = RangeIndex
        I64 = Int64Index
        cases = [(RI(0, 10, 1), RI(0, 10, 1), RI(0, 10, 1)),
                 (RI(0, 10, 1), RI(5, 20, 1), RI(0, 20, 1)),
                 (RI(0, 10, 1), RI(10, 20, 1), RI(0, 20, 1)),
                 (RI(0, -10, -1), RI(0, -10, -1), RI(0, -10, -1)),
                 (RI(0, -10, -1), RI(-10, -20, -1), RI(-19, 1, 1)),
                 (RI(0, 10, 2), RI(1, 10, 2), RI(0, 10, 1)),
                 (RI(0, 11, 2), RI(1, 12, 2), RI(0, 12, 1)),
                 (RI(0, 21, 4), RI(-2, 24, 4), RI(-2, 24, 2)),
                 (RI(0, -20, -2), RI(-1, -21, -2), RI(-19, 1, 1)),
                 (RI(0, 100, 5), RI(0, 100, 20), RI(0, 100, 5)),
                 (RI(0, -100, -5), RI(5, -100, -20), RI(-95, 10, 5)),
                 (RI(0, -11, -1), RI(1, -12, -4), RI(-11, 2, 1)),
                 (RI(0), RI(0), RI(0)), (RI(0, -10, -2), RI(0), RI(0, -10,
                                                                   -2)),
                 (RI(0, 100, 2), RI(100, 150, 200), RI(0, 102, 2)),
                 (RI(0, -100, -2), RI(-100, 50, 102), RI(-100, 4, 2)),
                 (RI(0, -100, -1), RI(0, -50, -3), RI(-99, 1, 1)),
                 (RI(0, 1, 1), RI(5, 6, 10), RI(0, 6, 5)),
                 (RI(0, 10, 5), RI(-5, -6, -20), RI(-5, 10, 5)),
                 (RI(0, 3, 1), RI(4, 5, 1), I64([0, 1, 2, 4])),
                 (RI(0, 10, 1), I64([]), RI(0, 10, 1)),
                 (RI(0), I64([1, 5, 6]), I64([1, 5, 6]))]
        for idx1, idx2, expected in cases:
            res1 = idx1.union(idx2)
            res2 = idx2.union(idx1)
            res3 = idx1._int64index.union(idx2)
            tm.assert_index_equal(res1, expected, exact=True)
            tm.assert_index_equal(res2, expected, exact=True)
            tm.assert_index_equal(res3, expected)

    def test_nbytes(self):

        # memory savings vs int index
        i = RangeIndex(0, 1000)
        assert i.nbytes < i._int64index.nbytes / 10

        # constant memory usage
        i2 = RangeIndex(0, 10)
        assert i.nbytes == i2.nbytes

    def test_cant_or_shouldnt_cast(self):
        # can't
        with pytest.raises(TypeError):
            RangeIndex('foo', 'bar', 'baz')

        # shouldn't
        with pytest.raises(TypeError):
            RangeIndex('0', '1', '2')

    def test_view_Index(self):
        self.index.view(Index)

    def test_prevent_casting(self):
        result = self.index.astype('O')
        assert result.dtype == np.object_

    def test_take_preserve_name(self):
        index = RangeIndex(1, 5, name='foo')
        taken = index.take([3, 0, 1])
        assert index.name == taken.name

    def test_take_fill_value(self):
        # GH 12631
        idx = pd.RangeIndex(1, 4, name='xxx')
        result = idx.take(np.array([1, 0, -1]))
        expected = pd.Int64Index([2, 1, 3], name='xxx')
        tm.assert_index_equal(result, expected)

        # fill_value
        msg = "Unable to fill values because RangeIndex cannot contain NA"
        with pytest.raises(ValueError, match=msg):
            idx.take(np.array([1, 0, -1]), fill_value=True)

        # allow_fill=False
        result = idx.take(np.array([1, 0, -1]),
                          allow_fill=False,
                          fill_value=True)
        expected = pd.Int64Index([2, 1, 3], name='xxx')
        tm.assert_index_equal(result, expected)

        msg = "Unable to fill values because RangeIndex cannot contain NA"
        with pytest.raises(ValueError, match=msg):
            idx.take(np.array([1, 0, -2]), fill_value=True)
        with pytest.raises(ValueError, match=msg):
            idx.take(np.array([1, 0, -5]), fill_value=True)

        with pytest.raises(IndexError):
            idx.take(np.array([1, -5]))

    def test_print_unicode_columns(self):
        df = pd.DataFrame({
            u("\u05d0"): [1, 2, 3],
            "\u05d1": [4, 5, 6],
            "c": [7, 8, 9]
        })
        repr(df.columns)  # should not raise UnicodeDecodeError

    def test_repr_roundtrip(self):
        tm.assert_index_equal(eval(repr(self.index)), self.index)

    def test_slice_keep_name(self):
        idx = RangeIndex(1, 2, name='asdf')
        assert idx.name == idx[1:].name

    def test_explicit_conversions(self):

        # GH 8608
        # add/sub are overridden explicitly for Float/Int Index
        idx = RangeIndex(5)

        # float conversions
        arr = np.arange(5, dtype='int64') * 3.2
        expected = Float64Index(arr)
        fidx = idx * 3.2
        tm.assert_index_equal(fidx, expected)
        fidx = 3.2 * idx
        tm.assert_index_equal(fidx, expected)

        # interops with numpy arrays
        expected = Float64Index(arr)
        a = np.zeros(5, dtype='float64')
        result = fidx - a
        tm.assert_index_equal(result, expected)

        expected = Float64Index(-arr)
        a = np.zeros(5, dtype='float64')
        result = a - fidx
        tm.assert_index_equal(result, expected)

    def test_has_duplicates(self):
        for ind in self.indices:
            if not len(ind):
                continue
            idx = self.indices[ind]
            assert idx.is_unique
            assert not idx.has_duplicates

    def test_extended_gcd(self):
        result = self.index._extended_gcd(6, 10)
        assert result[0] == result[1] * 6 + result[2] * 10
        assert 2 == result[0]

        result = self.index._extended_gcd(10, 6)
        assert 2 == result[1] * 10 + result[2] * 6
        assert 2 == result[0]

    def test_min_fitting_element(self):
        result = RangeIndex(0, 20, 2)._min_fitting_element(1)
        assert 2 == result

        result = RangeIndex(1, 6)._min_fitting_element(1)
        assert 1 == result

        result = RangeIndex(18, -2, -2)._min_fitting_element(1)
        assert 2 == result

        result = RangeIndex(5, 0, -1)._min_fitting_element(1)
        assert 1 == result

        big_num = 500000000000000000000000

        result = RangeIndex(5, big_num * 2, 1)._min_fitting_element(big_num)
        assert big_num == result

    def test_max_fitting_element(self):
        result = RangeIndex(0, 20, 2)._max_fitting_element(17)
        assert 16 == result

        result = RangeIndex(1, 6)._max_fitting_element(4)
        assert 4 == result

        result = RangeIndex(18, -2, -2)._max_fitting_element(17)
        assert 16 == result

        result = RangeIndex(5, 0, -1)._max_fitting_element(4)
        assert 4 == result

        big_num = 500000000000000000000000

        result = RangeIndex(5, big_num * 2, 1)._max_fitting_element(big_num)
        assert big_num == result

    def test_pickle_compat_construction(self):
        # RangeIndex() is a valid constructor
        pass

    def test_slice_specialised(self):

        # scalar indexing
        res = self.index[1]
        expected = 2
        assert res == expected

        res = self.index[-1]
        expected = 18
        assert res == expected

        # slicing
        # slice value completion
        index = self.index[:]
        expected = self.index
        tm.assert_index_equal(index, expected)

        # positive slice values
        index = self.index[7:10:2]
        expected = Index(np.array([14, 18]), name='foo')
        tm.assert_index_equal(index, expected)

        # negative slice values
        index = self.index[-1:-5:-2]
        expected = Index(np.array([18, 14]), name='foo')
        tm.assert_index_equal(index, expected)

        # stop overshoot
        index = self.index[2:100:4]
        expected = Index(np.array([4, 12]), name='foo')
        tm.assert_index_equal(index, expected)

        # reverse
        index = self.index[::-1]
        expected = Index(self.index.values[::-1], name='foo')
        tm.assert_index_equal(index, expected)

        index = self.index[-8::-1]
        expected = Index(np.array([4, 2, 0]), name='foo')
        tm.assert_index_equal(index, expected)

        index = self.index[-40::-1]
        expected = Index(np.array([], dtype=np.int64), name='foo')
        tm.assert_index_equal(index, expected)

        index = self.index[40::-1]
        expected = Index(self.index.values[40::-1], name='foo')
        tm.assert_index_equal(index, expected)

        index = self.index[10::-1]
        expected = Index(self.index.values[::-1], name='foo')
        tm.assert_index_equal(index, expected)

    def test_len_specialised(self):

        # make sure that our len is the same as
        # np.arange calc

        for step in np.arange(1, 6, 1):

            arr = np.arange(0, 5, step)
            i = RangeIndex(0, 5, step)
            assert len(i) == len(arr)

            i = RangeIndex(5, 0, step)
            assert len(i) == 0

        for step in np.arange(-6, -1, 1):

            arr = np.arange(5, 0, step)
            i = RangeIndex(5, 0, step)
            assert len(i) == len(arr)

            i = RangeIndex(0, 5, step)
            assert len(i) == 0

    def test_append(self):
        # GH16212
        RI = RangeIndex
        I64 = Int64Index
        F64 = Float64Index
        OI = Index
        cases = [([RI(1, 12, 5)], RI(1, 12, 5)), ([RI(0, 6, 4)], RI(0, 6, 4)),
                 ([RI(1, 3), RI(3, 7)], RI(1, 7)),
                 ([RI(1, 5, 2), RI(5, 6)], RI(1, 6, 2)),
                 ([RI(1, 3, 2), RI(4, 7, 3)], RI(1, 7, 3)),
                 ([RI(-4, 3, 2), RI(4, 7, 2)], RI(-4, 7, 2)),
                 ([RI(-4, -8), RI(-8, -12)], RI(0, 0)),
                 ([RI(-4, -8), RI(3, -4)], RI(0, 0)),
                 ([RI(-4, -8), RI(3, 5)], RI(3, 5)),
                 ([RI(-4, -2), RI(3, 5)], I64([-4, -3, 3, 4])),
                 ([RI(-2, ), RI(3, 5)], RI(3, 5)),
                 ([RI(2, ), RI(2)], I64([0, 1, 0, 1])),
                 ([RI(2, ), RI(2, 5), RI(5, 8, 4)], RI(0, 6)),
                 ([RI(2, ), RI(3, 5), RI(5, 8, 4)], I64([0, 1, 3, 4, 5])),
                 ([RI(-2, 2), RI(2, 5), RI(5, 8, 4)], RI(-2, 6)),
                 ([RI(3, ), I64([-1, 3, 15])], I64([0, 1, 2, -1, 3, 15])),
                 ([RI(3, ), F64([-1, 3.1, 15.])], F64([0, 1, 2, -1, 3.1,
                                                       15.])),
                 ([RI(3, ), OI(['a', None, 14])], OI([0, 1, 2, 'a', None,
                                                      14])),
                 ([RI(3, 1), OI(['a', None, 14])], OI(['a', None, 14]))]

        for indices, expected in cases:
            result = indices[0].append(indices[1:])
            tm.assert_index_equal(result, expected, exact=True)

            if len(indices) == 2:
                # Append single item rather than list
                result2 = indices[0].append(indices[1])
                tm.assert_index_equal(result2, expected, exact=True)
 def test_constructor_additional_invalid_args(self, args):
     msg = f"Value needs to be a scalar value, was type {type(args).__name__}"
     with pytest.raises(TypeError, match=msg):
         RangeIndex(args)
Пример #44
0
 def setup_method(self, method):
     self.indices = dict(index=RangeIndex(0, 20, 2, name='foo'),
                         index_dec=RangeIndex(18, -1, -2, name='bar'))
     self.setup_indices()
    def test_constructor_range(self):

        result = RangeIndex.from_range(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        tm.assert_index_equal(result, expected, exact=True)

        result = RangeIndex.from_range(range(5, 6))
        expected = RangeIndex(5, 6, 1)
        tm.assert_index_equal(result, expected, exact=True)

        # an invalid range
        result = RangeIndex.from_range(range(5, 1))
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected, exact=True)

        result = RangeIndex.from_range(range(5))
        expected = RangeIndex(0, 5, 1)
        tm.assert_index_equal(result, expected, exact=True)

        result = Index(range(1, 5, 2))
        expected = RangeIndex(1, 5, 2)
        tm.assert_index_equal(result, expected, exact=True)

        msg = (
            r"(RangeIndex.)?from_range\(\) got an unexpected keyword argument( 'copy')?"
        )
        with pytest.raises(TypeError, match=msg):
            RangeIndex.from_range(range(10), copy=True)
Пример #46
0
 def create_index(self):
     return RangeIndex(5)
Пример #47
0
    def _get_index_loc(self, key, base_index=None):
        """
        Get the location of a specific key in an index

        Parameters
        ----------
        key : label
            The key for which to find the location if the underlying index is
            a DateIndex or a location if the underlying index is a RangeIndex
            or an Int64Index.
        base_index : pd.Index, optional
            Optionally the base index to search. If None, the model's index is
            searched.

        Returns
        -------
        loc : int
            The location of the key
        index : pd.Index
            The index including the key; this is a copy of the original index
            unless the index had to be expanded to accommodate `key`.
        index_was_expanded : bool
            Whether or not the index was expanded to accommodate `key`.

        Notes
        -----
        If `key` is past the end of of the given index, and the index is either
        an Int64Index or a date index, this function extends the index up to
        and including key, and then returns the location in the new index.

        """
        if base_index is None:
            base_index = self._index

        index = base_index
        date_index = isinstance(base_index, (PeriodIndex, DatetimeIndex))
        int_index = isinstance(base_index, Int64Index)
        range_index = isinstance(base_index, RangeIndex)
        index_class = type(base_index)
        nobs = len(index)

        # Special handling for RangeIndex
        if range_index and isinstance(key, (int, np.integer)):
            # Negative indices (that lie in the Index)
            if key < 0 and -key <= nobs:
                key = nobs + key
            # Out-of-sample (note that we include key itself in the new index)
            elif key > nobs - 1:
                # See gh5835. Remove the except after pandas 0.25 required.
                try:
                    base_index_start = base_index.start
                    base_index_step = base_index.step
                except AttributeError:
                    base_index_start = base_index._start
                    base_index_step = base_index._step
                stop = base_index_start + (key + 1) * base_index_step
                index = RangeIndex(start=base_index_start,
                                   stop=stop,
                                   step=base_index_step)

        # Special handling for Int64Index
        if (not range_index and int_index and not date_index and
                isinstance(key, (int, np.integer))):
            # Negative indices (that lie in the Index)
            if key < 0 and -key <= nobs:
                key = nobs + key
            # Out-of-sample (note that we include key itself in the new index)
            elif key > base_index[-1]:
                index = Int64Index(np.arange(base_index[0], int(key + 1)))

        # Special handling for date indexes
        if date_index:
            # Use index type to choose creation function
            if index_class is DatetimeIndex:
                index_fn = date_range
            else:
                index_fn = period_range
            # Integer key (i.e. already given a location)
            if isinstance(key, (int, np.integer)):
                # Negative indices (that lie in the Index)
                if key < 0 and -key < nobs:
                    key = index[nobs + key]
                # Out-of-sample (note that we include key itself in the new
                # index)
                elif key > len(base_index) - 1:
                    index = index_fn(start=base_index[0],
                                     periods=int(key + 1),
                                     freq=base_index.freq)
                    key = index[-1]
                else:
                    key = index[key]
            # Other key types (i.e. string date or some datetime-like object)
            else:
                # Covert the key to the appropriate date-like object
                if index_class is PeriodIndex:
                    date_key = Period(key, freq=base_index.freq)
                else:
                    date_key = Timestamp(key)

                # Out-of-sample
                if date_key > base_index[-1]:
                    # First create an index that may not always include `key`
                    index = index_fn(start=base_index[0], end=date_key,
                                     freq=base_index.freq)

                    # Now make sure we include `key`
                    if not index[-1] == date_key:
                        index = index_fn(start=base_index[0],
                                         periods=len(index) + 1,
                                         freq=base_index.freq)

        # Get the location
        if date_index:
            # (note that get_loc will throw a KeyError if key is invalid)
            loc = index.get_loc(key)
        elif int_index or range_index:
            # For Int64Index and RangeIndex, key is assumed to be the location
            # and not an index value (this assumption is required to support
            # RangeIndex)
            try:
                index[key]
            # We want to raise a KeyError in this case, to keep the exception
            # consistent across index types.
            # - Attempting to index with an out-of-bound location (e.g.
            #   index[10] on an index of length 9) will raise an IndexError
            #   (as of Pandas 0.22)
            # - Attemtping to index with a type that cannot be cast to integer
            #   (e.g. a non-numeric string) will raise a ValueError if the
            #   index is RangeIndex (otherwise will raise an IndexError)
            #   (as of Pandas 0.22)
            except (IndexError, ValueError) as e:
                raise KeyError(str(e))
            loc = key
        else:
            loc = index.get_loc(key)

        # Check if we now have a modified index
        index_was_expanded = index is not base_index

        # Return the index through the end of the loc / slice
        if isinstance(loc, slice):
            end = loc.stop
        else:
            end = loc

        return loc, index[:end + 1], index_was_expanded
Пример #48
0
 def test_get_indexer(self):
     index = self.create_index()
     target = RangeIndex(10)
     indexer = index.get_indexer(target)
     expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
     tm.assert_numpy_array_equal(indexer, expected)
Пример #49
0
 def test_take_preserve_name(self):
     index = RangeIndex(1, 5, name='foo')
     taken = index.take([3, 0, 1])
     self.assertEqual(index.name, taken.name)
Пример #50
0
    def test_intersection(self, sort):
        # intersect with Int64Index
        index = RangeIndex(start=0, stop=20, step=2)
        other = Index(np.arange(1, 6))
        result = index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
        tm.assert_index_equal(result, expected)

        result = other.intersection(index, sort=sort)
        expected = Index(
            np.sort(np.asarray(np.intersect1d(index.values, other.values))))
        tm.assert_index_equal(result, expected)

        # intersect with increasing RangeIndex
        other = RangeIndex(1, 6)
        result = index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
        tm.assert_index_equal(result, expected)

        # intersect with decreasing RangeIndex
        other = RangeIndex(5, 0, -1)
        result = index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
        tm.assert_index_equal(result, expected)

        # reversed (GH 17296)
        result = other.intersection(index, sort=sort)
        tm.assert_index_equal(result, expected)

        # GH 17296: intersect two decreasing RangeIndexes
        first = RangeIndex(10, -2, -2)
        other = RangeIndex(5, -4, -1)
        expected = first.astype(int).intersection(other.astype(int), sort=sort)
        result = first.intersection(other, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        # reversed
        result = other.intersection(first, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        index = RangeIndex(5)

        # intersect of non-overlapping indices
        other = RangeIndex(5, 10, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        other = RangeIndex(-1, -5, -1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        # intersection of empty indices
        other = RangeIndex(0, 0, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        result = other.intersection(index, sort=sort)
        tm.assert_index_equal(result, expected)

        # intersection of non-overlapping values based on start value and gcd
        index = RangeIndex(1, 10, 2)
        other = RangeIndex(0, 10, 4)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)
Пример #51
0
    def setup(self):
        idx_large_fast = RangeIndex(100000)
        idx_small_slow = date_range(start="1/1/2012", periods=1)
        self.mi_large_slow = MultiIndex.from_product([idx_large_fast, idx_small_slow])

        self.idx_non_object = RangeIndex(1)
Пример #52
0
def decode(obj):
    """
    Decoder for deserializing numpy data types.
    """

    typ = obj.get('typ')
    if typ is None:
        return obj
    elif typ == 'timestamp':
        freq = obj['freq'] if 'freq' in obj else obj['offset']
        return Timestamp(obj['value'], tz=obj['tz'], freq=freq)
    elif typ == 'nat':
        return NaT
    elif typ == 'period':
        return Period(ordinal=obj['ordinal'], freq=obj['freq'])
    elif typ == 'index':
        dtype = dtype_for(obj['dtype'])
        data = unconvert(obj['data'], dtype, obj.get('compress'))
        return Index(data, dtype=dtype, name=obj['name'])
    elif typ == 'range_index':
        return RangeIndex(obj['start'],
                          obj['stop'],
                          obj['step'],
                          name=obj['name'])
    elif typ == 'multi_index':
        dtype = dtype_for(obj['dtype'])
        data = unconvert(obj['data'], dtype, obj.get('compress'))
        data = [tuple(x) for x in data]
        return MultiIndex.from_tuples(data, names=obj['names'])
    elif typ == 'period_index':
        data = unconvert(obj['data'], np.int64, obj.get('compress'))
        d = dict(name=obj['name'], freq=obj['freq'])
        freq = d.pop('freq', None)
        return PeriodIndex(PeriodArray(data, freq), **d)

    elif typ == 'datetime_index':
        data = unconvert(obj['data'], np.int64, obj.get('compress'))
        d = dict(name=obj['name'], freq=obj['freq'])
        result = DatetimeIndex(data, **d)
        tz = obj['tz']

        # reverse tz conversion
        if tz is not None:
            result = result.tz_localize('UTC').tz_convert(tz)
        return result

    elif typ in ('interval_index', 'interval_array'):
        return globals()[obj['klass']].from_arrays(obj['left'],
                                                   obj['right'],
                                                   obj['closed'],
                                                   name=obj['name'])
    elif typ == 'category':
        from_codes = globals()[obj['klass']].from_codes
        return from_codes(codes=obj['codes'],
                          categories=obj['categories'],
                          ordered=obj['ordered'])

    elif typ == 'interval':
        return Interval(obj['left'], obj['right'], obj['closed'])
    elif typ == 'series':
        dtype = dtype_for(obj['dtype'])
        pd_dtype = pandas_dtype(dtype)

        index = obj['index']
        result = Series(unconvert(obj['data'], dtype, obj['compress']),
                        index=index,
                        dtype=pd_dtype,
                        name=obj['name'])
        return result

    elif typ == 'block_manager':
        axes = obj['axes']

        def create_block(b):
            values = _safe_reshape(
                unconvert(b['values'], dtype_for(b['dtype']), b['compress']),
                b['shape'])

            # locs handles duplicate column names, and should be used instead
            # of items; see GH 9618
            if 'locs' in b:
                placement = b['locs']
            else:
                placement = axes[0].get_indexer(b['items'])

            if is_datetime64tz_dtype(b['dtype']):
                assert isinstance(values, np.ndarray), type(values)
                assert values.dtype == 'M8[ns]', values.dtype
                values = DatetimeArray(values, dtype=b['dtype'])

            return make_block(values=values,
                              klass=getattr(internals, b['klass']),
                              placement=placement,
                              dtype=b['dtype'])

        blocks = [create_block(b) for b in obj['blocks']]
        return globals()[obj['klass']](BlockManager(blocks, axes))
    elif typ == 'datetime':
        return parse(obj['data'])
    elif typ == 'datetime64':
        return np.datetime64(parse(obj['data']))
    elif typ == 'date':
        return parse(obj['data']).date()
    elif typ == 'timedelta':
        return timedelta(*obj['data'])
    elif typ == 'timedelta64':
        return np.timedelta64(int(obj['data']))
    # elif typ == 'sparse_series':
    #    dtype = dtype_for(obj['dtype'])
    #    return SparseSeries(
    #        unconvert(obj['sp_values'], dtype, obj['compress']),
    #        sparse_index=obj['sp_index'], index=obj['index'],
    #        fill_value=obj['fill_value'], kind=obj['kind'], name=obj['name'])
    # elif typ == 'sparse_dataframe':
    #    return SparseDataFrame(
    #        obj['data'], columns=obj['columns'],
    #        default_fill_value=obj['default_fill_value'],
    #        default_kind=obj['default_kind']
    #    )
    # elif typ == 'sparse_panel':
    #    return SparsePanel(
    #        obj['data'], items=obj['items'],
    #        default_fill_value=obj['default_fill_value'],
    #        default_kind=obj['default_kind'])
    elif typ == 'block_index':
        return globals()[obj['klass']](obj['length'], obj['blocs'],
                                       obj['blengths'])
    elif typ == 'int_index':
        return globals()[obj['klass']](obj['length'], obj['indices'])
    elif typ == 'ndarray':
        return unconvert(obj['data'], np.typeDict[obj['dtype']],
                         obj.get('compress')).reshape(obj['shape'])
    elif typ == 'np_scalar':
        if obj.get('sub_typ') == 'np_complex':
            return c2f(obj['real'], obj['imag'], obj['dtype'])
        else:
            dtype = dtype_for(obj['dtype'])
            try:
                return dtype(obj['data'])
            except (ValueError, TypeError):
                return dtype.type(obj['data'])
    elif typ == 'np_complex':
        return complex(obj['real'] + '+' + obj['imag'] + 'j')
    elif isinstance(obj, (dict, list, set)):
        return obj
    else:
        return obj
Пример #53
0
    def test_constructor(self):
        index = RangeIndex(5)
        expected = np.arange(5, dtype=np.int64)
        assert isinstance(index, RangeIndex)
        assert index._start == 0
        assert index._stop == 5
        assert index._step == 1
        assert index.name is None
        tm.assert_index_equal(Index(expected), index)

        index = RangeIndex(1, 5)
        expected = np.arange(1, 5, dtype=np.int64)
        assert isinstance(index, RangeIndex)
        assert index._start == 1
        tm.assert_index_equal(Index(expected), index)

        index = RangeIndex(1, 5, 2)
        expected = np.arange(1, 5, 2, dtype=np.int64)
        assert isinstance(index, RangeIndex)
        assert index._step == 2
        tm.assert_index_equal(Index(expected), index)

        for index in [
                RangeIndex(0),
                RangeIndex(start=0),
                RangeIndex(stop=0),
                RangeIndex(0, 0)
        ]:
            expected = np.empty(0, dtype=np.int64)
            assert isinstance(index, RangeIndex)
            assert index._start == 0
            assert index._stop == 0
            assert index._step == 1
            tm.assert_index_equal(Index(expected), index)

        for index in [
                RangeIndex(0, name='Foo'),
                RangeIndex(start=0, name='Foo'),
                RangeIndex(stop=0, name='Foo'),
                RangeIndex(0, 0, name='Foo')
        ]:
            assert isinstance(index, RangeIndex)
            assert index.name == 'Foo'

        # we don't allow on a bare Index
        with pytest.raises(TypeError):
            Index(0, 1000)
Пример #54
0
    def _get_index_loc(self, key, base_index=None):
        """
        Get the location of a specific key in an index

        Parameters
        ----------
        key : label
            The key for which to find the location if the underlying index is
            a DateIndex or a location if the underlying index is a RangeIndex
            or an Int64Index.
        base_index : pd.Index, optional
            Optionally the base index to search. If None, the model's index is
            searched.

        Returns
        -------
        loc : int
            The location of the key
        index : pd.Index
            The index including the key; this is a copy of the original index
            unless the index had to be expanded to accomodate `key`.
        index_was_expanded : bool
            Whether or not the index was expanded to accomodate `key`.

        Notes
        -----
        If `key` is past the end of of the given index, and the index is either
        an Int64Index or a date index, this function extends the index up to
        and including key, and then returns the location in the new index.

        """
        if base_index is None:
            base_index = self._index

        index = base_index
        date_index = isinstance(base_index, (PeriodIndex, DatetimeIndex))
        int_index = isinstance(base_index, Int64Index)
        range_index = isinstance(base_index, RangeIndex)
        index_class = type(base_index)
        nobs = len(index)

        # Special handling for RangeIndex
        if range_index and isinstance(key, (int, long, np.integer)):
            # Negative indices (that lie in the Index)
            if key < 0 and -key <= nobs:
                key = nobs + key
            # Out-of-sample (note that we include key itself in the new index)
            elif key > nobs - 1:
                stop = base_index._start + (key + 1) * base_index._step
                index = RangeIndex(start=base_index._start,
                                   stop=stop,
                                   step=base_index._step)

        # Special handling for Int64Index
        if (not range_index and int_index and not date_index and
                isinstance(key, (int, long, np.integer))):
            # Negative indices (that lie in the Index)
            if key < 0 and -key <= nobs:
                key = nobs + key
            # Out-of-sample (note that we include key itself in the new index)
            elif key > base_index[-1]:
                index = Int64Index(np.arange(base_index[0], int(key + 1)))

        # Special handling for date indexes
        if date_index:
            # Integer key (i.e. already given a location)
            if isinstance(key, (int, long, np.integer)):
                # Negative indices (that lie in the Index)
                if key < 0 and -key < nobs:
                    key = index[nobs + key]
                # Out-of-sample (note that we include key itself in the new
                # index)
                elif key > len(base_index) - 1:
                    index = index_class(start=base_index[0],
                                        periods=int(key + 1),
                                        freq=base_index.freq)
                    key = index[-1]
                else:
                    key = index[key]
            # Other key types (i.e. string date or some datetime-like object)
            else:
                # Covert the key to the appropriate date-like object
                if index_class is PeriodIndex:
                    date_key = Period(key, freq=base_index.freq)
                else:
                    date_key = Timestamp(key)

                # Out-of-sample
                if date_key > base_index[-1]:
                    # First create an index that may not always include `key`
                    index = index_class(start=base_index[0], end=date_key,
                                        freq=base_index.freq)

                    # Now make sure we include `key`
                    if not index[-1] == date_key:
                        index = index_class(start=base_index[0],
                                            periods=len(index) + 1,
                                            freq=base_index.freq)

        # Get the location
        if date_index:
            # (note that get_loc will throw a KeyError if key is invalid)
            loc = index.get_loc(key)
        elif int_index or range_index:
            # For Int64Index and RangeIndex, key is assumed to be the location
            # and not an index value (this assumption is required to support
            # RangeIndex)
            try:
                index[key]
            # We want to raise a KeyError in this case, to keep the exception
            # consistent across index types.
            # - Attempting to index with an out-of-bound location (e.g.
            #   index[10] on an index of length 9) will raise an IndexError
            #   (as of Pandas 0.22)
            # - Attemtping to index with a type that cannot be cast to integer
            #   (e.g. a non-numeric string) will raise a ValueError if the
            #   index is RangeIndex (otherwise will raise an IndexError)
            #   (as of Pandas 0.22)
            except (IndexError, ValueError) as e:
                raise KeyError(str(e))
            loc = key
        else:
            loc = index.get_loc(key)

        # Check if we now have a modified index
        index_was_expanded = index is not base_index

        # Return the index through the end of the loc / slice
        if isinstance(loc, slice):
            end = loc.stop
        else:
            end = loc

        return loc, index[:end + 1], index_was_expanded
Пример #55
0
class TestRangeIndex(Numeric):
    _holder = RangeIndex
    _compat_props = ["shape", "ndim", "size"]

    @pytest.fixture(
        params=[
            RangeIndex(start=0, stop=20, step=2, name="foo"),
            RangeIndex(start=18, stop=-1, step=-2, name="bar"),
        ],
        ids=["index_inc", "index_dec"],
    )
    def indices(self, request):
        return request.param

    def create_index(self):
        return RangeIndex(start=0, stop=20, step=2)

    def test_can_hold_identifiers(self):
        idx = self.create_index()
        key = idx[0]
        assert idx._can_hold_identifiers_and_holds_name(key) is False

    def test_too_many_names(self):
        index = self.create_index()
        with pytest.raises(ValueError, match="^Length"):
            index.names = ["roger", "harold"]

    @pytest.mark.parametrize(
        "index, start, stop, step",
        [
            (RangeIndex(5), 0, 5, 1),
            (RangeIndex(0, 5), 0, 5, 1),
            (RangeIndex(5, step=2), 0, 5, 2),
            (RangeIndex(1, 5, 2), 1, 5, 2),
        ],
    )
    def test_start_stop_step_attrs(self, index, start, stop, step):
        # GH 25710
        assert index.start == start
        assert index.stop == stop
        assert index.step == step

    @pytest.mark.parametrize("attr_name", ["_start", "_stop", "_step"])
    def test_deprecated_start_stop_step_attrs(self, attr_name):
        # GH 26581
        idx = self.create_index()
        with tm.assert_produces_warning(FutureWarning):
            getattr(idx, attr_name)

    def test_copy(self):
        i = RangeIndex(5, name="Foo")
        i_copy = i.copy()
        assert i_copy is not i
        assert i_copy.identical(i)
        assert i_copy._range == range(0, 5, 1)
        assert i_copy.name == "Foo"

    def test_repr(self):
        i = RangeIndex(5, name="Foo")
        result = repr(i)
        expected = "RangeIndex(start=0, stop=5, step=1, name='Foo')"
        assert result == expected

        result = eval(result)
        tm.assert_index_equal(result, i, exact=True)

        i = RangeIndex(5, 0, -1)
        result = repr(i)
        expected = "RangeIndex(start=5, stop=0, step=-1)"
        assert result == expected

        result = eval(result)
        tm.assert_index_equal(result, i, exact=True)

    def test_insert(self):

        idx = RangeIndex(5, name="Foo")
        result = idx[1:4]

        # test 0th element
        tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]))

        # GH 18295 (test missing)
        expected = Float64Index([0, np.nan, 1, 2, 3, 4])
        for na in (np.nan, pd.NaT, None):
            result = RangeIndex(5).insert(1, na)
            tm.assert_index_equal(result, expected)

    def test_delete(self):

        idx = RangeIndex(5, name="Foo")
        expected = idx[1:].astype(int)
        result = idx.delete(0)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

        expected = idx[:-1].astype(int)
        result = idx.delete(-1)
        tm.assert_index_equal(result, expected)
        assert result.name == expected.name

        with pytest.raises((IndexError, ValueError)):
            # either depending on numpy version
            result = idx.delete(len(idx))

    def test_view(self):
        i = RangeIndex(0, name="Foo")
        i_view = i.view()
        assert i_view.name == "Foo"

        i_view = i.view("i8")
        tm.assert_numpy_array_equal(i.values, i_view)

        i_view = i.view(RangeIndex)
        tm.assert_index_equal(i, i_view)

    def test_dtype(self):
        index = self.create_index()
        assert index.dtype == np.int64

    def test_cached_data(self):
        # GH 26565, GH26617
        # Calling RangeIndex._data caches an int64 array of the same length at
        # self._cached_data. This test checks whether _cached_data has been set
        idx = RangeIndex(0, 100, 10)

        assert idx._cached_data is None

        repr(idx)
        assert idx._cached_data is None

        str(idx)
        assert idx._cached_data is None

        idx.get_loc(20)
        assert idx._cached_data is None

        90 in idx
        assert idx._cached_data is None

        91 in idx
        assert idx._cached_data is None

        idx.all()
        assert idx._cached_data is None

        idx.any()
        assert idx._cached_data is None

        df = pd.DataFrame({"a": range(10)}, index=idx)

        df.loc[50]
        assert idx._cached_data is None

        with pytest.raises(KeyError, match="51"):
            df.loc[51]
        assert idx._cached_data is None

        df.loc[10:50]
        assert idx._cached_data is None

        df.iloc[5:10]
        assert idx._cached_data is None

        # actually calling idx._data
        assert isinstance(idx._data, np.ndarray)
        assert isinstance(idx._cached_data, np.ndarray)

    def test_is_monotonic(self):
        index = RangeIndex(0, 20, 2)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is False
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is False

        index = RangeIndex(4, 0, -1)
        assert index.is_monotonic is False
        assert index._is_strictly_monotonic_increasing is False
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_decreasing is True

        index = RangeIndex(1, 2)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is True

        index = RangeIndex(2, 1)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is True

        index = RangeIndex(1, 1)
        assert index.is_monotonic is True
        assert index.is_monotonic_increasing is True
        assert index.is_monotonic_decreasing is True
        assert index._is_strictly_monotonic_increasing is True
        assert index._is_strictly_monotonic_decreasing is True

    def test_equals_range(self):
        equiv_pairs = [
            (RangeIndex(0, 9, 2), RangeIndex(0, 10, 2)),
            (RangeIndex(0), RangeIndex(1, -1, 3)),
            (RangeIndex(1, 2, 3), RangeIndex(1, 3, 4)),
            (RangeIndex(0, -9, -2), RangeIndex(0, -10, -2)),
        ]
        for left, right in equiv_pairs:
            assert left.equals(right)
            assert right.equals(left)

    def test_logical_compat(self):
        idx = self.create_index()
        assert idx.all() == idx.values.all()
        assert idx.any() == idx.values.any()

    def test_identical(self):
        index = self.create_index()
        i = Index(index.copy())
        assert i.identical(index)

        # we don't allow object dtype for RangeIndex
        if isinstance(index, RangeIndex):
            return

        same_values_different_type = Index(i, dtype=object)
        assert not i.identical(same_values_different_type)

        i = index.copy(dtype=object)
        i = i.rename("foo")
        same_values = Index(i, dtype=object)
        assert same_values.identical(index.copy(dtype=object))

        assert not i.identical(index)
        assert Index(same_values, name="foo", dtype=object).identical(i)

        assert not index.copy(dtype=object).identical(index.copy(dtype="int64"))

    def test_get_indexer(self):
        index = self.create_index()
        target = RangeIndex(10)
        indexer = index.get_indexer(target)
        expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

    def test_get_indexer_pad(self):
        index = self.create_index()
        target = RangeIndex(10)
        indexer = index.get_indexer(target, method="pad")
        expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

    def test_get_indexer_backfill(self):
        index = self.create_index()
        target = RangeIndex(10)
        indexer = index.get_indexer(target, method="backfill")
        expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
        tm.assert_numpy_array_equal(indexer, expected)

    def test_get_indexer_limit(self):
        # GH 28631
        idx = RangeIndex(4)
        target = RangeIndex(6)
        result = idx.get_indexer(target, method="pad", limit=1)
        expected = np.array([0, 1, 2, 3, 3, -1], dtype=np.intp)
        tm.assert_numpy_array_equal(result, expected)

    @pytest.mark.parametrize("stop", [0, -1, -2])
    def test_get_indexer_decreasing(self, stop):
        # GH 28678
        index = RangeIndex(7, stop, -3)
        result = index.get_indexer(range(9))
        expected = np.array([-1, 2, -1, -1, 1, -1, -1, 0, -1], dtype=np.intp)
        tm.assert_numpy_array_equal(result, expected)

    def test_join_outer(self):
        # join with Int64Index
        index = self.create_index()
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = index.join(other, how="outer", return_indexers=True)
        noidx_res = index.join(other, how="outer")
        tm.assert_index_equal(res, noidx_res)

        eres = Int64Index(
            [0, 2, 4, 6, 8, 10, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]
        )
        elidx = np.array(
            [0, 1, 2, 3, 4, 5, 6, 7, -1, 8, -1, 9, -1, -1, -1, -1, -1, -1, -1],
            dtype=np.intp,
        )
        eridx = np.array(
            [-1, -1, -1, -1, -1, -1, -1, -1, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0],
            dtype=np.intp,
        )

        assert isinstance(res, Int64Index)
        assert not isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

        # join with RangeIndex
        other = RangeIndex(25, 14, -1)

        res, lidx, ridx = index.join(other, how="outer", return_indexers=True)
        noidx_res = index.join(other, how="outer")
        tm.assert_index_equal(res, noidx_res)

        assert isinstance(res, Int64Index)
        assert not isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_inner(self):
        # Join with non-RangeIndex
        index = self.create_index()
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = index.join(other, how="inner", return_indexers=True)

        # no guarantee of sortedness, so sort for comparison purposes
        ind = res.argsort()
        res = res.take(ind)
        lidx = lidx.take(ind)
        ridx = ridx.take(ind)

        eres = Int64Index([16, 18])
        elidx = np.array([8, 9], dtype=np.intp)
        eridx = np.array([9, 7], dtype=np.intp)

        assert isinstance(res, Int64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

        # Join two RangeIndex
        other = RangeIndex(25, 14, -1)

        res, lidx, ridx = index.join(other, how="inner", return_indexers=True)

        assert isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_left(self):
        # Join with Int64Index
        index = self.create_index()
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = index.join(other, how="left", return_indexers=True)
        eres = index
        eridx = np.array([-1, -1, -1, -1, -1, -1, -1, -1, 9, 7], dtype=np.intp)

        assert isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        assert lidx is None
        tm.assert_numpy_array_equal(ridx, eridx)

        # Join withRangeIndex
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = index.join(other, how="left", return_indexers=True)

        assert isinstance(res, RangeIndex)
        tm.assert_index_equal(res, eres)
        assert lidx is None
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_right(self):
        # Join with Int64Index
        index = self.create_index()
        other = Int64Index(np.arange(25, 14, -1))

        res, lidx, ridx = index.join(other, how="right", return_indexers=True)
        eres = other
        elidx = np.array([-1, -1, -1, -1, -1, -1, -1, 9, -1, 8, -1], dtype=np.intp)

        assert isinstance(other, Int64Index)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        assert ridx is None

        # Join withRangeIndex
        other = RangeIndex(25, 14, -1)

        res, lidx, ridx = index.join(other, how="right", return_indexers=True)
        eres = other

        assert isinstance(other, RangeIndex)
        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        assert ridx is None

    def test_join_non_int_index(self):
        index = self.create_index()
        other = Index([3, 6, 7, 8, 10], dtype=object)

        outer = index.join(other, how="outer")
        outer2 = other.join(index, how="outer")
        expected = Index([0, 2, 3, 4, 6, 7, 8, 10, 12, 14, 16, 18])
        tm.assert_index_equal(outer, outer2)
        tm.assert_index_equal(outer, expected)

        inner = index.join(other, how="inner")
        inner2 = other.join(index, how="inner")
        expected = Index([6, 8, 10])
        tm.assert_index_equal(inner, inner2)
        tm.assert_index_equal(inner, expected)

        left = index.join(other, how="left")
        tm.assert_index_equal(left, index.astype(object))

        left2 = other.join(index, how="left")
        tm.assert_index_equal(left2, other)

        right = index.join(other, how="right")
        tm.assert_index_equal(right, other)

        right2 = other.join(index, how="right")
        tm.assert_index_equal(right2, index.astype(object))

    def test_join_non_unique(self):
        index = self.create_index()
        other = Index([4, 4, 3, 3])

        res, lidx, ridx = index.join(other, return_indexers=True)

        eres = Int64Index([0, 2, 4, 4, 6, 8, 10, 12, 14, 16, 18])
        elidx = np.array([0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9], dtype=np.intp)
        eridx = np.array([-1, -1, 0, 1, -1, -1, -1, -1, -1, -1, -1], dtype=np.intp)

        tm.assert_index_equal(res, eres)
        tm.assert_numpy_array_equal(lidx, elidx)
        tm.assert_numpy_array_equal(ridx, eridx)

    def test_join_self(self, join_type):
        index = self.create_index()
        joined = index.join(index, how=join_type)
        assert index is joined

    def test_nbytes(self):

        # memory savings vs int index
        i = RangeIndex(0, 1000)
        assert i.nbytes < i._int64index.nbytes / 10

        # constant memory usage
        i2 = RangeIndex(0, 10)
        assert i.nbytes == i2.nbytes

    def test_cant_or_shouldnt_cast(self):
        # can't
        with pytest.raises(TypeError):
            RangeIndex("foo", "bar", "baz")

        # shouldn't
        with pytest.raises(TypeError):
            RangeIndex("0", "1", "2")

    def test_view_index(self):
        index = self.create_index()
        index.view(Index)

    def test_prevent_casting(self):
        index = self.create_index()
        result = index.astype("O")
        assert result.dtype == np.object_

    def test_take_preserve_name(self):
        index = RangeIndex(1, 5, name="foo")
        taken = index.take([3, 0, 1])
        assert index.name == taken.name

    def test_take_fill_value(self):
        # GH 12631
        idx = pd.RangeIndex(1, 4, name="xxx")
        result = idx.take(np.array([1, 0, -1]))
        expected = pd.Int64Index([2, 1, 3], name="xxx")
        tm.assert_index_equal(result, expected)

        # fill_value
        msg = "Unable to fill values because RangeIndex cannot contain NA"
        with pytest.raises(ValueError, match=msg):
            idx.take(np.array([1, 0, -1]), fill_value=True)

        # allow_fill=False
        result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
        expected = pd.Int64Index([2, 1, 3], name="xxx")
        tm.assert_index_equal(result, expected)

        msg = "Unable to fill values because RangeIndex cannot contain NA"
        with pytest.raises(ValueError, match=msg):
            idx.take(np.array([1, 0, -2]), fill_value=True)
        with pytest.raises(ValueError, match=msg):
            idx.take(np.array([1, 0, -5]), fill_value=True)

        with pytest.raises(IndexError):
            idx.take(np.array([1, -5]))

    def test_print_unicode_columns(self):
        df = pd.DataFrame({"\u05d0": [1, 2, 3], "\u05d1": [4, 5, 6], "c": [7, 8, 9]})
        repr(df.columns)  # should not raise UnicodeDecodeError

    def test_repr_roundtrip(self):
        index = self.create_index()
        tm.assert_index_equal(eval(repr(index)), index)

    def test_slice_keep_name(self):
        idx = RangeIndex(1, 2, name="asdf")
        assert idx.name == idx[1:].name

    def test_explicit_conversions(self):

        # GH 8608
        # add/sub are overridden explicitly for Float/Int Index
        idx = RangeIndex(5)

        # float conversions
        arr = np.arange(5, dtype="int64") * 3.2
        expected = Float64Index(arr)
        fidx = idx * 3.2
        tm.assert_index_equal(fidx, expected)
        fidx = 3.2 * idx
        tm.assert_index_equal(fidx, expected)

        # interops with numpy arrays
        expected = Float64Index(arr)
        a = np.zeros(5, dtype="float64")
        result = fidx - a
        tm.assert_index_equal(result, expected)

        expected = Float64Index(-arr)
        a = np.zeros(5, dtype="float64")
        result = a - fidx
        tm.assert_index_equal(result, expected)

    def test_has_duplicates(self, indices):
        assert indices.is_unique
        assert not indices.has_duplicates

    def test_extended_gcd(self):
        index = self.create_index()
        result = index._extended_gcd(6, 10)
        assert result[0] == result[1] * 6 + result[2] * 10
        assert 2 == result[0]

        result = index._extended_gcd(10, 6)
        assert 2 == result[1] * 10 + result[2] * 6
        assert 2 == result[0]

    def test_min_fitting_element(self):
        result = RangeIndex(0, 20, 2)._min_fitting_element(1)
        assert 2 == result

        result = RangeIndex(1, 6)._min_fitting_element(1)
        assert 1 == result

        result = RangeIndex(18, -2, -2)._min_fitting_element(1)
        assert 2 == result

        result = RangeIndex(5, 0, -1)._min_fitting_element(1)
        assert 1 == result

        big_num = 500000000000000000000000

        result = RangeIndex(5, big_num * 2, 1)._min_fitting_element(big_num)
        assert big_num == result

    def test_max_fitting_element(self):
        result = RangeIndex(0, 20, 2)._max_fitting_element(17)
        assert 16 == result

        result = RangeIndex(1, 6)._max_fitting_element(4)
        assert 4 == result

        result = RangeIndex(18, -2, -2)._max_fitting_element(17)
        assert 16 == result

        result = RangeIndex(5, 0, -1)._max_fitting_element(4)
        assert 4 == result

        big_num = 500000000000000000000000

        result = RangeIndex(5, big_num * 2, 1)._max_fitting_element(big_num)
        assert big_num == result

    def test_pickle_compat_construction(self):
        # RangeIndex() is a valid constructor
        pass

    def test_slice_specialised(self):
        index = self.create_index()
        index.name = "foo"

        # scalar indexing
        res = index[1]
        expected = 2
        assert res == expected

        res = index[-1]
        expected = 18
        assert res == expected

        # slicing
        # slice value completion
        index_slice = index[:]
        expected = index
        tm.assert_index_equal(index_slice, expected)

        # positive slice values
        index_slice = index[7:10:2]
        expected = Index(np.array([14, 18]), name="foo")
        tm.assert_index_equal(index_slice, expected)

        # negative slice values
        index_slice = index[-1:-5:-2]
        expected = Index(np.array([18, 14]), name="foo")
        tm.assert_index_equal(index_slice, expected)

        # stop overshoot
        index_slice = index[2:100:4]
        expected = Index(np.array([4, 12]), name="foo")
        tm.assert_index_equal(index_slice, expected)

        # reverse
        index_slice = index[::-1]
        expected = Index(index.values[::-1], name="foo")
        tm.assert_index_equal(index_slice, expected)

        index_slice = index[-8::-1]
        expected = Index(np.array([4, 2, 0]), name="foo")
        tm.assert_index_equal(index_slice, expected)

        index_slice = index[-40::-1]
        expected = Index(np.array([], dtype=np.int64), name="foo")
        tm.assert_index_equal(index_slice, expected)

        index_slice = index[40::-1]
        expected = Index(index.values[40::-1], name="foo")
        tm.assert_index_equal(index_slice, expected)

        index_slice = index[10::-1]
        expected = Index(index.values[::-1], name="foo")
        tm.assert_index_equal(index_slice, expected)

    @pytest.mark.parametrize("step", set(range(-5, 6)) - {0})
    def test_len_specialised(self, step):
        # make sure that our len is the same as np.arange calc
        start, stop = (0, 5) if step > 0 else (5, 0)

        arr = np.arange(start, stop, step)
        index = RangeIndex(start, stop, step)
        assert len(index) == len(arr)

        index = RangeIndex(stop, start, step)
        assert len(index) == 0

    @pytest.fixture(
        params=[
            ([RI(1, 12, 5)], RI(1, 12, 5)),
            ([RI(0, 6, 4)], RI(0, 6, 4)),
            ([RI(1, 3), RI(3, 7)], RI(1, 7)),
            ([RI(1, 5, 2), RI(5, 6)], RI(1, 6, 2)),
            ([RI(1, 3, 2), RI(4, 7, 3)], RI(1, 7, 3)),
            ([RI(-4, 3, 2), RI(4, 7, 2)], RI(-4, 7, 2)),
            ([RI(-4, -8), RI(-8, -12)], RI(0, 0)),
            ([RI(-4, -8), RI(3, -4)], RI(0, 0)),
            ([RI(-4, -8), RI(3, 5)], RI(3, 5)),
            ([RI(-4, -2), RI(3, 5)], I64([-4, -3, 3, 4])),
            ([RI(-2), RI(3, 5)], RI(3, 5)),
            ([RI(2), RI(2)], I64([0, 1, 0, 1])),
            ([RI(2), RI(2, 5), RI(5, 8, 4)], RI(0, 6)),
            ([RI(2), RI(3, 5), RI(5, 8, 4)], I64([0, 1, 3, 4, 5])),
            ([RI(-2, 2), RI(2, 5), RI(5, 8, 4)], RI(-2, 6)),
            ([RI(3), I64([-1, 3, 15])], I64([0, 1, 2, -1, 3, 15])),
            ([RI(3), F64([-1, 3.1, 15.0])], F64([0, 1, 2, -1, 3.1, 15.0])),
            ([RI(3), OI(["a", None, 14])], OI([0, 1, 2, "a", None, 14])),
            ([RI(3, 1), OI(["a", None, 14])], OI(["a", None, 14])),
        ]
    )
    def appends(self, request):
        """Inputs and expected outputs for RangeIndex.append test"""

        return request.param

    def test_append(self, appends):
        # GH16212

        indices, expected = appends

        result = indices[0].append(indices[1:])
        tm.assert_index_equal(result, expected, exact=True)

        if len(indices) == 2:
            # Append single item rather than list
            result2 = indices[0].append(indices[1])
            tm.assert_index_equal(result2, expected, exact=True)

    def test_engineless_lookup(self):
        # GH 16685
        # Standard lookup on RangeIndex should not require the engine to be
        # created
        idx = RangeIndex(2, 10, 3)

        assert idx.get_loc(5) == 1
        tm.assert_numpy_array_equal(
            idx.get_indexer([2, 8]), ensure_platform_int(np.array([0, 2]))
        )
        with pytest.raises(KeyError, match="3"):
            idx.get_loc(3)

        assert "_engine" not in idx._cache

        # The engine is still required for lookup of a different dtype scalar:
        with pytest.raises(KeyError, match="'a'"):
            assert idx.get_loc("a") == -1

        assert "_engine" in idx._cache
Пример #56
0
 def test_get_indexer_backfill(self):
     index = self.create_index()
     target = RangeIndex(10)
     indexer = index.get_indexer(target, method="backfill")
     expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
     tm.assert_numpy_array_equal(indexer, expected)
Пример #57
0
 def test_take_preserve_name(self):
     index = RangeIndex(1, 5, name='foo')
     taken = index.take([3, 0, 1])
     assert index.name == taken.name
 def test_constructor_range_object(self):
     result = RangeIndex(range(1, 5, 2))
     expected = RangeIndex(1, 5, 2)
     tm.assert_index_equal(result, expected, exact=True)
Пример #59
0
class Range:
    def setup(self):
        self.idx_inc = RangeIndex(start=0, stop=10**7, step=3)
        self.idx_dec = RangeIndex(start=10**7, stop=-1, step=-3)

    def time_max(self):
        self.idx_inc.max()

    def time_max_trivial(self):
        self.idx_dec.max()

    def time_min(self):
        self.idx_dec.min()

    def time_min_trivial(self):
        self.idx_inc.min()

    def time_get_loc_inc(self):
        self.idx_inc.get_loc(900000)

    def time_get_loc_dec(self):
        self.idx_dec.get_loc(100000)
Пример #60
0
class TestRangeIndexSetOps:
    @pytest.mark.parametrize("sort", [None, False])
    def test_intersection(self, sort):
        # intersect with Int64Index
        index = RangeIndex(start=0, stop=20, step=2)
        other = Index(np.arange(1, 6))
        result = index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
        tm.assert_index_equal(result, expected)

        result = other.intersection(index, sort=sort)
        expected = Index(
            np.sort(np.asarray(np.intersect1d(index.values, other.values))))
        tm.assert_index_equal(result, expected)

        # intersect with increasing RangeIndex
        other = RangeIndex(1, 6)
        result = index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
        tm.assert_index_equal(result, expected)

        # intersect with decreasing RangeIndex
        other = RangeIndex(5, 0, -1)
        result = index.intersection(other, sort=sort)
        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
        tm.assert_index_equal(result, expected)

        # reversed (GH 17296)
        result = other.intersection(index, sort=sort)
        tm.assert_index_equal(result, expected)

        # GH 17296: intersect two decreasing RangeIndexes
        first = RangeIndex(10, -2, -2)
        other = RangeIndex(5, -4, -1)
        expected = first.astype(int).intersection(other.astype(int), sort=sort)
        result = first.intersection(other, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        # reversed
        result = other.intersection(first, sort=sort).astype(int)
        tm.assert_index_equal(result, expected)

        index = RangeIndex(5)

        # intersect of non-overlapping indices
        other = RangeIndex(5, 10, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        other = RangeIndex(-1, -5, -1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        # intersection of empty indices
        other = RangeIndex(0, 0, 1)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

        result = other.intersection(index, sort=sort)
        tm.assert_index_equal(result, expected)

        # intersection of non-overlapping values based on start value and gcd
        index = RangeIndex(1, 10, 2)
        other = RangeIndex(0, 10, 4)
        result = index.intersection(other, sort=sort)
        expected = RangeIndex(0, 0, 1)
        tm.assert_index_equal(result, expected)

    @pytest.mark.parametrize("sort", [False, None])
    def test_union_noncomparable(self, sort):
        # corner case, non-Int64Index
        index = RangeIndex(start=0, stop=20, step=2)
        other = Index([datetime.now() + timedelta(i) for i in range(4)],
                      dtype=object)
        result = index.union(other, sort=sort)
        expected = Index(np.concatenate((index, other)))
        tm.assert_index_equal(result, expected)

        result = other.union(index, sort=sort)
        expected = Index(np.concatenate((other, index)))
        tm.assert_index_equal(result, expected)

    @pytest.fixture(params=[
        (
            RangeIndex(0, 10, 1),
            RangeIndex(0, 10, 1),
            RangeIndex(0, 10, 1),
            RangeIndex(0, 10, 1),
        ),
        (
            RangeIndex(0, 10, 1),
            RangeIndex(5, 20, 1),
            RangeIndex(0, 20, 1),
            Int64Index(range(20)),
        ),
        (
            RangeIndex(0, 10, 1),
            RangeIndex(10, 20, 1),
            RangeIndex(0, 20, 1),
            Int64Index(range(20)),
        ),
        (
            RangeIndex(0, -10, -1),
            RangeIndex(0, -10, -1),
            RangeIndex(0, -10, -1),
            RangeIndex(0, -10, -1),
        ),
        (
            RangeIndex(0, -10, -1),
            RangeIndex(-10, -20, -1),
            RangeIndex(-19, 1, 1),
            Int64Index(range(0, -20, -1)),
        ),
        (
            RangeIndex(0, 10, 2),
            RangeIndex(1, 10, 2),
            RangeIndex(0, 10, 1),
            Int64Index(list(range(0, 10, 2)) + list(range(1, 10, 2))),
        ),
        (
            RangeIndex(0, 11, 2),
            RangeIndex(1, 12, 2),
            RangeIndex(0, 12, 1),
            Int64Index(list(range(0, 11, 2)) + list(range(1, 12, 2))),
        ),
        (
            RangeIndex(0, 21, 4),
            RangeIndex(-2, 24, 4),
            RangeIndex(-2, 24, 2),
            Int64Index(list(range(0, 21, 4)) + list(range(-2, 24, 4))),
        ),
        (
            RangeIndex(0, -20, -2),
            RangeIndex(-1, -21, -2),
            RangeIndex(-19, 1, 1),
            Int64Index(list(range(0, -20, -2)) + list(range(-1, -21, -2))),
        ),
        (
            RangeIndex(0, 100, 5),
            RangeIndex(0, 100, 20),
            RangeIndex(0, 100, 5),
            Int64Index(range(0, 100, 5)),
        ),
        (
            RangeIndex(0, -100, -5),
            RangeIndex(5, -100, -20),
            RangeIndex(-95, 10, 5),
            Int64Index(list(range(0, -100, -5)) + [5]),
        ),
        (
            RangeIndex(0, -11, -1),
            RangeIndex(1, -12, -4),
            RangeIndex(-11, 2, 1),
            Int64Index(list(range(0, -11, -1)) + [1, -11]),
        ),
        (RangeIndex(0), RangeIndex(0), RangeIndex(0), RangeIndex(0)),
        (
            RangeIndex(0, -10, -2),
            RangeIndex(0),
            RangeIndex(0, -10, -2),
            RangeIndex(0, -10, -2),
        ),
        (
            RangeIndex(0, 100, 2),
            RangeIndex(100, 150, 200),
            RangeIndex(0, 102, 2),
            Int64Index(range(0, 102, 2)),
        ),
        (
            RangeIndex(0, -100, -2),
            RangeIndex(-100, 50, 102),
            RangeIndex(-100, 4, 2),
            Int64Index(list(range(0, -100, -2)) + [-100, 2]),
        ),
        (
            RangeIndex(0, -100, -1),
            RangeIndex(0, -50, -3),
            RangeIndex(-99, 1, 1),
            Int64Index(list(range(0, -100, -1))),
        ),
        (
            RangeIndex(0, 1, 1),
            RangeIndex(5, 6, 10),
            RangeIndex(0, 6, 5),
            Int64Index([0, 5]),
        ),
        (
            RangeIndex(0, 10, 5),
            RangeIndex(-5, -6, -20),
            RangeIndex(-5, 10, 5),
            Int64Index([0, 5, -5]),
        ),
        (
            RangeIndex(0, 3, 1),
            RangeIndex(4, 5, 1),
            Int64Index([0, 1, 2, 4]),
            Int64Index([0, 1, 2, 4]),
        ),
        (
            RangeIndex(0, 10, 1),
            Int64Index([]),
            RangeIndex(0, 10, 1),
            RangeIndex(0, 10, 1),
        ),
        (
            RangeIndex(0),
            Int64Index([1, 5, 6]),
            Int64Index([1, 5, 6]),
            Int64Index([1, 5, 6]),
        ),
    ])
    def unions(self, request):
        """Inputs and expected outputs for RangeIndex.union tests"""

        return request.param

    def test_union_sorted(self, unions):

        idx1, idx2, expected_sorted, expected_notsorted = unions

        res1 = idx1.union(idx2, sort=None)
        tm.assert_index_equal(res1, expected_sorted, exact=True)

        res1 = idx1.union(idx2, sort=False)
        tm.assert_index_equal(res1, expected_notsorted, exact=True)

        res2 = idx2.union(idx1, sort=None)
        res3 = idx1._int64index.union(idx2, sort=None)
        tm.assert_index_equal(res2, expected_sorted, exact=True)
        tm.assert_index_equal(res3, expected_sorted)