venv

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_asof.py

@@ -0,0 +1,30 @@
+from datetime import timedelta
+
+from pandas import (
+    Index,
+    Timestamp,
+    date_range,
+    isna,
+)
+
+
+class TestAsOf:
+    def test_asof_partial(self):
+        index = date_range("2010-01-01", periods=2, freq="ME")
+        expected = Timestamp("2010-02-28")
+        result = index.asof("2010-02")
+        assert result == expected
+        assert not isinstance(result, Index)
+
+    def test_asof(self):
+        index = date_range("2020-01-01", periods=10)
+
+        dt = index[0]
+        assert index.asof(dt) == dt
+        assert isna(index.asof(dt - timedelta(1)))
+
+        dt = index[-1]
+        assert index.asof(dt + timedelta(1)) == dt
+
+        dt = index[0].to_pydatetime()
+        assert isinstance(index.asof(dt), Timestamp)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_astype.py

@@ -0,0 +1,335 @@
+from datetime import datetime
+
+import dateutil
+import numpy as np
+import pytest
+import pytz
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    Index,
+    NaT,
+    PeriodIndex,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndex:
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_astype_asobject_around_dst_transition(self, tzstr):
+        # GH#1345
+
+        # dates around a dst transition
+        rng = date_range("2/13/2010", "5/6/2010", tz=tzstr)
+
+        objs = rng.astype(object)
+        for i, x in enumerate(objs):
+            exval = rng[i]
+            assert x == exval
+            assert x.tzinfo == exval.tzinfo
+
+        objs = rng.astype(object)
+        for i, x in enumerate(objs):
+            exval = rng[i]
+            assert x == exval
+            assert x.tzinfo == exval.tzinfo
+
+    def test_astype(self):
+        # GH 13149, GH 13209
+        idx = DatetimeIndex(
+            ["2016-05-16", "NaT", NaT, np.nan], dtype="M8[ns]", name="idx"
+        )
+
+        result = idx.astype(object)
+        expected = Index(
+            [Timestamp("2016-05-16")] + [NaT] * 3, dtype=object, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.astype(np.int64)
+        expected = Index(
+            [1463356800000000000] + [-9223372036854775808] * 3,
+            dtype=np.int64,
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype2(self):
+        rng = date_range("1/1/2000", periods=10, name="idx")
+        result = rng.astype("i8")
+        tm.assert_index_equal(result, Index(rng.asi8, name="idx"))
+        tm.assert_numpy_array_equal(result.values, rng.asi8)
+
+    def test_astype_uint(self):
+        arr = date_range("2000", periods=2, name="idx")
+
+        with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
+            arr.astype("uint64")
+        with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
+            arr.astype("uint32")
+
+    def test_astype_with_tz(self):
+        # with tz
+        rng = date_range("1/1/2000", periods=10, tz="US/Eastern")
+        msg = "Cannot use .astype to convert from timezone-aware"
+        with pytest.raises(TypeError, match=msg):
+            # deprecated
+            rng.astype("datetime64[ns]")
+        with pytest.raises(TypeError, match=msg):
+            # check DatetimeArray while we're here deprecated
+            rng._data.astype("datetime64[ns]")
+
+    def test_astype_tzaware_to_tzaware(self):
+        # GH 18951: tz-aware to tz-aware
+        idx = date_range("20170101", periods=4, tz="US/Pacific")
+        result = idx.astype("datetime64[ns, US/Eastern]")
+        expected = date_range("20170101 03:00:00", periods=4, tz="US/Eastern")
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+    def test_astype_tznaive_to_tzaware(self):
+        # GH 18951: tz-naive to tz-aware
+        idx = date_range("20170101", periods=4)
+        idx = idx._with_freq(None)  # tz_localize does not preserve freq
+        msg = "Cannot use .astype to convert from timezone-naive"
+        with pytest.raises(TypeError, match=msg):
+            # dt64->dt64tz deprecated
+            idx.astype("datetime64[ns, US/Eastern]")
+        with pytest.raises(TypeError, match=msg):
+            # dt64->dt64tz deprecated
+            idx._data.astype("datetime64[ns, US/Eastern]")
+
+    def test_astype_str_nat(self):
+        # GH 13149, GH 13209
+        # verify that we are returning NaT as a string (and not unicode)
+
+        idx = DatetimeIndex(["2016-05-16", "NaT", NaT, np.nan])
+        result = idx.astype(str)
+        expected = Index(["2016-05-16", "NaT", "NaT", "NaT"], dtype=object)
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str(self):
+        # test astype string - #10442
+        dti = date_range("2012-01-01", periods=4, name="test_name")
+        result = dti.astype(str)
+        expected = Index(
+            ["2012-01-01", "2012-01-02", "2012-01-03", "2012-01-04"],
+            name="test_name",
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str_tz_and_name(self):
+        # test astype string with tz and name
+        dti = date_range("2012-01-01", periods=3, name="test_name", tz="US/Eastern")
+        result = dti.astype(str)
+        expected = Index(
+            [
+                "2012-01-01 00:00:00-05:00",
+                "2012-01-02 00:00:00-05:00",
+                "2012-01-03 00:00:00-05:00",
+            ],
+            name="test_name",
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str_freq_and_name(self):
+        # test astype string with freqH and name
+        dti = date_range("1/1/2011", periods=3, freq="h", name="test_name")
+        result = dti.astype(str)
+        expected = Index(
+            ["2011-01-01 00:00:00", "2011-01-01 01:00:00", "2011-01-01 02:00:00"],
+            name="test_name",
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_str_freq_and_tz(self):
+        # test astype string with freqH and timezone
+        dti = date_range(
+            "3/6/2012 00:00", periods=2, freq="h", tz="Europe/London", name="test_name"
+        )
+        result = dti.astype(str)
+        expected = Index(
+            ["2012-03-06 00:00:00+00:00", "2012-03-06 01:00:00+00:00"],
+            dtype=object,
+            name="test_name",
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_astype_datetime64(self):
+        # GH 13149, GH 13209
+        idx = DatetimeIndex(
+            ["2016-05-16", "NaT", NaT, np.nan], dtype="M8[ns]", name="idx"
+        )
+
+        result = idx.astype("datetime64[ns]")
+        tm.assert_index_equal(result, idx)
+        assert result is not idx
+
+        result = idx.astype("datetime64[ns]", copy=False)
+        tm.assert_index_equal(result, idx)
+        assert result is idx
+
+        idx_tz = DatetimeIndex(["2016-05-16", "NaT", NaT, np.nan], tz="EST", name="idx")
+        msg = "Cannot use .astype to convert from timezone-aware"
+        with pytest.raises(TypeError, match=msg):
+            # dt64tz->dt64 deprecated
+            result = idx_tz.astype("datetime64[ns]")
+
+    def test_astype_object(self):
+        rng = date_range("1/1/2000", periods=20)
+
+        casted = rng.astype("O")
+        exp_values = list(rng)
+
+        tm.assert_index_equal(casted, Index(exp_values, dtype=np.object_))
+        assert casted.tolist() == exp_values
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo"])
+    def test_astype_object_tz(self, tz):
+        idx = date_range(start="2013-01-01", periods=4, freq="ME", name="idx", tz=tz)
+        expected_list = [
+            Timestamp("2013-01-31", tz=tz),
+            Timestamp("2013-02-28", tz=tz),
+            Timestamp("2013-03-31", tz=tz),
+            Timestamp("2013-04-30", tz=tz),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        tm.assert_index_equal(result, expected)
+        assert idx.tolist() == expected_list
+
+    def test_astype_object_with_nat(self):
+        idx = DatetimeIndex(
+            [datetime(2013, 1, 1), datetime(2013, 1, 2), NaT, datetime(2013, 1, 4)],
+            name="idx",
+        )
+        expected_list = [
+            Timestamp("2013-01-01"),
+            Timestamp("2013-01-02"),
+            NaT,
+            Timestamp("2013-01-04"),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        tm.assert_index_equal(result, expected)
+        assert idx.tolist() == expected_list
+
+    @pytest.mark.parametrize(
+        "dtype",
+        [float, "timedelta64", "timedelta64[ns]", "datetime64", "datetime64[D]"],
+    )
+    def test_astype_raises(self, dtype):
+        # GH 13149, GH 13209
+        idx = DatetimeIndex(["2016-05-16", "NaT", NaT, np.nan])
+        msg = "Cannot cast DatetimeIndex to dtype"
+        if dtype == "datetime64":
+            msg = "Casting to unit-less dtype 'datetime64' is not supported"
+        with pytest.raises(TypeError, match=msg):
+            idx.astype(dtype)
+
+    def test_index_convert_to_datetime_array(self):
+        def _check_rng(rng):
+            converted = rng.to_pydatetime()
+            assert isinstance(converted, np.ndarray)
+            for x, stamp in zip(converted, rng):
+                assert isinstance(x, datetime)
+                assert x == stamp.to_pydatetime()
+                assert x.tzinfo == stamp.tzinfo
+
+        rng = date_range("20090415", "20090519")
+        rng_eastern = date_range("20090415", "20090519", tz="US/Eastern")
+        rng_utc = date_range("20090415", "20090519", tz="utc")
+
+        _check_rng(rng)
+        _check_rng(rng_eastern)
+        _check_rng(rng_utc)
+
+    def test_index_convert_to_datetime_array_explicit_pytz(self):
+        def _check_rng(rng):
+            converted = rng.to_pydatetime()
+            assert isinstance(converted, np.ndarray)
+            for x, stamp in zip(converted, rng):
+                assert isinstance(x, datetime)
+                assert x == stamp.to_pydatetime()
+                assert x.tzinfo == stamp.tzinfo
+
+        rng = date_range("20090415", "20090519")
+        rng_eastern = date_range("20090415", "20090519", tz=pytz.timezone("US/Eastern"))
+        rng_utc = date_range("20090415", "20090519", tz=pytz.utc)
+
+        _check_rng(rng)
+        _check_rng(rng_eastern)
+        _check_rng(rng_utc)
+
+    def test_index_convert_to_datetime_array_dateutil(self):
+        def _check_rng(rng):
+            converted = rng.to_pydatetime()
+            assert isinstance(converted, np.ndarray)
+            for x, stamp in zip(converted, rng):
+                assert isinstance(x, datetime)
+                assert x == stamp.to_pydatetime()
+                assert x.tzinfo == stamp.tzinfo
+
+        rng = date_range("20090415", "20090519")
+        rng_eastern = date_range("20090415", "20090519", tz="dateutil/US/Eastern")
+        rng_utc = date_range("20090415", "20090519", tz=dateutil.tz.tzutc())
+
+        _check_rng(rng)
+        _check_rng(rng_eastern)
+        _check_rng(rng_utc)
+
+    @pytest.mark.parametrize(
+        "tz, dtype",
+        [["US/Pacific", "datetime64[ns, US/Pacific]"], [None, "datetime64[ns]"]],
+    )
+    def test_integer_index_astype_datetime(self, tz, dtype):
+        # GH 20997, 20964, 24559
+        val = [Timestamp("2018-01-01", tz=tz).as_unit("ns")._value]
+        result = Index(val, name="idx").astype(dtype)
+        expected = DatetimeIndex(["2018-01-01"], tz=tz, name="idx").as_unit("ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_dti_astype_period(self):
+        idx = DatetimeIndex([NaT, "2011-01-01", "2011-02-01"], name="idx")
+
+        res = idx.astype("period[M]")
+        exp = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="M", name="idx")
+        tm.assert_index_equal(res, exp)
+
+        res = idx.astype("period[3M]")
+        exp = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="3M", name="idx")
+        tm.assert_index_equal(res, exp)
+
+
+class TestAstype:
+    @pytest.mark.parametrize("tz", [None, "US/Central"])
+    def test_astype_category(self, tz):
+        obj = date_range("2000", periods=2, tz=tz, name="idx")
+        result = obj.astype("category")
+        dti = DatetimeIndex(["2000-01-01", "2000-01-02"], tz=tz).as_unit("ns")
+        expected = pd.CategoricalIndex(
+            dti,
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype("category")
+        expected = expected.values
+        tm.assert_categorical_equal(result, expected)
+
+    @pytest.mark.parametrize("tz", [None, "US/Central"])
+    def test_astype_array_fallback(self, tz):
+        obj = date_range("2000", periods=2, tz=tz, name="idx")
+        result = obj.astype(bool)
+        expected = Index(np.array([True, True]), name="idx")
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype(bool)
+        expected = np.array([True, True])
+        tm.assert_numpy_array_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_delete.py

@@ -0,0 +1,141 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Series,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDelete:
+    def test_delete(self, unit):
+        idx = date_range(
+            start="2000-01-01", periods=5, freq="ME", name="idx", unit=unit
+        )
+
+        # preserve freq
+        expected_0 = date_range(
+            start="2000-02-01", periods=4, freq="ME", name="idx", unit=unit
+        )
+        expected_4 = date_range(
+            start="2000-01-01", periods=4, freq="ME", name="idx", unit=unit
+        )
+
+        # reset freq to None
+        expected_1 = DatetimeIndex(
+            ["2000-01-31", "2000-03-31", "2000-04-30", "2000-05-31"],
+            freq=None,
+            name="idx",
+        ).as_unit(unit)
+
+        cases = {
+            0: expected_0,
+            -5: expected_0,
+            -1: expected_4,
+            4: expected_4,
+            1: expected_1,
+        }
+        for n, expected in cases.items():
+            result = idx.delete(n)
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+        with pytest.raises((IndexError, ValueError), match="out of bounds"):
+            # either depending on numpy version
+            idx.delete(5)
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo", "US/Pacific"])
+    def test_delete2(self, tz):
+        idx = date_range(
+            start="2000-01-01 09:00", periods=10, freq="h", name="idx", tz=tz
+        )
+
+        expected = date_range(
+            start="2000-01-01 10:00", periods=9, freq="h", name="idx", tz=tz
+        )
+        result = idx.delete(0)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freqstr == "h"
+        assert result.tz == expected.tz
+
+        expected = date_range(
+            start="2000-01-01 09:00", periods=9, freq="h", name="idx", tz=tz
+        )
+        result = idx.delete(-1)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freqstr == "h"
+        assert result.tz == expected.tz
+
+    def test_delete_slice(self, unit):
+        idx = date_range(
+            start="2000-01-01", periods=10, freq="D", name="idx", unit=unit
+        )
+
+        # preserve freq
+        expected_0_2 = date_range(
+            start="2000-01-04", periods=7, freq="D", name="idx", unit=unit
+        )
+        expected_7_9 = date_range(
+            start="2000-01-01", periods=7, freq="D", name="idx", unit=unit
+        )
+
+        # reset freq to None
+        expected_3_5 = DatetimeIndex(
+            [
+                "2000-01-01",
+                "2000-01-02",
+                "2000-01-03",
+                "2000-01-07",
+                "2000-01-08",
+                "2000-01-09",
+                "2000-01-10",
+            ],
+            freq=None,
+            name="idx",
+        ).as_unit(unit)
+
+        cases = {
+            (0, 1, 2): expected_0_2,
+            (7, 8, 9): expected_7_9,
+            (3, 4, 5): expected_3_5,
+        }
+        for n, expected in cases.items():
+            result = idx.delete(n)
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+            result = idx.delete(slice(n[0], n[-1] + 1))
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+    # TODO: belongs in Series.drop tests?
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo", "US/Pacific"])
+    def test_delete_slice2(self, tz, unit):
+        dti = date_range(
+            "2000-01-01 09:00", periods=10, freq="h", name="idx", tz=tz, unit=unit
+        )
+        ts = Series(
+            1,
+            index=dti,
+        )
+        # preserve freq
+        result = ts.drop(ts.index[:5]).index
+        expected = dti[5:]
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freq == expected.freq
+        assert result.tz == expected.tz
+
+        # reset freq to None
+        result = ts.drop(ts.index[[1, 3, 5, 7, 9]]).index
+        expected = dti[::2]._with_freq(None)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freq == expected.freq
+        assert result.tz == expected.tz

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_factorize.py

@@ -0,0 +1,125 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    date_range,
+    factorize,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndexFactorize:
+    def test_factorize(self):
+        idx1 = DatetimeIndex(
+            ["2014-01", "2014-01", "2014-02", "2014-02", "2014-03", "2014-03"]
+        )
+
+        exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp)
+        exp_idx = DatetimeIndex(["2014-01", "2014-02", "2014-03"])
+
+        arr, idx = idx1.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        arr, idx = idx1.factorize(sort=True)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        # tz must be preserved
+        idx1 = idx1.tz_localize("Asia/Tokyo")
+        exp_idx = exp_idx.tz_localize("Asia/Tokyo")
+
+        arr, idx = idx1.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        idx2 = DatetimeIndex(
+            ["2014-03", "2014-03", "2014-02", "2014-01", "2014-03", "2014-01"]
+        )
+
+        exp_arr = np.array([2, 2, 1, 0, 2, 0], dtype=np.intp)
+        exp_idx = DatetimeIndex(["2014-01", "2014-02", "2014-03"])
+        arr, idx = idx2.factorize(sort=True)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+        exp_arr = np.array([0, 0, 1, 2, 0, 2], dtype=np.intp)
+        exp_idx = DatetimeIndex(["2014-03", "2014-02", "2014-01"])
+        arr, idx = idx2.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+        assert idx.freq == exp_idx.freq
+
+    def test_factorize_preserves_freq(self):
+        # GH#38120 freq should be preserved
+        idx3 = date_range("2000-01", periods=4, freq="ME", tz="Asia/Tokyo")
+        exp_arr = np.array([0, 1, 2, 3], dtype=np.intp)
+
+        arr, idx = idx3.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, idx3)
+        assert idx.freq == idx3.freq
+
+        arr, idx = factorize(idx3)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, idx3)
+        assert idx.freq == idx3.freq
+
+    def test_factorize_tz(self, tz_naive_fixture, index_or_series):
+        tz = tz_naive_fixture
+        # GH#13750
+        base = date_range("2016-11-05", freq="h", periods=100, tz=tz)
+        idx = base.repeat(5)
+
+        exp_arr = np.arange(100, dtype=np.intp).repeat(5)
+
+        obj = index_or_series(idx)
+
+        arr, res = obj.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        expected = base._with_freq(None)
+        tm.assert_index_equal(res, expected)
+        assert res.freq == expected.freq
+
+    def test_factorize_dst(self, index_or_series):
+        # GH#13750
+        idx = date_range("2016-11-06", freq="h", periods=12, tz="US/Eastern")
+        obj = index_or_series(idx)
+
+        arr, res = obj.factorize()
+        tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp))
+        tm.assert_index_equal(res, idx)
+        if index_or_series is Index:
+            assert res.freq == idx.freq
+
+        idx = date_range("2016-06-13", freq="h", periods=12, tz="US/Eastern")
+        obj = index_or_series(idx)
+
+        arr, res = obj.factorize()
+        tm.assert_numpy_array_equal(arr, np.arange(12, dtype=np.intp))
+        tm.assert_index_equal(res, idx)
+        if index_or_series is Index:
+            assert res.freq == idx.freq
+
+    @pytest.mark.parametrize("sort", [True, False])
+    def test_factorize_no_freq_non_nano(self, tz_naive_fixture, sort):
+        # GH#51978 case that does not go through the fastpath based on
+        #  non-None freq
+        tz = tz_naive_fixture
+        idx = date_range("2016-11-06", freq="h", periods=5, tz=tz)[[0, 4, 1, 3, 2]]
+        exp_codes, exp_uniques = idx.factorize(sort=sort)
+
+        res_codes, res_uniques = idx.as_unit("s").factorize(sort=sort)
+
+        tm.assert_numpy_array_equal(res_codes, exp_codes)
+        tm.assert_index_equal(res_uniques, exp_uniques.as_unit("s"))
+
+        res_codes, res_uniques = idx.as_unit("s").to_series().factorize(sort=sort)
+        tm.assert_numpy_array_equal(res_codes, exp_codes)
+        tm.assert_index_equal(res_uniques, exp_uniques.as_unit("s"))

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_fillna.py

@@ -0,0 +1,62 @@
+import pytest
+
+import pandas as pd
+import pandas._testing as tm
+
+
+class TestDatetimeIndexFillNA:
+    @pytest.mark.parametrize("tz", ["US/Eastern", "Asia/Tokyo"])
+    def test_fillna_datetime64(self, tz):
+        # GH 11343
+        idx = pd.DatetimeIndex(["2011-01-01 09:00", pd.NaT, "2011-01-01 11:00"])
+
+        exp = pd.DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"]
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00")), exp)
+
+        # tz mismatch
+        exp = pd.Index(
+            [
+                pd.Timestamp("2011-01-01 09:00"),
+                pd.Timestamp("2011-01-01 10:00", tz=tz),
+                pd.Timestamp("2011-01-01 11:00"),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00", tz=tz)), exp)
+
+        # object
+        exp = pd.Index(
+            [pd.Timestamp("2011-01-01 09:00"), "x", pd.Timestamp("2011-01-01 11:00")],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna("x"), exp)
+
+        idx = pd.DatetimeIndex(["2011-01-01 09:00", pd.NaT, "2011-01-01 11:00"], tz=tz)
+
+        exp = pd.DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"], tz=tz
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00", tz=tz)), exp)
+
+        exp = pd.Index(
+            [
+                pd.Timestamp("2011-01-01 09:00", tz=tz),
+                pd.Timestamp("2011-01-01 10:00"),
+                pd.Timestamp("2011-01-01 11:00", tz=tz),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna(pd.Timestamp("2011-01-01 10:00")), exp)
+
+        # object
+        exp = pd.Index(
+            [
+                pd.Timestamp("2011-01-01 09:00", tz=tz),
+                "x",
+                pd.Timestamp("2011-01-01 11:00", tz=tz),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(idx.fillna("x"), exp)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_insert.py

@@ -0,0 +1,265 @@
+from datetime import datetime
+
+import numpy as np
+import pytest
+import pytz
+
+from pandas import (
+    NA,
+    DatetimeIndex,
+    Index,
+    NaT,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestInsert:
+    @pytest.mark.parametrize("null", [None, np.nan, np.datetime64("NaT"), NaT, NA])
+    @pytest.mark.parametrize("tz", [None, "UTC", "US/Eastern"])
+    def test_insert_nat(self, tz, null):
+        # GH#16537, GH#18295 (test missing)
+
+        idx = DatetimeIndex(["2017-01-01"], tz=tz)
+        expected = DatetimeIndex(["NaT", "2017-01-01"], tz=tz)
+        if tz is not None and isinstance(null, np.datetime64):
+            expected = Index([null, idx[0]], dtype=object)
+
+        res = idx.insert(0, null)
+        tm.assert_index_equal(res, expected)
+
+    @pytest.mark.parametrize("tz", [None, "UTC", "US/Eastern"])
+    def test_insert_invalid_na(self, tz):
+        idx = DatetimeIndex(["2017-01-01"], tz=tz)
+
+        item = np.timedelta64("NaT")
+        result = idx.insert(0, item)
+        expected = Index([item] + list(idx), dtype=object)
+        tm.assert_index_equal(result, expected)
+
+    def test_insert_empty_preserves_freq(self, tz_naive_fixture):
+        # GH#33573
+        tz = tz_naive_fixture
+        dti = DatetimeIndex([], tz=tz, freq="D")
+        item = Timestamp("2017-04-05").tz_localize(tz)
+
+        result = dti.insert(0, item)
+        assert result.freq == dti.freq
+
+        # But not when we insert an item that doesn't conform to freq
+        dti = DatetimeIndex([], tz=tz, freq="W-THU")
+        result = dti.insert(0, item)
+        assert result.freq is None
+
+    def test_insert(self, unit):
+        idx = DatetimeIndex(
+            ["2000-01-04", "2000-01-01", "2000-01-02"], name="idx"
+        ).as_unit(unit)
+
+        result = idx.insert(2, datetime(2000, 1, 5))
+        exp = DatetimeIndex(
+            ["2000-01-04", "2000-01-01", "2000-01-05", "2000-01-02"], name="idx"
+        ).as_unit(unit)
+        tm.assert_index_equal(result, exp)
+
+        # insertion of non-datetime should coerce to object index
+        result = idx.insert(1, "inserted")
+        expected = Index(
+            [
+                datetime(2000, 1, 4),
+                "inserted",
+                datetime(2000, 1, 1),
+                datetime(2000, 1, 2),
+            ],
+            name="idx",
+        )
+        assert not isinstance(result, DatetimeIndex)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+
+    def test_insert2(self, unit):
+        idx = date_range("1/1/2000", periods=3, freq="ME", name="idx", unit=unit)
+
+        # preserve freq
+        expected_0 = DatetimeIndex(
+            ["1999-12-31", "2000-01-31", "2000-02-29", "2000-03-31"],
+            name="idx",
+            freq="ME",
+        ).as_unit(unit)
+        expected_3 = DatetimeIndex(
+            ["2000-01-31", "2000-02-29", "2000-03-31", "2000-04-30"],
+            name="idx",
+            freq="ME",
+        ).as_unit(unit)
+
+        # reset freq to None
+        expected_1_nofreq = DatetimeIndex(
+            ["2000-01-31", "2000-01-31", "2000-02-29", "2000-03-31"],
+            name="idx",
+            freq=None,
+        ).as_unit(unit)
+        expected_3_nofreq = DatetimeIndex(
+            ["2000-01-31", "2000-02-29", "2000-03-31", "2000-01-02"],
+            name="idx",
+            freq=None,
+        ).as_unit(unit)
+
+        cases = [
+            (0, datetime(1999, 12, 31), expected_0),
+            (-3, datetime(1999, 12, 31), expected_0),
+            (3, datetime(2000, 4, 30), expected_3),
+            (1, datetime(2000, 1, 31), expected_1_nofreq),
+            (3, datetime(2000, 1, 2), expected_3_nofreq),
+        ]
+
+        for n, d, expected in cases:
+            result = idx.insert(n, d)
+            tm.assert_index_equal(result, expected)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
+
+    def test_insert3(self, unit):
+        idx = date_range("1/1/2000", periods=3, freq="ME", name="idx", unit=unit)
+
+        # reset freq to None
+        result = idx.insert(3, datetime(2000, 1, 2))
+        expected = DatetimeIndex(
+            ["2000-01-31", "2000-02-29", "2000-03-31", "2000-01-02"],
+            name="idx",
+            freq=None,
+        ).as_unit(unit)
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert result.freq is None
+
+    def test_insert4(self, unit):
+        for tz in ["US/Pacific", "Asia/Singapore"]:
+            idx = date_range(
+                "1/1/2000 09:00", periods=6, freq="h", tz=tz, name="idx", unit=unit
+            )
+            # preserve freq
+            expected = date_range(
+                "1/1/2000 09:00", periods=7, freq="h", tz=tz, name="idx", unit=unit
+            )
+            for d in [
+                Timestamp("2000-01-01 15:00", tz=tz),
+                pytz.timezone(tz).localize(datetime(2000, 1, 1, 15)),
+            ]:
+                result = idx.insert(6, d)
+                tm.assert_index_equal(result, expected)
+                assert result.name == expected.name
+                assert result.freq == expected.freq
+                assert result.tz == expected.tz
+
+            expected = DatetimeIndex(
+                [
+                    "2000-01-01 09:00",
+                    "2000-01-01 10:00",
+                    "2000-01-01 11:00",
+                    "2000-01-01 12:00",
+                    "2000-01-01 13:00",
+                    "2000-01-01 14:00",
+                    "2000-01-01 10:00",
+                ],
+                name="idx",
+                tz=tz,
+                freq=None,
+            ).as_unit(unit)
+            # reset freq to None
+            for d in [
+                Timestamp("2000-01-01 10:00", tz=tz),
+                pytz.timezone(tz).localize(datetime(2000, 1, 1, 10)),
+            ]:
+                result = idx.insert(6, d)
+                tm.assert_index_equal(result, expected)
+                assert result.name == expected.name
+                assert result.tz == expected.tz
+                assert result.freq is None
+
+    # TODO: also changes DataFrame.__setitem__ with expansion
+    def test_insert_mismatched_tzawareness(self):
+        # see GH#7299
+        idx = date_range("1/1/2000", periods=3, freq="D", tz="Asia/Tokyo", name="idx")
+
+        # mismatched tz-awareness
+        item = Timestamp("2000-01-04")
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item] + list(idx[3:]), dtype=object, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        # mismatched tz-awareness
+        item = datetime(2000, 1, 4)
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item] + list(idx[3:]), dtype=object, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+    # TODO: also changes DataFrame.__setitem__ with expansion
+    def test_insert_mismatched_tz(self):
+        # see GH#7299
+        # pre-2.0 with mismatched tzs we would cast to object
+        idx = date_range("1/1/2000", periods=3, freq="D", tz="Asia/Tokyo", name="idx")
+
+        # mismatched tz -> cast to object (could reasonably cast to same tz or UTC)
+        item = Timestamp("2000-01-04", tz="US/Eastern")
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item.tz_convert(idx.tz)] + list(idx[3:]),
+            name="idx",
+        )
+        assert expected.dtype == idx.dtype
+        tm.assert_index_equal(result, expected)
+
+        item = datetime(2000, 1, 4, tzinfo=pytz.timezone("US/Eastern"))
+        result = idx.insert(3, item)
+        expected = Index(
+            list(idx[:3]) + [item.astimezone(idx.tzinfo)] + list(idx[3:]),
+            name="idx",
+        )
+        assert expected.dtype == idx.dtype
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "item", [0, np.int64(0), np.float64(0), np.array(0), np.timedelta64(456)]
+    )
+    def test_insert_mismatched_types_raises(self, tz_aware_fixture, item):
+        # GH#33703 dont cast these to dt64
+        tz = tz_aware_fixture
+        dti = date_range("2019-11-04", periods=9, freq="-1D", name=9, tz=tz)
+
+        result = dti.insert(1, item)
+
+        if isinstance(item, np.ndarray):
+            assert item.item() == 0
+            expected = Index([dti[0], 0] + list(dti[1:]), dtype=object, name=9)
+        else:
+            expected = Index([dti[0], item] + list(dti[1:]), dtype=object, name=9)
+
+        tm.assert_index_equal(result, expected)
+
+    def test_insert_castable_str(self, tz_aware_fixture):
+        # GH#33703
+        tz = tz_aware_fixture
+        dti = date_range("2019-11-04", periods=3, freq="-1D", name=9, tz=tz)
+
+        value = "2019-11-05"
+        result = dti.insert(0, value)
+
+        ts = Timestamp(value).tz_localize(tz)
+        expected = DatetimeIndex([ts] + list(dti), dtype=dti.dtype, name=9)
+        tm.assert_index_equal(result, expected)
+
+    def test_insert_non_castable_str(self, tz_aware_fixture):
+        # GH#33703
+        tz = tz_aware_fixture
+        dti = date_range("2019-11-04", periods=3, freq="-1D", name=9, tz=tz)
+
+        value = "foo"
+        result = dti.insert(0, value)
+
+        expected = Index(["foo"] + list(dti), dtype=object, name=9)
+        tm.assert_index_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_isocalendar.py

@@ -0,0 +1,28 @@
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    date_range,
+)
+import pandas._testing as tm
+
+
+def test_isocalendar_returns_correct_values_close_to_new_year_with_tz():
+    # GH#6538: Check that DatetimeIndex and its TimeStamp elements
+    # return the same weekofyear accessor close to new year w/ tz
+    dates = ["2013/12/29", "2013/12/30", "2013/12/31"]
+    dates = DatetimeIndex(dates, tz="Europe/Brussels")
+    result = dates.isocalendar()
+    expected_data_frame = DataFrame(
+        [[2013, 52, 7], [2014, 1, 1], [2014, 1, 2]],
+        columns=["year", "week", "day"],
+        index=dates,
+        dtype="UInt32",
+    )
+    tm.assert_frame_equal(result, expected_data_frame)
+
+
+def test_dti_timestamp_isocalendar_fields():
+    idx = date_range("2020-01-01", periods=10)
+    expected = tuple(idx.isocalendar().iloc[-1].to_list())
+    result = idx[-1].isocalendar()
+    assert result == expected

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_map.py

@@ -0,0 +1,47 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    MultiIndex,
+    Period,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestMap:
+    def test_map(self):
+        rng = date_range("1/1/2000", periods=10)
+
+        f = lambda x: x.strftime("%Y%m%d")
+        result = rng.map(f)
+        exp = Index([f(x) for x in rng])
+        tm.assert_index_equal(result, exp)
+
+    def test_map_fallthrough(self, capsys):
+        # GH#22067, check we don't get warnings about silently ignored errors
+        dti = date_range("2017-01-01", "2018-01-01", freq="B")
+
+        dti.map(lambda x: Period(year=x.year, month=x.month, freq="M"))
+
+        captured = capsys.readouterr()
+        assert captured.err == ""
+
+    def test_map_bug_1677(self):
+        index = DatetimeIndex(["2012-04-25 09:30:00.393000"])
+        f = index.asof
+
+        result = index.map(f)
+        expected = Index([f(index[0])])
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("name", [None, "name"])
+    def test_index_map(self, name):
+        # see GH#20990
+        count = 6
+        index = date_range("2018-01-01", periods=count, freq="ME", name=name).map(
+            lambda x: (x.year, x.month)
+        )
+        exp_index = MultiIndex.from_product(((2018,), range(1, 7)), names=[name, name])
+        tm.assert_index_equal(index, exp_index)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_normalize.py

@@ -0,0 +1,95 @@
+from dateutil.tz import tzlocal
+import numpy as np
+import pytest
+
+import pandas.util._test_decorators as td
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestNormalize:
+    def test_normalize(self):
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D")
+
+        result = rng.normalize()
+        expected = date_range("1/1/2000", periods=10, freq="D")
+        tm.assert_index_equal(result, expected)
+
+        arr_ns = np.array([1380585623454345752, 1380585612343234312]).astype(
+            "datetime64[ns]"
+        )
+        rng_ns = DatetimeIndex(arr_ns)
+        rng_ns_normalized = rng_ns.normalize()
+
+        arr_ns = np.array([1380585600000000000, 1380585600000000000]).astype(
+            "datetime64[ns]"
+        )
+        expected = DatetimeIndex(arr_ns)
+        tm.assert_index_equal(rng_ns_normalized, expected)
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+    def test_normalize_nat(self):
+        dti = DatetimeIndex([NaT, Timestamp("2018-01-01 01:00:00")])
+        result = dti.normalize()
+        expected = DatetimeIndex([NaT, Timestamp("2018-01-01")])
+        tm.assert_index_equal(result, expected)
+
+    def test_normalize_tz(self):
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz="US/Eastern")
+
+        result = rng.normalize()  # does not preserve freq
+        expected = date_range("1/1/2000", periods=10, freq="D", tz="US/Eastern")
+        tm.assert_index_equal(result, expected._with_freq(None))
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz="UTC")
+
+        result = rng.normalize()
+        expected = date_range("1/1/2000", periods=10, freq="D", tz="UTC")
+        tm.assert_index_equal(result, expected)
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+        rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz=tzlocal())
+        result = rng.normalize()  # does not preserve freq
+        expected = date_range("1/1/2000", periods=10, freq="D", tz=tzlocal())
+        tm.assert_index_equal(result, expected._with_freq(None))
+
+        assert result.is_normalized
+        assert not rng.is_normalized
+
+    @td.skip_if_windows
+    @pytest.mark.parametrize(
+        "timezone",
+        [
+            "US/Pacific",
+            "US/Eastern",
+            "UTC",
+            "Asia/Kolkata",
+            "Asia/Shanghai",
+            "Australia/Canberra",
+        ],
+    )
+    def test_normalize_tz_local(self, timezone):
+        # GH#13459
+        with tm.set_timezone(timezone):
+            rng = date_range("1/1/2000 9:30", periods=10, freq="D", tz=tzlocal())
+
+            result = rng.normalize()
+            expected = date_range("1/1/2000", periods=10, freq="D", tz=tzlocal())
+            expected = expected._with_freq(None)
+            tm.assert_index_equal(result, expected)
+
+            assert result.is_normalized
+            assert not rng.is_normalized

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_repeat.py

@@ -0,0 +1,83 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestRepeat:
+    def test_repeat_range(self, tz_naive_fixture):
+        rng = date_range("1/1/2000", "1/1/2001")
+
+        result = rng.repeat(5)
+        assert result.freq is None
+        assert len(result) == 5 * len(rng)
+
+    def test_repeat_range2(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        index = date_range("2001-01-01", periods=2, freq="D", tz=tz, unit=unit)
+        exp = DatetimeIndex(
+            ["2001-01-01", "2001-01-01", "2001-01-02", "2001-01-02"], tz=tz
+        ).as_unit(unit)
+        for res in [index.repeat(2), np.repeat(index, 2)]:
+            tm.assert_index_equal(res, exp)
+            assert res.freq is None
+
+    def test_repeat_range3(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        index = date_range("2001-01-01", periods=2, freq="2D", tz=tz, unit=unit)
+        exp = DatetimeIndex(
+            ["2001-01-01", "2001-01-01", "2001-01-03", "2001-01-03"], tz=tz
+        ).as_unit(unit)
+        for res in [index.repeat(2), np.repeat(index, 2)]:
+            tm.assert_index_equal(res, exp)
+            assert res.freq is None
+
+    def test_repeat_range4(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        index = DatetimeIndex(["2001-01-01", "NaT", "2003-01-01"], tz=tz).as_unit(unit)
+        exp = DatetimeIndex(
+            [
+                "2001-01-01",
+                "2001-01-01",
+                "2001-01-01",
+                "NaT",
+                "NaT",
+                "NaT",
+                "2003-01-01",
+                "2003-01-01",
+                "2003-01-01",
+            ],
+            tz=tz,
+        ).as_unit(unit)
+        for res in [index.repeat(3), np.repeat(index, 3)]:
+            tm.assert_index_equal(res, exp)
+            assert res.freq is None
+
+    def test_repeat(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        reps = 2
+        msg = "the 'axis' parameter is not supported"
+
+        rng = date_range(start="2016-01-01", periods=2, freq="30Min", tz=tz, unit=unit)
+
+        expected_rng = DatetimeIndex(
+            [
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 00:30:00", tz=tz),
+                Timestamp("2016-01-01 00:30:00", tz=tz),
+            ]
+        ).as_unit(unit)
+
+        res = rng.repeat(reps)
+        tm.assert_index_equal(res, expected_rng)
+        assert res.freq is None
+
+        tm.assert_index_equal(np.repeat(rng, reps), expected_rng)
+        with pytest.raises(ValueError, match=msg):
+            np.repeat(rng, reps, axis=1)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_resolution.py

@@ -0,0 +1,31 @@
+from dateutil.tz import tzlocal
+import pytest
+
+from pandas.compat import IS64
+
+from pandas import date_range
+
+
+@pytest.mark.parametrize(
+    "freq,expected",
+    [
+        ("YE", "day"),
+        ("QE", "day"),
+        ("ME", "day"),
+        ("D", "day"),
+        ("h", "hour"),
+        ("min", "minute"),
+        ("s", "second"),
+        ("ms", "millisecond"),
+        ("us", "microsecond"),
+    ],
+)
+def test_dti_resolution(request, tz_naive_fixture, freq, expected):
+    tz = tz_naive_fixture
+    if freq == "YE" and not IS64 and isinstance(tz, tzlocal):
+        request.applymarker(
+            pytest.mark.xfail(reason="OverflowError inside tzlocal past 2038")
+        )
+
+    idx = date_range(start="2013-04-01", periods=30, freq=freq, tz=tz)
+    assert idx.resolution == expected

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_round.py

@@ -0,0 +1,221 @@
+import pytest
+
+from pandas._libs.tslibs import to_offset
+from pandas._libs.tslibs.offsets import INVALID_FREQ_ERR_MSG
+
+from pandas import (
+    DatetimeIndex,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndexRound:
+    def test_round_daily(self):
+        dti = date_range("20130101 09:10:11", periods=5)
+        result = dti.round("D")
+        expected = date_range("20130101", periods=5)
+        tm.assert_index_equal(result, expected)
+
+        dti = dti.tz_localize("UTC").tz_convert("US/Eastern")
+        result = dti.round("D")
+        expected = date_range("20130101", periods=5).tz_localize("US/Eastern")
+        tm.assert_index_equal(result, expected)
+
+        result = dti.round("s")
+        tm.assert_index_equal(result, dti)
+
+    @pytest.mark.parametrize(
+        "freq, error_msg",
+        [
+            ("YE", "<YearEnd: month=12> is a non-fixed frequency"),
+            ("ME", "<MonthEnd> is a non-fixed frequency"),
+            ("foobar", "Invalid frequency: foobar"),
+        ],
+    )
+    def test_round_invalid(self, freq, error_msg):
+        dti = date_range("20130101 09:10:11", periods=5)
+        dti = dti.tz_localize("UTC").tz_convert("US/Eastern")
+        with pytest.raises(ValueError, match=error_msg):
+            dti.round(freq)
+
+    def test_round(self, tz_naive_fixture, unit):
+        tz = tz_naive_fixture
+        rng = date_range(start="2016-01-01", periods=5, freq="30Min", tz=tz, unit=unit)
+        elt = rng[1]
+
+        expected_rng = DatetimeIndex(
+            [
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 01:00:00", tz=tz),
+                Timestamp("2016-01-01 02:00:00", tz=tz),
+                Timestamp("2016-01-01 02:00:00", tz=tz),
+            ]
+        ).as_unit(unit)
+        expected_elt = expected_rng[1]
+
+        result = rng.round(freq="h")
+        tm.assert_index_equal(result, expected_rng)
+        assert elt.round(freq="h") == expected_elt
+
+        msg = INVALID_FREQ_ERR_MSG
+        with pytest.raises(ValueError, match=msg):
+            rng.round(freq="foo")
+        with pytest.raises(ValueError, match=msg):
+            elt.round(freq="foo")
+
+        msg = "<MonthEnd> is a non-fixed frequency"
+        with pytest.raises(ValueError, match=msg):
+            rng.round(freq="ME")
+        with pytest.raises(ValueError, match=msg):
+            elt.round(freq="ME")
+
+    def test_round2(self, tz_naive_fixture):
+        tz = tz_naive_fixture
+        # GH#14440 & GH#15578
+        index = DatetimeIndex(["2016-10-17 12:00:00.0015"], tz=tz).as_unit("ns")
+        result = index.round("ms")
+        expected = DatetimeIndex(["2016-10-17 12:00:00.002000"], tz=tz).as_unit("ns")
+        tm.assert_index_equal(result, expected)
+
+        for freq in ["us", "ns"]:
+            tm.assert_index_equal(index, index.round(freq))
+
+    def test_round3(self, tz_naive_fixture):
+        tz = tz_naive_fixture
+        index = DatetimeIndex(["2016-10-17 12:00:00.00149"], tz=tz).as_unit("ns")
+        result = index.round("ms")
+        expected = DatetimeIndex(["2016-10-17 12:00:00.001000"], tz=tz).as_unit("ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_round4(self, tz_naive_fixture):
+        index = DatetimeIndex(["2016-10-17 12:00:00.001501031"], dtype="M8[ns]")
+        result = index.round("10ns")
+        expected = DatetimeIndex(["2016-10-17 12:00:00.001501030"], dtype="M8[ns]")
+        tm.assert_index_equal(result, expected)
+
+        ts = "2016-10-17 12:00:00.001501031"
+        dti = DatetimeIndex([ts], dtype="M8[ns]")
+        with tm.assert_produces_warning(False):
+            dti.round("1010ns")
+
+    def test_no_rounding_occurs(self, tz_naive_fixture):
+        # GH 21262
+        tz = tz_naive_fixture
+        rng = date_range(start="2016-01-01", periods=5, freq="2Min", tz=tz)
+
+        expected_rng = DatetimeIndex(
+            [
+                Timestamp("2016-01-01 00:00:00", tz=tz),
+                Timestamp("2016-01-01 00:02:00", tz=tz),
+                Timestamp("2016-01-01 00:04:00", tz=tz),
+                Timestamp("2016-01-01 00:06:00", tz=tz),
+                Timestamp("2016-01-01 00:08:00", tz=tz),
+            ]
+        ).as_unit("ns")
+
+        result = rng.round(freq="2min")
+        tm.assert_index_equal(result, expected_rng)
+
+    @pytest.mark.parametrize(
+        "test_input, rounder, freq, expected",
+        [
+            (["2117-01-01 00:00:45"], "floor", "15s", ["2117-01-01 00:00:45"]),
+            (["2117-01-01 00:00:45"], "ceil", "15s", ["2117-01-01 00:00:45"]),
+            (
+                ["2117-01-01 00:00:45.000000012"],
+                "floor",
+                "10ns",
+                ["2117-01-01 00:00:45.000000010"],
+            ),
+            (
+                ["1823-01-01 00:00:01.000000012"],
+                "ceil",
+                "10ns",
+                ["1823-01-01 00:00:01.000000020"],
+            ),
+            (["1823-01-01 00:00:01"], "floor", "1s", ["1823-01-01 00:00:01"]),
+            (["1823-01-01 00:00:01"], "ceil", "1s", ["1823-01-01 00:00:01"]),
+            (["2018-01-01 00:15:00"], "ceil", "15min", ["2018-01-01 00:15:00"]),
+            (["2018-01-01 00:15:00"], "floor", "15min", ["2018-01-01 00:15:00"]),
+            (["1823-01-01 03:00:00"], "ceil", "3h", ["1823-01-01 03:00:00"]),
+            (["1823-01-01 03:00:00"], "floor", "3h", ["1823-01-01 03:00:00"]),
+            (
+                ("NaT", "1823-01-01 00:00:01"),
+                "floor",
+                "1s",
+                ("NaT", "1823-01-01 00:00:01"),
+            ),
+            (
+                ("NaT", "1823-01-01 00:00:01"),
+                "ceil",
+                "1s",
+                ("NaT", "1823-01-01 00:00:01"),
+            ),
+        ],
+    )
+    def test_ceil_floor_edge(self, test_input, rounder, freq, expected):
+        dt = DatetimeIndex(list(test_input))
+        func = getattr(dt, rounder)
+        result = func(freq)
+        expected = DatetimeIndex(list(expected))
+        assert expected.equals(result)
+
+    @pytest.mark.parametrize(
+        "start, index_freq, periods",
+        [("2018-01-01", "12h", 25), ("2018-01-01 0:0:0.124999", "1ns", 1000)],
+    )
+    @pytest.mark.parametrize(
+        "round_freq",
+        [
+            "2ns",
+            "3ns",
+            "4ns",
+            "5ns",
+            "6ns",
+            "7ns",
+            "250ns",
+            "500ns",
+            "750ns",
+            "1us",
+            "19us",
+            "250us",
+            "500us",
+            "750us",
+            "1s",
+            "2s",
+            "3s",
+            "12h",
+            "1D",
+        ],
+    )
+    def test_round_int64(self, start, index_freq, periods, round_freq):
+        dt = date_range(start=start, freq=index_freq, periods=periods)
+        unit = to_offset(round_freq).nanos
+
+        # test floor
+        result = dt.floor(round_freq)
+        diff = dt.asi8 - result.asi8
+        mod = result.asi8 % unit
+        assert (mod == 0).all(), f"floor not a {round_freq} multiple"
+        assert (0 <= diff).all() and (diff < unit).all(), "floor error"
+
+        # test ceil
+        result = dt.ceil(round_freq)
+        diff = result.asi8 - dt.asi8
+        mod = result.asi8 % unit
+        assert (mod == 0).all(), f"ceil not a {round_freq} multiple"
+        assert (0 <= diff).all() and (diff < unit).all(), "ceil error"
+
+        # test round
+        result = dt.round(round_freq)
+        diff = abs(result.asi8 - dt.asi8)
+        mod = result.asi8 % unit
+        assert (mod == 0).all(), f"round not a {round_freq} multiple"
+        assert (diff <= unit // 2).all(), "round error"
+        if unit % 2 == 0:
+            assert (
+                result.asi8[diff == unit // 2] % 2 == 0
+            ).all(), "round half to even error"

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_shift.py

@@ -0,0 +1,169 @@
+from datetime import datetime
+
+import pytest
+import pytz
+
+from pandas.errors import NullFrequencyError
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    Series,
+    date_range,
+)
+import pandas._testing as tm
+
+START, END = datetime(2009, 1, 1), datetime(2010, 1, 1)
+
+
+class TestDatetimeIndexShift:
+    # -------------------------------------------------------------
+    # DatetimeIndex.shift is used in integer addition
+
+    def test_dti_shift_tzaware(self, tz_naive_fixture, unit):
+        # GH#9903
+        tz = tz_naive_fixture
+        idx = DatetimeIndex([], name="xxx", tz=tz).as_unit(unit)
+        tm.assert_index_equal(idx.shift(0, freq="h"), idx)
+        tm.assert_index_equal(idx.shift(3, freq="h"), idx)
+
+        idx = DatetimeIndex(
+            ["2011-01-01 10:00", "2011-01-01 11:00", "2011-01-01 12:00"],
+            name="xxx",
+            tz=tz,
+            freq="h",
+        ).as_unit(unit)
+        tm.assert_index_equal(idx.shift(0, freq="h"), idx)
+        exp = DatetimeIndex(
+            ["2011-01-01 13:00", "2011-01-01 14:00", "2011-01-01 15:00"],
+            name="xxx",
+            tz=tz,
+            freq="h",
+        ).as_unit(unit)
+        tm.assert_index_equal(idx.shift(3, freq="h"), exp)
+        exp = DatetimeIndex(
+            ["2011-01-01 07:00", "2011-01-01 08:00", "2011-01-01 09:00"],
+            name="xxx",
+            tz=tz,
+            freq="h",
+        ).as_unit(unit)
+        tm.assert_index_equal(idx.shift(-3, freq="h"), exp)
+
+    def test_dti_shift_freqs(self, unit):
+        # test shift for DatetimeIndex and non DatetimeIndex
+        # GH#8083
+        drange = date_range("20130101", periods=5, unit=unit)
+        result = drange.shift(1)
+        expected = DatetimeIndex(
+            ["2013-01-02", "2013-01-03", "2013-01-04", "2013-01-05", "2013-01-06"],
+            dtype=f"M8[{unit}]",
+            freq="D",
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = drange.shift(-1)
+        expected = DatetimeIndex(
+            ["2012-12-31", "2013-01-01", "2013-01-02", "2013-01-03", "2013-01-04"],
+            dtype=f"M8[{unit}]",
+            freq="D",
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = drange.shift(3, freq="2D")
+        expected = DatetimeIndex(
+            ["2013-01-07", "2013-01-08", "2013-01-09", "2013-01-10", "2013-01-11"],
+            dtype=f"M8[{unit}]",
+            freq="D",
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_dti_shift_int(self, unit):
+        rng = date_range("1/1/2000", periods=20, unit=unit)
+
+        result = rng + 5 * rng.freq
+        expected = rng.shift(5)
+        tm.assert_index_equal(result, expected)
+
+        result = rng - 5 * rng.freq
+        expected = rng.shift(-5)
+        tm.assert_index_equal(result, expected)
+
+    def test_dti_shift_no_freq(self, unit):
+        # GH#19147
+        dti = DatetimeIndex(["2011-01-01 10:00", "2011-01-01"], freq=None).as_unit(unit)
+        with pytest.raises(NullFrequencyError, match="Cannot shift with no freq"):
+            dti.shift(2)
+
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_shift_localized(self, tzstr, unit):
+        dr = date_range("2011/1/1", "2012/1/1", freq="W-FRI", unit=unit)
+        dr_tz = dr.tz_localize(tzstr)
+
+        result = dr_tz.shift(1, "10min")
+        assert result.tz == dr_tz.tz
+
+    def test_dti_shift_across_dst(self, unit):
+        # GH 8616
+        idx = date_range(
+            "2013-11-03", tz="America/Chicago", periods=7, freq="h", unit=unit
+        )
+        ser = Series(index=idx[:-1], dtype=object)
+        result = ser.shift(freq="h")
+        expected = Series(index=idx[1:], dtype=object)
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "shift, result_time",
+        [
+            [0, "2014-11-14 00:00:00"],
+            [-1, "2014-11-13 23:00:00"],
+            [1, "2014-11-14 01:00:00"],
+        ],
+    )
+    def test_dti_shift_near_midnight(self, shift, result_time, unit):
+        # GH 8616
+        dt = datetime(2014, 11, 14, 0)
+        dt_est = pytz.timezone("EST").localize(dt)
+        idx = DatetimeIndex([dt_est]).as_unit(unit)
+        ser = Series(data=[1], index=idx)
+        result = ser.shift(shift, freq="h")
+        exp_index = DatetimeIndex([result_time], tz="EST").as_unit(unit)
+        expected = Series(1, index=exp_index)
+        tm.assert_series_equal(result, expected)
+
+    def test_shift_periods(self, unit):
+        # GH#22458 : argument 'n' was deprecated in favor of 'periods'
+        idx = date_range(start=START, end=END, periods=3, unit=unit)
+        tm.assert_index_equal(idx.shift(periods=0), idx)
+        tm.assert_index_equal(idx.shift(0), idx)
+
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_shift_bday(self, freq, unit):
+        rng = date_range(START, END, freq=freq, unit=unit)
+        shifted = rng.shift(5)
+        assert shifted[0] == rng[5]
+        assert shifted.freq == rng.freq
+
+        shifted = rng.shift(-5)
+        assert shifted[5] == rng[0]
+        assert shifted.freq == rng.freq
+
+        shifted = rng.shift(0)
+        assert shifted[0] == rng[0]
+        assert shifted.freq == rng.freq
+
+    def test_shift_bmonth(self, unit):
+        rng = date_range(START, END, freq=pd.offsets.BMonthEnd(), unit=unit)
+        shifted = rng.shift(1, freq=pd.offsets.BDay())
+        assert shifted[0] == rng[0] + pd.offsets.BDay()
+
+        rng = date_range(START, END, freq=pd.offsets.BMonthEnd(), unit=unit)
+        with tm.assert_produces_warning(pd.errors.PerformanceWarning):
+            shifted = rng.shift(1, freq=pd.offsets.CDay())
+            assert shifted[0] == rng[0] + pd.offsets.CDay()
+
+    def test_shift_empty(self, unit):
+        # GH#14811
+        dti = date_range(start="2016-10-21", end="2016-10-21", freq="BME", unit=unit)
+        result = dti.shift(1)
+        tm.assert_index_equal(result, dti)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_snap.py

@@ -0,0 +1,47 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    date_range,
+)
+import pandas._testing as tm
+
+
+@pytest.mark.parametrize("tz", [None, "Asia/Shanghai", "Europe/Berlin"])
+@pytest.mark.parametrize("name", [None, "my_dti"])
+@pytest.mark.parametrize("unit", ["ns", "us", "ms", "s"])
+def test_dti_snap(name, tz, unit):
+    dti = DatetimeIndex(
+        [
+            "1/1/2002",
+            "1/2/2002",
+            "1/3/2002",
+            "1/4/2002",
+            "1/5/2002",
+            "1/6/2002",
+            "1/7/2002",
+        ],
+        name=name,
+        tz=tz,
+        freq="D",
+    )
+    dti = dti.as_unit(unit)
+
+    result = dti.snap(freq="W-MON")
+    expected = date_range("12/31/2001", "1/7/2002", name=name, tz=tz, freq="w-mon")
+    expected = expected.repeat([3, 4])
+    expected = expected.as_unit(unit)
+    tm.assert_index_equal(result, expected)
+    assert result.tz == expected.tz
+    assert result.freq is None
+    assert expected.freq is None
+
+    result = dti.snap(freq="B")
+
+    expected = date_range("1/1/2002", "1/7/2002", name=name, tz=tz, freq="b")
+    expected = expected.repeat([1, 1, 1, 2, 2])
+    expected = expected.as_unit(unit)
+    tm.assert_index_equal(result, expected)
+    assert result.tz == expected.tz
+    assert result.freq is None
+    assert expected.freq is None

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_to_frame.py

@@ -0,0 +1,28 @@
+from pandas import (
+    DataFrame,
+    Index,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestToFrame:
+    def test_to_frame_datetime_tz(self):
+        # GH#25809
+        idx = date_range(start="2019-01-01", end="2019-01-30", freq="D", tz="UTC")
+        result = idx.to_frame()
+        expected = DataFrame(idx, index=idx)
+        tm.assert_frame_equal(result, expected)
+
+    def test_to_frame_respects_none_name(self):
+        # GH#44212 if we explicitly pass name=None, then that should be respected,
+        #  not changed to 0
+        # GH-45448 this is first deprecated to only change in the future
+        idx = date_range(start="2019-01-01", end="2019-01-30", freq="D", tz="UTC")
+        result = idx.to_frame(name=None)
+        exp_idx = Index([None], dtype=object)
+        tm.assert_index_equal(exp_idx, result.columns)
+
+        result = idx.rename("foo").to_frame(name=None)
+        exp_idx = Index([None], dtype=object)
+        tm.assert_index_equal(exp_idx, result.columns)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_to_julian_date.py

@@ -0,0 +1,45 @@
+import numpy as np
+
+from pandas import (
+    Index,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDateTimeIndexToJulianDate:
+    def test_1700(self):
+        dr = date_range(start=Timestamp("1710-10-01"), periods=5, freq="D")
+        r1 = Index([x.to_julian_date() for x in dr])
+        r2 = dr.to_julian_date()
+        assert isinstance(r2, Index) and r2.dtype == np.float64
+        tm.assert_index_equal(r1, r2)
+
+    def test_2000(self):
+        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="D")
+        r1 = Index([x.to_julian_date() for x in dr])
+        r2 = dr.to_julian_date()
+        assert isinstance(r2, Index) and r2.dtype == np.float64
+        tm.assert_index_equal(r1, r2)
+
+    def test_hour(self):
+        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="h")
+        r1 = Index([x.to_julian_date() for x in dr])
+        r2 = dr.to_julian_date()
+        assert isinstance(r2, Index) and r2.dtype == np.float64
+        tm.assert_index_equal(r1, r2)
+
+    def test_minute(self):
+        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="min")
+        r1 = Index([x.to_julian_date() for x in dr])
+        r2 = dr.to_julian_date()
+        assert isinstance(r2, Index) and r2.dtype == np.float64
+        tm.assert_index_equal(r1, r2)
+
+    def test_second(self):
+        dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="s")
+        r1 = Index([x.to_julian_date() for x in dr])
+        r2 = dr.to_julian_date()
+        assert isinstance(r2, Index) and r2.dtype == np.float64
+        tm.assert_index_equal(r1, r2)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_to_period.py

@@ -0,0 +1,225 @@
+import dateutil.tz
+from dateutil.tz import tzlocal
+import pytest
+import pytz
+
+from pandas._libs.tslibs.ccalendar import MONTHS
+from pandas._libs.tslibs.offsets import MonthEnd
+from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG
+
+from pandas import (
+    DatetimeIndex,
+    Period,
+    PeriodIndex,
+    Timestamp,
+    date_range,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestToPeriod:
+    def test_dti_to_period(self):
+        dti = date_range(start="1/1/2005", end="12/1/2005", freq="ME")
+        pi1 = dti.to_period()
+        pi2 = dti.to_period(freq="D")
+        pi3 = dti.to_period(freq="3D")
+
+        assert pi1[0] == Period("Jan 2005", freq="M")
+        assert pi2[0] == Period("1/31/2005", freq="D")
+        assert pi3[0] == Period("1/31/2005", freq="3D")
+
+        assert pi1[-1] == Period("Nov 2005", freq="M")
+        assert pi2[-1] == Period("11/30/2005", freq="D")
+        assert pi3[-1], Period("11/30/2005", freq="3D")
+
+        tm.assert_index_equal(pi1, period_range("1/1/2005", "11/1/2005", freq="M"))
+        tm.assert_index_equal(
+            pi2, period_range("1/1/2005", "11/1/2005", freq="M").asfreq("D")
+        )
+        tm.assert_index_equal(
+            pi3, period_range("1/1/2005", "11/1/2005", freq="M").asfreq("3D")
+        )
+
+    @pytest.mark.parametrize("month", MONTHS)
+    def test_to_period_quarterly(self, month):
+        # make sure we can make the round trip
+        freq = f"Q-{month}"
+        rng = period_range("1989Q3", "1991Q3", freq=freq)
+        stamps = rng.to_timestamp()
+        result = stamps.to_period(freq)
+        tm.assert_index_equal(rng, result)
+
+    @pytest.mark.parametrize("off", ["BQE", "QS", "BQS"])
+    def test_to_period_quarterlyish(self, off):
+        rng = date_range("01-Jan-2012", periods=8, freq=off)
+        prng = rng.to_period()
+        assert prng.freq == "QE-DEC"
+
+    @pytest.mark.parametrize("off", ["BYE", "YS", "BYS"])
+    def test_to_period_annualish(self, off):
+        rng = date_range("01-Jan-2012", periods=8, freq=off)
+        prng = rng.to_period()
+        assert prng.freq == "YE-DEC"
+
+    def test_to_period_monthish(self):
+        offsets = ["MS", "BME"]
+        for off in offsets:
+            rng = date_range("01-Jan-2012", periods=8, freq=off)
+            prng = rng.to_period()
+            assert prng.freqstr == "M"
+
+        rng = date_range("01-Jan-2012", periods=8, freq="ME")
+        prng = rng.to_period()
+        assert prng.freqstr == "M"
+
+        with pytest.raises(ValueError, match=INVALID_FREQ_ERR_MSG):
+            date_range("01-Jan-2012", periods=8, freq="EOM")
+
+    @pytest.mark.parametrize(
+        "freq_offset, freq_period",
+        [
+            ("2ME", "2M"),
+            (MonthEnd(2), MonthEnd(2)),
+        ],
+    )
+    def test_dti_to_period_2monthish(self, freq_offset, freq_period):
+        dti = date_range("2020-01-01", periods=3, freq=freq_offset)
+        pi = dti.to_period()
+
+        tm.assert_index_equal(pi, period_range("2020-01", "2020-05", freq=freq_period))
+
+    @pytest.mark.parametrize(
+        "freq, freq_depr",
+        [
+            ("2ME", "2M"),
+            ("2QE", "2Q"),
+            ("2QE-SEP", "2Q-SEP"),
+            ("1YE", "1Y"),
+            ("2YE-MAR", "2Y-MAR"),
+            ("1YE", "1A"),
+            ("2YE-MAR", "2A-MAR"),
+        ],
+    )
+    def test_to_period_frequency_M_Q_Y_A_deprecated(self, freq, freq_depr):
+        # GH#9586
+        msg = f"'{freq_depr[1:]}' is deprecated and will be removed "
+        f"in a future version, please use '{freq[1:]}' instead."
+
+        rng = date_range("01-Jan-2012", periods=8, freq=freq)
+        prng = rng.to_period()
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert prng.freq == freq_depr
+
+    def test_to_period_infer(self):
+        # https://github.com/pandas-dev/pandas/issues/33358
+        rng = date_range(
+            start="2019-12-22 06:40:00+00:00",
+            end="2019-12-22 08:45:00+00:00",
+            freq="5min",
+        )
+
+        with tm.assert_produces_warning(UserWarning):
+            pi1 = rng.to_period("5min")
+
+        with tm.assert_produces_warning(UserWarning):
+            pi2 = rng.to_period()
+
+        tm.assert_index_equal(pi1, pi2)
+
+    @pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
+    def test_period_dt64_round_trip(self):
+        dti = date_range("1/1/2000", "1/7/2002", freq="B")
+        pi = dti.to_period()
+        tm.assert_index_equal(pi.to_timestamp(), dti)
+
+        dti = date_range("1/1/2000", "1/7/2002", freq="B")
+        pi = dti.to_period(freq="h")
+        tm.assert_index_equal(pi.to_timestamp(), dti)
+
+    def test_to_period_millisecond(self):
+        index = DatetimeIndex(
+            [
+                Timestamp("2007-01-01 10:11:12.123456Z"),
+                Timestamp("2007-01-01 10:11:13.789123Z"),
+            ]
+        )
+
+        with tm.assert_produces_warning(UserWarning):
+            # warning that timezone info will be lost
+            period = index.to_period(freq="ms")
+        assert 2 == len(period)
+        assert period[0] == Period("2007-01-01 10:11:12.123Z", "ms")
+        assert period[1] == Period("2007-01-01 10:11:13.789Z", "ms")
+
+    def test_to_period_microsecond(self):
+        index = DatetimeIndex(
+            [
+                Timestamp("2007-01-01 10:11:12.123456Z"),
+                Timestamp("2007-01-01 10:11:13.789123Z"),
+            ]
+        )
+
+        with tm.assert_produces_warning(UserWarning):
+            # warning that timezone info will be lost
+            period = index.to_period(freq="us")
+        assert 2 == len(period)
+        assert period[0] == Period("2007-01-01 10:11:12.123456Z", "us")
+        assert period[1] == Period("2007-01-01 10:11:13.789123Z", "us")
+
+    @pytest.mark.parametrize(
+        "tz",
+        ["US/Eastern", pytz.utc, tzlocal(), "dateutil/US/Eastern", dateutil.tz.tzutc()],
+    )
+    def test_to_period_tz(self, tz):
+        ts = date_range("1/1/2000", "2/1/2000", tz=tz)
+
+        with tm.assert_produces_warning(UserWarning):
+            # GH#21333 warning that timezone info will be lost
+            # filter warning about freq deprecation
+
+            result = ts.to_period()[0]
+            expected = ts[0].to_period(ts.freq)
+
+        assert result == expected
+
+        expected = date_range("1/1/2000", "2/1/2000").to_period()
+
+        with tm.assert_produces_warning(UserWarning):
+            # GH#21333 warning that timezone info will be lost
+            result = ts.to_period(ts.freq)
+
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("tz", ["Etc/GMT-1", "Etc/GMT+1"])
+    def test_to_period_tz_utc_offset_consistency(self, tz):
+        # GH#22905
+        ts = date_range("1/1/2000", "2/1/2000", tz="Etc/GMT-1")
+        with tm.assert_produces_warning(UserWarning):
+            result = ts.to_period()[0]
+            expected = ts[0].to_period(ts.freq)
+            assert result == expected
+
+    def test_to_period_nofreq(self):
+        idx = DatetimeIndex(["2000-01-01", "2000-01-02", "2000-01-04"])
+        msg = "You must pass a freq argument as current index has none."
+        with pytest.raises(ValueError, match=msg):
+            idx.to_period()
+
+        idx = DatetimeIndex(["2000-01-01", "2000-01-02", "2000-01-03"], freq="infer")
+        assert idx.freqstr == "D"
+        expected = PeriodIndex(["2000-01-01", "2000-01-02", "2000-01-03"], freq="D")
+        tm.assert_index_equal(idx.to_period(), expected)
+
+        # GH#7606
+        idx = DatetimeIndex(["2000-01-01", "2000-01-02", "2000-01-03"])
+        assert idx.freqstr is None
+        tm.assert_index_equal(idx.to_period(), expected)
+
+    @pytest.mark.parametrize("freq", ["2BMS", "1SME-15"])
+    def test_to_period_offsets_not_supported(self, freq):
+        # GH#56243
+        msg = f"{freq[1:]} is not supported as period frequency"
+        ts = date_range("1/1/2012", periods=4, freq=freq)
+        with pytest.raises(ValueError, match=msg):
+            ts.to_period()

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_to_pydatetime.py

@@ -0,0 +1,51 @@
+from datetime import (
+    datetime,
+    timezone,
+)
+
+import dateutil.parser
+import dateutil.tz
+from dateutil.tz import tzlocal
+import numpy as np
+
+from pandas import (
+    DatetimeIndex,
+    date_range,
+    to_datetime,
+)
+import pandas._testing as tm
+from pandas.tests.indexes.datetimes.test_timezones import FixedOffset
+
+fixed_off = FixedOffset(-420, "-07:00")
+
+
+class TestToPyDatetime:
+    def test_dti_to_pydatetime(self):
+        dt = dateutil.parser.parse("2012-06-13T01:39:00Z")
+        dt = dt.replace(tzinfo=tzlocal())
+
+        arr = np.array([dt], dtype=object)
+
+        result = to_datetime(arr, utc=True)
+        assert result.tz is timezone.utc
+
+        rng = date_range("2012-11-03 03:00", "2012-11-05 03:00", tz=tzlocal())
+        arr = rng.to_pydatetime()
+        result = to_datetime(arr, utc=True)
+        assert result.tz is timezone.utc
+
+    def test_dti_to_pydatetime_fizedtz(self):
+        dates = np.array(
+            [
+                datetime(2000, 1, 1, tzinfo=fixed_off),
+                datetime(2000, 1, 2, tzinfo=fixed_off),
+                datetime(2000, 1, 3, tzinfo=fixed_off),
+            ]
+        )
+        dti = DatetimeIndex(dates)
+
+        result = dti.to_pydatetime()
+        tm.assert_numpy_array_equal(dates, result)
+
+        result = dti._mpl_repr()
+        tm.assert_numpy_array_equal(dates, result)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_to_series.py

@@ -0,0 +1,18 @@
+import numpy as np
+
+from pandas import (
+    DatetimeIndex,
+    Series,
+)
+import pandas._testing as tm
+
+
+class TestToSeries:
+    def test_to_series(self):
+        naive = DatetimeIndex(["2013-1-1 13:00", "2013-1-2 14:00"], name="B")
+        idx = naive.tz_localize("US/Pacific")
+
+        expected = Series(np.array(idx.tolist(), dtype="object"), name="B")
+        result = idx.to_series(index=[0, 1])
+        assert expected.dtype == idx.dtype
+        tm.assert_series_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_tz_convert.py

@@ -0,0 +1,283 @@
+from datetime import datetime
+
+import dateutil.tz
+from dateutil.tz import gettz
+import numpy as np
+import pytest
+import pytz
+
+from pandas._libs.tslibs import timezones
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    NaT,
+    Timestamp,
+    date_range,
+    offsets,
+)
+import pandas._testing as tm
+
+
+class TestTZConvert:
+    def test_tz_convert_nat(self):
+        # GH#5546
+        dates = [NaT]
+        idx = DatetimeIndex(dates)
+        idx = idx.tz_localize("US/Pacific")
+        tm.assert_index_equal(idx, DatetimeIndex(dates, tz="US/Pacific"))
+        idx = idx.tz_convert("US/Eastern")
+        tm.assert_index_equal(idx, DatetimeIndex(dates, tz="US/Eastern"))
+        idx = idx.tz_convert("UTC")
+        tm.assert_index_equal(idx, DatetimeIndex(dates, tz="UTC"))
+
+        dates = ["2010-12-01 00:00", "2010-12-02 00:00", NaT]
+        idx = DatetimeIndex(dates)
+        idx = idx.tz_localize("US/Pacific")
+        tm.assert_index_equal(idx, DatetimeIndex(dates, tz="US/Pacific"))
+        idx = idx.tz_convert("US/Eastern")
+        expected = ["2010-12-01 03:00", "2010-12-02 03:00", NaT]
+        tm.assert_index_equal(idx, DatetimeIndex(expected, tz="US/Eastern"))
+
+        idx = idx + offsets.Hour(5)
+        expected = ["2010-12-01 08:00", "2010-12-02 08:00", NaT]
+        tm.assert_index_equal(idx, DatetimeIndex(expected, tz="US/Eastern"))
+        idx = idx.tz_convert("US/Pacific")
+        expected = ["2010-12-01 05:00", "2010-12-02 05:00", NaT]
+        tm.assert_index_equal(idx, DatetimeIndex(expected, tz="US/Pacific"))
+
+        idx = idx + np.timedelta64(3, "h")
+        expected = ["2010-12-01 08:00", "2010-12-02 08:00", NaT]
+        tm.assert_index_equal(idx, DatetimeIndex(expected, tz="US/Pacific"))
+
+        idx = idx.tz_convert("US/Eastern")
+        expected = ["2010-12-01 11:00", "2010-12-02 11:00", NaT]
+        tm.assert_index_equal(idx, DatetimeIndex(expected, tz="US/Eastern"))
+
+    @pytest.mark.parametrize("prefix", ["", "dateutil/"])
+    def test_dti_tz_convert_compat_timestamp(self, prefix):
+        strdates = ["1/1/2012", "3/1/2012", "4/1/2012"]
+        idx = DatetimeIndex(strdates, tz=prefix + "US/Eastern")
+
+        conv = idx[0].tz_convert(prefix + "US/Pacific")
+        expected = idx.tz_convert(prefix + "US/Pacific")[0]
+
+        assert conv == expected
+
+    def test_dti_tz_convert_hour_overflow_dst(self):
+        # Regression test for GH#13306
+
+        # sorted case US/Eastern -> UTC
+        ts = ["2008-05-12 09:50:00", "2008-12-12 09:50:35", "2009-05-12 09:50:32"]
+        tt = DatetimeIndex(ts).tz_localize("US/Eastern")
+        ut = tt.tz_convert("UTC")
+        expected = Index([13, 14, 13], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+        # sorted case UTC -> US/Eastern
+        ts = ["2008-05-12 13:50:00", "2008-12-12 14:50:35", "2009-05-12 13:50:32"]
+        tt = DatetimeIndex(ts).tz_localize("UTC")
+        ut = tt.tz_convert("US/Eastern")
+        expected = Index([9, 9, 9], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+        # unsorted case US/Eastern -> UTC
+        ts = ["2008-05-12 09:50:00", "2008-12-12 09:50:35", "2008-05-12 09:50:32"]
+        tt = DatetimeIndex(ts).tz_localize("US/Eastern")
+        ut = tt.tz_convert("UTC")
+        expected = Index([13, 14, 13], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+        # unsorted case UTC -> US/Eastern
+        ts = ["2008-05-12 13:50:00", "2008-12-12 14:50:35", "2008-05-12 13:50:32"]
+        tt = DatetimeIndex(ts).tz_localize("UTC")
+        ut = tt.tz_convert("US/Eastern")
+        expected = Index([9, 9, 9], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+    @pytest.mark.parametrize("tz", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_tz_convert_hour_overflow_dst_timestamps(self, tz):
+        # Regression test for GH#13306
+
+        # sorted case US/Eastern -> UTC
+        ts = [
+            Timestamp("2008-05-12 09:50:00", tz=tz),
+            Timestamp("2008-12-12 09:50:35", tz=tz),
+            Timestamp("2009-05-12 09:50:32", tz=tz),
+        ]
+        tt = DatetimeIndex(ts)
+        ut = tt.tz_convert("UTC")
+        expected = Index([13, 14, 13], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+        # sorted case UTC -> US/Eastern
+        ts = [
+            Timestamp("2008-05-12 13:50:00", tz="UTC"),
+            Timestamp("2008-12-12 14:50:35", tz="UTC"),
+            Timestamp("2009-05-12 13:50:32", tz="UTC"),
+        ]
+        tt = DatetimeIndex(ts)
+        ut = tt.tz_convert("US/Eastern")
+        expected = Index([9, 9, 9], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+        # unsorted case US/Eastern -> UTC
+        ts = [
+            Timestamp("2008-05-12 09:50:00", tz=tz),
+            Timestamp("2008-12-12 09:50:35", tz=tz),
+            Timestamp("2008-05-12 09:50:32", tz=tz),
+        ]
+        tt = DatetimeIndex(ts)
+        ut = tt.tz_convert("UTC")
+        expected = Index([13, 14, 13], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+        # unsorted case UTC -> US/Eastern
+        ts = [
+            Timestamp("2008-05-12 13:50:00", tz="UTC"),
+            Timestamp("2008-12-12 14:50:35", tz="UTC"),
+            Timestamp("2008-05-12 13:50:32", tz="UTC"),
+        ]
+        tt = DatetimeIndex(ts)
+        ut = tt.tz_convert("US/Eastern")
+        expected = Index([9, 9, 9], dtype=np.int32)
+        tm.assert_index_equal(ut.hour, expected)
+
+    @pytest.mark.parametrize("freq, n", [("h", 1), ("min", 60), ("s", 3600)])
+    def test_dti_tz_convert_trans_pos_plus_1__bug(self, freq, n):
+        # Regression test for tslib.tz_convert(vals, tz1, tz2).
+        # See GH#4496 for details.
+        idx = date_range(datetime(2011, 3, 26, 23), datetime(2011, 3, 27, 1), freq=freq)
+        idx = idx.tz_localize("UTC")
+        idx = idx.tz_convert("Europe/Moscow")
+
+        expected = np.repeat(np.array([3, 4, 5]), np.array([n, n, 1]))
+        tm.assert_index_equal(idx.hour, Index(expected, dtype=np.int32))
+
+    def test_dti_tz_convert_dst(self):
+        for freq, n in [("h", 1), ("min", 60), ("s", 3600)]:
+            # Start DST
+            idx = date_range(
+                "2014-03-08 23:00", "2014-03-09 09:00", freq=freq, tz="UTC"
+            )
+            idx = idx.tz_convert("US/Eastern")
+            expected = np.repeat(
+                np.array([18, 19, 20, 21, 22, 23, 0, 1, 3, 4, 5]),
+                np.array([n, n, n, n, n, n, n, n, n, n, 1]),
+            )
+            tm.assert_index_equal(idx.hour, Index(expected, dtype=np.int32))
+
+            idx = date_range(
+                "2014-03-08 18:00", "2014-03-09 05:00", freq=freq, tz="US/Eastern"
+            )
+            idx = idx.tz_convert("UTC")
+            expected = np.repeat(
+                np.array([23, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),
+                np.array([n, n, n, n, n, n, n, n, n, n, 1]),
+            )
+            tm.assert_index_equal(idx.hour, Index(expected, dtype=np.int32))
+
+            # End DST
+            idx = date_range(
+                "2014-11-01 23:00", "2014-11-02 09:00", freq=freq, tz="UTC"
+            )
+            idx = idx.tz_convert("US/Eastern")
+            expected = np.repeat(
+                np.array([19, 20, 21, 22, 23, 0, 1, 1, 2, 3, 4]),
+                np.array([n, n, n, n, n, n, n, n, n, n, 1]),
+            )
+            tm.assert_index_equal(idx.hour, Index(expected, dtype=np.int32))
+
+            idx = date_range(
+                "2014-11-01 18:00", "2014-11-02 05:00", freq=freq, tz="US/Eastern"
+            )
+            idx = idx.tz_convert("UTC")
+            expected = np.repeat(
+                np.array([22, 23, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
+                np.array([n, n, n, n, n, n, n, n, n, n, n, n, 1]),
+            )
+            tm.assert_index_equal(idx.hour, Index(expected, dtype=np.int32))
+
+        # daily
+        # Start DST
+        idx = date_range("2014-03-08 00:00", "2014-03-09 00:00", freq="D", tz="UTC")
+        idx = idx.tz_convert("US/Eastern")
+        tm.assert_index_equal(idx.hour, Index([19, 19], dtype=np.int32))
+
+        idx = date_range(
+            "2014-03-08 00:00", "2014-03-09 00:00", freq="D", tz="US/Eastern"
+        )
+        idx = idx.tz_convert("UTC")
+        tm.assert_index_equal(idx.hour, Index([5, 5], dtype=np.int32))
+
+        # End DST
+        idx = date_range("2014-11-01 00:00", "2014-11-02 00:00", freq="D", tz="UTC")
+        idx = idx.tz_convert("US/Eastern")
+        tm.assert_index_equal(idx.hour, Index([20, 20], dtype=np.int32))
+
+        idx = date_range(
+            "2014-11-01 00:00", "2014-11-02 000:00", freq="D", tz="US/Eastern"
+        )
+        idx = idx.tz_convert("UTC")
+        tm.assert_index_equal(idx.hour, Index([4, 4], dtype=np.int32))
+
+    def test_tz_convert_roundtrip(self, tz_aware_fixture):
+        tz = tz_aware_fixture
+        idx1 = date_range(start="2014-01-01", end="2014-12-31", freq="ME", tz="UTC")
+        exp1 = date_range(start="2014-01-01", end="2014-12-31", freq="ME")
+
+        idx2 = date_range(start="2014-01-01", end="2014-12-31", freq="D", tz="UTC")
+        exp2 = date_range(start="2014-01-01", end="2014-12-31", freq="D")
+
+        idx3 = date_range(start="2014-01-01", end="2014-03-01", freq="h", tz="UTC")
+        exp3 = date_range(start="2014-01-01", end="2014-03-01", freq="h")
+
+        idx4 = date_range(start="2014-08-01", end="2014-10-31", freq="min", tz="UTC")
+        exp4 = date_range(start="2014-08-01", end="2014-10-31", freq="min")
+
+        for idx, expected in [(idx1, exp1), (idx2, exp2), (idx3, exp3), (idx4, exp4)]:
+            converted = idx.tz_convert(tz)
+            reset = converted.tz_convert(None)
+            tm.assert_index_equal(reset, expected)
+            assert reset.tzinfo is None
+            expected = converted.tz_convert("UTC").tz_localize(None)
+            expected = expected._with_freq("infer")
+            tm.assert_index_equal(reset, expected)
+
+    def test_dti_tz_convert_tzlocal(self):
+        # GH#13583
+        # tz_convert doesn't affect to internal
+        dti = date_range(start="2001-01-01", end="2001-03-01", tz="UTC")
+        dti2 = dti.tz_convert(dateutil.tz.tzlocal())
+        tm.assert_numpy_array_equal(dti2.asi8, dti.asi8)
+
+        dti = date_range(start="2001-01-01", end="2001-03-01", tz=dateutil.tz.tzlocal())
+        dti2 = dti.tz_convert(None)
+        tm.assert_numpy_array_equal(dti2.asi8, dti.asi8)
+
+    @pytest.mark.parametrize(
+        "tz",
+        [
+            "US/Eastern",
+            "dateutil/US/Eastern",
+            pytz.timezone("US/Eastern"),
+            gettz("US/Eastern"),
+        ],
+    )
+    def test_dti_tz_convert_utc_to_local_no_modify(self, tz):
+        rng = date_range("3/11/2012", "3/12/2012", freq="h", tz="utc")
+        rng_eastern = rng.tz_convert(tz)
+
+        # Values are unmodified
+        tm.assert_numpy_array_equal(rng.asi8, rng_eastern.asi8)
+
+        assert timezones.tz_compare(rng_eastern.tz, timezones.maybe_get_tz(tz))
+
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_tz_convert_unsorted(self, tzstr):
+        dr = date_range("2012-03-09", freq="h", periods=100, tz="utc")
+        dr = dr.tz_convert(tzstr)
+
+        result = dr[::-1].hour
+        exp = dr.hour[::-1]
+        tm.assert_almost_equal(result, exp)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_tz_localize.py

@@ -0,0 +1,402 @@
+from datetime import (
+    datetime,
+    timedelta,
+)
+
+import dateutil.tz
+from dateutil.tz import gettz
+import numpy as np
+import pytest
+import pytz
+
+from pandas import (
+    DatetimeIndex,
+    Timestamp,
+    bdate_range,
+    date_range,
+    offsets,
+    to_datetime,
+)
+import pandas._testing as tm
+
+try:
+    from zoneinfo import ZoneInfo
+except ImportError:
+    # Cannot assign to a type  [misc]
+    ZoneInfo = None  # type: ignore[misc, assignment]
+
+
+easts = [pytz.timezone("US/Eastern"), gettz("US/Eastern")]
+if ZoneInfo is not None:
+    try:
+        tz = ZoneInfo("US/Eastern")
+    except KeyError:
+        # no tzdata
+        pass
+    else:
+        easts.append(tz)
+
+
+class TestTZLocalize:
+    def test_tz_localize_invalidates_freq(self):
+        # we only preserve freq in unambiguous cases
+
+        # if localized to US/Eastern, this crosses a DST transition
+        dti = date_range("2014-03-08 23:00", "2014-03-09 09:00", freq="h")
+        assert dti.freq == "h"
+
+        result = dti.tz_localize(None)  # no-op
+        assert result.freq == "h"
+
+        result = dti.tz_localize("UTC")  # unambiguous freq preservation
+        assert result.freq == "h"
+
+        result = dti.tz_localize("US/Eastern", nonexistent="shift_forward")
+        assert result.freq is None
+        assert result.inferred_freq is None  # i.e. we are not _too_ strict here
+
+        # Case where we _can_ keep freq because we're length==1
+        dti2 = dti[:1]
+        result = dti2.tz_localize("US/Eastern")
+        assert result.freq == "h"
+
+    def test_tz_localize_utc_copies(self, utc_fixture):
+        # GH#46460
+        times = ["2015-03-08 01:00", "2015-03-08 02:00", "2015-03-08 03:00"]
+        index = DatetimeIndex(times)
+
+        res = index.tz_localize(utc_fixture)
+        assert not tm.shares_memory(res, index)
+
+        res2 = index._data.tz_localize(utc_fixture)
+        assert not tm.shares_memory(index._data, res2)
+
+    def test_dti_tz_localize_nonexistent_raise_coerce(self):
+        # GH#13057
+        times = ["2015-03-08 01:00", "2015-03-08 02:00", "2015-03-08 03:00"]
+        index = DatetimeIndex(times)
+        tz = "US/Eastern"
+        with pytest.raises(pytz.NonExistentTimeError, match="|".join(times)):
+            index.tz_localize(tz=tz)
+
+        with pytest.raises(pytz.NonExistentTimeError, match="|".join(times)):
+            index.tz_localize(tz=tz, nonexistent="raise")
+
+        result = index.tz_localize(tz=tz, nonexistent="NaT")
+        test_times = ["2015-03-08 01:00-05:00", "NaT", "2015-03-08 03:00-04:00"]
+        dti = to_datetime(test_times, utc=True)
+        expected = dti.tz_convert("US/Eastern")
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_infer(self, tz):
+        # November 6, 2011, fall back, repeat 2 AM hour
+        # With no repeated hours, we cannot infer the transition
+        dr = date_range(datetime(2011, 11, 6, 0), periods=5, freq=offsets.Hour())
+        with pytest.raises(pytz.AmbiguousTimeError, match="Cannot infer dst time"):
+            dr.tz_localize(tz)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_infer2(self, tz, unit):
+        # With repeated hours, we can infer the transition
+        dr = date_range(
+            datetime(2011, 11, 6, 0), periods=5, freq=offsets.Hour(), tz=tz, unit=unit
+        )
+        times = [
+            "11/06/2011 00:00",
+            "11/06/2011 01:00",
+            "11/06/2011 01:00",
+            "11/06/2011 02:00",
+            "11/06/2011 03:00",
+        ]
+        di = DatetimeIndex(times).as_unit(unit)
+        result = di.tz_localize(tz, ambiguous="infer")
+        expected = dr._with_freq(None)
+        tm.assert_index_equal(result, expected)
+        result2 = DatetimeIndex(times, tz=tz, ambiguous="infer").as_unit(unit)
+        tm.assert_index_equal(result2, expected)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_infer3(self, tz):
+        # When there is no dst transition, nothing special happens
+        dr = date_range(datetime(2011, 6, 1, 0), periods=10, freq=offsets.Hour())
+        localized = dr.tz_localize(tz)
+        localized_infer = dr.tz_localize(tz, ambiguous="infer")
+        tm.assert_index_equal(localized, localized_infer)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_times(self, tz):
+        # March 13, 2011, spring forward, skip from 2 AM to 3 AM
+        dr = date_range(datetime(2011, 3, 13, 1, 30), periods=3, freq=offsets.Hour())
+        with pytest.raises(pytz.NonExistentTimeError, match="2011-03-13 02:30:00"):
+            dr.tz_localize(tz)
+
+        # after dst transition, it works
+        dr = date_range(
+            datetime(2011, 3, 13, 3, 30), periods=3, freq=offsets.Hour(), tz=tz
+        )
+
+        # November 6, 2011, fall back, repeat 2 AM hour
+        dr = date_range(datetime(2011, 11, 6, 1, 30), periods=3, freq=offsets.Hour())
+        with pytest.raises(pytz.AmbiguousTimeError, match="Cannot infer dst time"):
+            dr.tz_localize(tz)
+
+        # UTC is OK
+        dr = date_range(
+            datetime(2011, 3, 13), periods=48, freq=offsets.Minute(30), tz=pytz.utc
+        )
+
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_tz_localize_pass_dates_to_utc(self, tzstr):
+        strdates = ["1/1/2012", "3/1/2012", "4/1/2012"]
+
+        idx = DatetimeIndex(strdates)
+        conv = idx.tz_localize(tzstr)
+
+        fromdates = DatetimeIndex(strdates, tz=tzstr)
+
+        assert conv.tz == fromdates.tz
+        tm.assert_numpy_array_equal(conv.values, fromdates.values)
+
+    @pytest.mark.parametrize("prefix", ["", "dateutil/"])
+    def test_dti_tz_localize(self, prefix):
+        tzstr = prefix + "US/Eastern"
+        dti = date_range(start="1/1/2005", end="1/1/2005 0:00:30.256", freq="ms")
+        dti2 = dti.tz_localize(tzstr)
+
+        dti_utc = date_range(
+            start="1/1/2005 05:00", end="1/1/2005 5:00:30.256", freq="ms", tz="utc"
+        )
+
+        tm.assert_numpy_array_equal(dti2.values, dti_utc.values)
+
+        dti3 = dti2.tz_convert(prefix + "US/Pacific")
+        tm.assert_numpy_array_equal(dti3.values, dti_utc.values)
+
+        dti = date_range(start="11/6/2011 1:59", end="11/6/2011 2:00", freq="ms")
+        with pytest.raises(pytz.AmbiguousTimeError, match="Cannot infer dst time"):
+            dti.tz_localize(tzstr)
+
+        dti = date_range(start="3/13/2011 1:59", end="3/13/2011 2:00", freq="ms")
+        with pytest.raises(pytz.NonExistentTimeError, match="2011-03-13 02:00:00"):
+            dti.tz_localize(tzstr)
+
+    @pytest.mark.parametrize(
+        "tz",
+        [
+            "US/Eastern",
+            "dateutil/US/Eastern",
+            pytz.timezone("US/Eastern"),
+            gettz("US/Eastern"),
+        ],
+    )
+    def test_dti_tz_localize_utc_conversion(self, tz):
+        # Localizing to time zone should:
+        #  1) check for DST ambiguities
+        #  2) convert to UTC
+
+        rng = date_range("3/10/2012", "3/11/2012", freq="30min")
+
+        converted = rng.tz_localize(tz)
+        expected_naive = rng + offsets.Hour(5)
+        tm.assert_numpy_array_equal(converted.asi8, expected_naive.asi8)
+
+        # DST ambiguity, this should fail
+        rng = date_range("3/11/2012", "3/12/2012", freq="30min")
+        # Is this really how it should fail??
+        with pytest.raises(pytz.NonExistentTimeError, match="2012-03-11 02:00:00"):
+            rng.tz_localize(tz)
+
+    def test_dti_tz_localize_roundtrip(self, tz_aware_fixture):
+        # note: this tz tests that a tz-naive index can be localized
+        # and de-localized successfully, when there are no DST transitions
+        # in the range.
+        idx = date_range(start="2014-06-01", end="2014-08-30", freq="15min")
+        tz = tz_aware_fixture
+        localized = idx.tz_localize(tz)
+        # can't localize a tz-aware object
+        with pytest.raises(
+            TypeError, match="Already tz-aware, use tz_convert to convert"
+        ):
+            localized.tz_localize(tz)
+        reset = localized.tz_localize(None)
+        assert reset.tzinfo is None
+        expected = idx._with_freq(None)
+        tm.assert_index_equal(reset, expected)
+
+    def test_dti_tz_localize_naive(self):
+        rng = date_range("1/1/2011", periods=100, freq="h")
+
+        conv = rng.tz_localize("US/Pacific")
+        exp = date_range("1/1/2011", periods=100, freq="h", tz="US/Pacific")
+
+        tm.assert_index_equal(conv, exp._with_freq(None))
+
+    def test_dti_tz_localize_tzlocal(self):
+        # GH#13583
+        offset = dateutil.tz.tzlocal().utcoffset(datetime(2011, 1, 1))
+        offset = int(offset.total_seconds() * 1000000000)
+
+        dti = date_range(start="2001-01-01", end="2001-03-01")
+        dti2 = dti.tz_localize(dateutil.tz.tzlocal())
+        tm.assert_numpy_array_equal(dti2.asi8 + offset, dti.asi8)
+
+        dti = date_range(start="2001-01-01", end="2001-03-01", tz=dateutil.tz.tzlocal())
+        dti2 = dti.tz_localize(None)
+        tm.assert_numpy_array_equal(dti2.asi8 - offset, dti.asi8)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_nat(self, tz):
+        times = [
+            "11/06/2011 00:00",
+            "11/06/2011 01:00",
+            "11/06/2011 01:00",
+            "11/06/2011 02:00",
+            "11/06/2011 03:00",
+        ]
+        di = DatetimeIndex(times)
+        localized = di.tz_localize(tz, ambiguous="NaT")
+
+        times = [
+            "11/06/2011 00:00",
+            np.nan,
+            np.nan,
+            "11/06/2011 02:00",
+            "11/06/2011 03:00",
+        ]
+        di_test = DatetimeIndex(times, tz="US/Eastern")
+
+        # left dtype is datetime64[ns, US/Eastern]
+        # right is datetime64[ns, tzfile('/usr/share/zoneinfo/US/Eastern')]
+        tm.assert_numpy_array_equal(di_test.values, localized.values)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_flags(self, tz, unit):
+        # November 6, 2011, fall back, repeat 2 AM hour
+
+        # Pass in flags to determine right dst transition
+        dr = date_range(
+            datetime(2011, 11, 6, 0), periods=5, freq=offsets.Hour(), tz=tz, unit=unit
+        )
+        times = [
+            "11/06/2011 00:00",
+            "11/06/2011 01:00",
+            "11/06/2011 01:00",
+            "11/06/2011 02:00",
+            "11/06/2011 03:00",
+        ]
+
+        # Test tz_localize
+        di = DatetimeIndex(times).as_unit(unit)
+        is_dst = [1, 1, 0, 0, 0]
+        localized = di.tz_localize(tz, ambiguous=is_dst)
+        expected = dr._with_freq(None)
+        tm.assert_index_equal(expected, localized)
+
+        result = DatetimeIndex(times, tz=tz, ambiguous=is_dst).as_unit(unit)
+        tm.assert_index_equal(result, expected)
+
+        localized = di.tz_localize(tz, ambiguous=np.array(is_dst))
+        tm.assert_index_equal(dr, localized)
+
+        localized = di.tz_localize(tz, ambiguous=np.array(is_dst).astype("bool"))
+        tm.assert_index_equal(dr, localized)
+
+        # Test constructor
+        localized = DatetimeIndex(times, tz=tz, ambiguous=is_dst).as_unit(unit)
+        tm.assert_index_equal(dr, localized)
+
+        # Test duplicate times where inferring the dst fails
+        times += times
+        di = DatetimeIndex(times).as_unit(unit)
+
+        # When the sizes are incompatible, make sure error is raised
+        msg = "Length of ambiguous bool-array must be the same size as vals"
+        with pytest.raises(Exception, match=msg):
+            di.tz_localize(tz, ambiguous=is_dst)
+
+        # When sizes are compatible and there are repeats ('infer' won't work)
+        is_dst = np.hstack((is_dst, is_dst))
+        localized = di.tz_localize(tz, ambiguous=is_dst)
+        dr = dr.append(dr)
+        tm.assert_index_equal(dr, localized)
+
+    @pytest.mark.parametrize("tz", easts)
+    def test_dti_tz_localize_ambiguous_flags2(self, tz, unit):
+        # When there is no dst transition, nothing special happens
+        dr = date_range(datetime(2011, 6, 1, 0), periods=10, freq=offsets.Hour())
+        is_dst = np.array([1] * 10)
+        localized = dr.tz_localize(tz)
+        localized_is_dst = dr.tz_localize(tz, ambiguous=is_dst)
+        tm.assert_index_equal(localized, localized_is_dst)
+
+    def test_dti_tz_localize_bdate_range(self):
+        dr = bdate_range("1/1/2009", "1/1/2010")
+        dr_utc = bdate_range("1/1/2009", "1/1/2010", tz=pytz.utc)
+        localized = dr.tz_localize(pytz.utc)
+        tm.assert_index_equal(dr_utc, localized)
+
+    @pytest.mark.parametrize(
+        "start_ts, tz, end_ts, shift",
+        [
+            ["2015-03-29 02:20:00", "Europe/Warsaw", "2015-03-29 03:00:00", "forward"],
+            [
+                "2015-03-29 02:20:00",
+                "Europe/Warsaw",
+                "2015-03-29 01:59:59.999999999",
+                "backward",
+            ],
+            [
+                "2015-03-29 02:20:00",
+                "Europe/Warsaw",
+                "2015-03-29 03:20:00",
+                timedelta(hours=1),
+            ],
+            [
+                "2015-03-29 02:20:00",
+                "Europe/Warsaw",
+                "2015-03-29 01:20:00",
+                timedelta(hours=-1),
+            ],
+            ["2018-03-11 02:33:00", "US/Pacific", "2018-03-11 03:00:00", "forward"],
+            [
+                "2018-03-11 02:33:00",
+                "US/Pacific",
+                "2018-03-11 01:59:59.999999999",
+                "backward",
+            ],
+            [
+                "2018-03-11 02:33:00",
+                "US/Pacific",
+                "2018-03-11 03:33:00",
+                timedelta(hours=1),
+            ],
+            [
+                "2018-03-11 02:33:00",
+                "US/Pacific",
+                "2018-03-11 01:33:00",
+                timedelta(hours=-1),
+            ],
+        ],
+    )
+    @pytest.mark.parametrize("tz_type", ["", "dateutil/"])
+    def test_dti_tz_localize_nonexistent_shift(
+        self, start_ts, tz, end_ts, shift, tz_type, unit
+    ):
+        # GH#8917
+        tz = tz_type + tz
+        if isinstance(shift, str):
+            shift = "shift_" + shift
+        dti = DatetimeIndex([Timestamp(start_ts)]).as_unit(unit)
+        result = dti.tz_localize(tz, nonexistent=shift)
+        expected = DatetimeIndex([Timestamp(end_ts)]).tz_localize(tz).as_unit(unit)
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("offset", [-1, 1])
+    def test_dti_tz_localize_nonexistent_shift_invalid(self, offset, warsaw):
+        # GH#8917
+        tz = warsaw
+        dti = DatetimeIndex([Timestamp("2015-03-29 02:20:00")])
+        msg = "The provided timedelta will relocalize on a nonexistent time"
+        with pytest.raises(ValueError, match=msg):
+            dti.tz_localize(tz, nonexistent=timedelta(seconds=offset))

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/methods/test_unique.py

@@ -0,0 +1,77 @@
+from datetime import (
+    datetime,
+    timedelta,
+)
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    Timestamp,
+)
+import pandas._testing as tm
+
+
+def test_unique(tz_naive_fixture):
+    idx = DatetimeIndex(["2017"] * 2, tz=tz_naive_fixture)
+    expected = idx[:1]
+
+    result = idx.unique()
+    tm.assert_index_equal(result, expected)
+    # GH#21737
+    # Ensure the underlying data is consistent
+    assert result[0] == expected[0]
+
+
+def test_index_unique(rand_series_with_duplicate_datetimeindex):
+    dups = rand_series_with_duplicate_datetimeindex
+    index = dups.index
+
+    uniques = index.unique()
+    expected = DatetimeIndex(
+        [
+            datetime(2000, 1, 2),
+            datetime(2000, 1, 3),
+            datetime(2000, 1, 4),
+            datetime(2000, 1, 5),
+        ],
+        dtype=index.dtype,
+    )
+    assert uniques.dtype == index.dtype  # sanity
+    tm.assert_index_equal(uniques, expected)
+    assert index.nunique() == 4
+
+    # GH#2563
+    assert isinstance(uniques, DatetimeIndex)
+
+    dups_local = index.tz_localize("US/Eastern")
+    dups_local.name = "foo"
+    result = dups_local.unique()
+    expected = DatetimeIndex(expected, name="foo")
+    expected = expected.tz_localize("US/Eastern")
+    assert result.tz is not None
+    assert result.name == "foo"
+    tm.assert_index_equal(result, expected)
+
+
+def test_index_unique2():
+    # NaT, note this is excluded
+    arr = [1370745748 + t for t in range(20)] + [NaT._value]
+    idx = DatetimeIndex(arr * 3)
+    tm.assert_index_equal(idx.unique(), DatetimeIndex(arr))
+    assert idx.nunique() == 20
+    assert idx.nunique(dropna=False) == 21
+
+
+def test_index_unique3():
+    arr = [
+        Timestamp("2013-06-09 02:42:28") + timedelta(seconds=t) for t in range(20)
+    ] + [NaT]
+    idx = DatetimeIndex(arr * 3)
+    tm.assert_index_equal(idx.unique(), DatetimeIndex(arr))
+    assert idx.nunique() == 20
+    assert idx.nunique(dropna=False) == 21
+
+
+def test_is_unique_monotonic(rand_series_with_duplicate_datetimeindex):
+    index = rand_series_with_duplicate_datetimeindex.index
+    assert not index.is_unique

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_arithmetic.py

@@ -0,0 +1,56 @@
+# Arithmetic tests specific to DatetimeIndex are generally about `freq`
+#  rentention or inference.  Other arithmetic tests belong in
+#  tests/arithmetic/test_datetime64.py
+import pytest
+
+from pandas import (
+    Timedelta,
+    TimedeltaIndex,
+    Timestamp,
+    date_range,
+    timedelta_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndexArithmetic:
+    def test_add_timedelta_preserves_freq(self):
+        # GH#37295 should hold for any DTI with freq=None or Tick freq
+        tz = "Canada/Eastern"
+        dti = date_range(
+            start=Timestamp("2019-03-26 00:00:00-0400", tz=tz),
+            end=Timestamp("2020-10-17 00:00:00-0400", tz=tz),
+            freq="D",
+        )
+        result = dti + Timedelta(days=1)
+        assert result.freq == dti.freq
+
+    def test_sub_datetime_preserves_freq(self, tz_naive_fixture):
+        # GH#48818
+        dti = date_range("2016-01-01", periods=12, tz=tz_naive_fixture)
+
+        res = dti - dti[0]
+        expected = timedelta_range("0 Days", "11 Days")
+        tm.assert_index_equal(res, expected)
+        assert res.freq == expected.freq
+
+    @pytest.mark.xfail(
+        reason="The inherited freq is incorrect bc dti.freq is incorrect "
+        "https://github.com/pandas-dev/pandas/pull/48818/files#r982793461"
+    )
+    def test_sub_datetime_preserves_freq_across_dst(self):
+        # GH#48818
+        ts = Timestamp("2016-03-11", tz="US/Pacific")
+        dti = date_range(ts, periods=4)
+
+        res = dti - dti[0]
+        expected = TimedeltaIndex(
+            [
+                Timedelta(days=0),
+                Timedelta(days=1),
+                Timedelta(days=2),
+                Timedelta(days=2, hours=23),
+            ]
+        )
+        tm.assert_index_equal(res, expected)
+        assert res.freq == expected.freq

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_datetime.py

@@ -0,0 +1,216 @@
+import datetime as dt
+from datetime import date
+import re
+
+import numpy as np
+import pytest
+
+from pandas.compat.numpy import np_long
+
+import pandas as pd
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    Index,
+    Timestamp,
+    date_range,
+    offsets,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndex:
+    def test_is_(self):
+        dti = date_range(start="1/1/2005", end="12/1/2005", freq="ME")
+        assert dti.is_(dti)
+        assert dti.is_(dti.view())
+        assert not dti.is_(dti.copy())
+
+    def test_time_overflow_for_32bit_machines(self):
+        # GH8943.  On some machines NumPy defaults to np.int32 (for example,
+        # 32-bit Linux machines).  In the function _generate_regular_range
+        # found in tseries/index.py, `periods` gets multiplied by `strides`
+        # (which has value 1e9) and since the max value for np.int32 is ~2e9,
+        # and since those machines won't promote np.int32 to np.int64, we get
+        # overflow.
+        periods = np_long(1000)
+
+        idx1 = date_range(start="2000", periods=periods, freq="s")
+        assert len(idx1) == periods
+
+        idx2 = date_range(end="2000", periods=periods, freq="s")
+        assert len(idx2) == periods
+
+    def test_nat(self):
+        assert DatetimeIndex([np.nan])[0] is pd.NaT
+
+    def test_week_of_month_frequency(self):
+        # GH 5348: "ValueError: Could not evaluate WOM-1SUN" shouldn't raise
+        d1 = date(2002, 9, 1)
+        d2 = date(2013, 10, 27)
+        d3 = date(2012, 9, 30)
+        idx1 = DatetimeIndex([d1, d2])
+        idx2 = DatetimeIndex([d3])
+        result_append = idx1.append(idx2)
+        expected = DatetimeIndex([d1, d2, d3])
+        tm.assert_index_equal(result_append, expected)
+        result_union = idx1.union(idx2)
+        expected = DatetimeIndex([d1, d3, d2])
+        tm.assert_index_equal(result_union, expected)
+
+    def test_append_nondatetimeindex(self):
+        rng = date_range("1/1/2000", periods=10)
+        idx = Index(["a", "b", "c", "d"])
+
+        result = rng.append(idx)
+        assert isinstance(result[0], Timestamp)
+
+    def test_misc_coverage(self):
+        rng = date_range("1/1/2000", periods=5)
+        result = rng.groupby(rng.day)
+        assert isinstance(next(iter(result.values()))[0], Timestamp)
+
+    # TODO: belongs in frame groupby tests?
+    def test_groupby_function_tuple_1677(self):
+        df = DataFrame(
+            np.random.default_rng(2).random(100),
+            index=date_range("1/1/2000", periods=100),
+        )
+        monthly_group = df.groupby(lambda x: (x.year, x.month))
+
+        result = monthly_group.mean()
+        assert isinstance(result.index[0], tuple)
+
+    def assert_index_parameters(self, index):
+        assert index.freq == "40960ns"
+        assert index.inferred_freq == "40960ns"
+
+    def test_ns_index(self):
+        nsamples = 400
+        ns = int(1e9 / 24414)
+        dtstart = np.datetime64("2012-09-20T00:00:00")
+
+        dt = dtstart + np.arange(nsamples) * np.timedelta64(ns, "ns")
+        freq = ns * offsets.Nano()
+        index = DatetimeIndex(dt, freq=freq, name="time")
+        self.assert_index_parameters(index)
+
+        new_index = date_range(start=index[0], end=index[-1], freq=index.freq)
+        self.assert_index_parameters(new_index)
+
+    def test_asarray_tz_naive(self):
+        # This shouldn't produce a warning.
+        idx = date_range("2000", periods=2)
+        # M8[ns] by default
+        result = np.asarray(idx)
+
+        expected = np.array(["2000-01-01", "2000-01-02"], dtype="M8[ns]")
+        tm.assert_numpy_array_equal(result, expected)
+
+        # optionally, object
+        result = np.asarray(idx, dtype=object)
+
+        expected = np.array([Timestamp("2000-01-01"), Timestamp("2000-01-02")])
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_asarray_tz_aware(self):
+        tz = "US/Central"
+        idx = date_range("2000", periods=2, tz=tz)
+        expected = np.array(["2000-01-01T06", "2000-01-02T06"], dtype="M8[ns]")
+        result = np.asarray(idx, dtype="datetime64[ns]")
+
+        tm.assert_numpy_array_equal(result, expected)
+
+        # Old behavior with no warning
+        result = np.asarray(idx, dtype="M8[ns]")
+
+        tm.assert_numpy_array_equal(result, expected)
+
+        # Future behavior with no warning
+        expected = np.array(
+            [Timestamp("2000-01-01", tz=tz), Timestamp("2000-01-02", tz=tz)]
+        )
+        result = np.asarray(idx, dtype=object)
+
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_CBH_deprecated(self):
+        msg = "'CBH' is deprecated and will be removed in a future version."
+
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            expected = date_range(
+                dt.datetime(2022, 12, 11), dt.datetime(2022, 12, 13), freq="CBH"
+            )
+        result = DatetimeIndex(
+            [
+                "2022-12-12 09:00:00",
+                "2022-12-12 10:00:00",
+                "2022-12-12 11:00:00",
+                "2022-12-12 12:00:00",
+                "2022-12-12 13:00:00",
+                "2022-12-12 14:00:00",
+                "2022-12-12 15:00:00",
+                "2022-12-12 16:00:00",
+            ],
+            dtype="datetime64[ns]",
+            freq="cbh",
+        )
+
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "freq_depr, expected_values, expected_freq",
+        [
+            (
+                "AS-AUG",
+                ["2021-08-01", "2022-08-01", "2023-08-01"],
+                "YS-AUG",
+            ),
+            (
+                "1BAS-MAY",
+                ["2021-05-03", "2022-05-02", "2023-05-01"],
+                "1BYS-MAY",
+            ),
+        ],
+    )
+    def test_AS_BAS_deprecated(self, freq_depr, expected_values, expected_freq):
+        # GH#55479
+        freq_msg = re.split("[0-9]*", freq_depr, maxsplit=1)[1]
+        msg = f"'{freq_msg}' is deprecated and will be removed in a future version."
+
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            expected = date_range(
+                dt.datetime(2020, 12, 1), dt.datetime(2023, 12, 1), freq=freq_depr
+            )
+        result = DatetimeIndex(
+            expected_values,
+            dtype="datetime64[ns]",
+            freq=expected_freq,
+        )
+
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "freq, expected_values, freq_depr",
+        [
+            ("2BYE-MAR", ["2016-03-31"], "2BA-MAR"),
+            ("2BYE-JUN", ["2016-06-30"], "2BY-JUN"),
+            ("2BME", ["2016-02-29", "2016-04-29", "2016-06-30"], "2BM"),
+            ("2BQE", ["2016-03-31"], "2BQ"),
+            ("1BQE-MAR", ["2016-03-31", "2016-06-30"], "1BQ-MAR"),
+        ],
+    )
+    def test_BM_BQ_BY_deprecated(self, freq, expected_values, freq_depr):
+        # GH#52064
+        msg = f"'{freq_depr[1:]}' is deprecated and will be removed "
+        f"in a future version, please use '{freq[1:]}' instead."
+
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            expected = date_range(start="2016-02-21", end="2016-08-21", freq=freq_depr)
+        result = DatetimeIndex(
+            data=expected_values,
+            dtype="datetime64[ns]",
+            freq=freq,
+        )
+
+        tm.assert_index_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_formats.py

@@ -0,0 +1,356 @@
+from datetime import datetime
+
+import dateutil.tz
+import numpy as np
+import pytest
+import pytz
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    Series,
+)
+import pandas._testing as tm
+
+
+@pytest.fixture(params=["s", "ms", "us", "ns"])
+def unit(request):
+    return request.param
+
+
+def test_get_values_for_csv():
+    index = pd.date_range(freq="1D", periods=3, start="2017-01-01")
+
+    # First, with no arguments.
+    expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object)
+
+    result = index._get_values_for_csv()
+    tm.assert_numpy_array_equal(result, expected)
+
+    # No NaN values, so na_rep has no effect
+    result = index._get_values_for_csv(na_rep="pandas")
+    tm.assert_numpy_array_equal(result, expected)
+
+    # Make sure date formatting works
+    expected = np.array(["01-2017-01", "01-2017-02", "01-2017-03"], dtype=object)
+
+    result = index._get_values_for_csv(date_format="%m-%Y-%d")
+    tm.assert_numpy_array_equal(result, expected)
+
+    # NULL object handling should work
+    index = DatetimeIndex(["2017-01-01", NaT, "2017-01-03"])
+    expected = np.array(["2017-01-01", "NaT", "2017-01-03"], dtype=object)
+
+    result = index._get_values_for_csv(na_rep="NaT")
+    tm.assert_numpy_array_equal(result, expected)
+
+    expected = np.array(["2017-01-01", "pandas", "2017-01-03"], dtype=object)
+
+    result = index._get_values_for_csv(na_rep="pandas")
+    tm.assert_numpy_array_equal(result, expected)
+
+    result = index._get_values_for_csv(na_rep="NaT", date_format="%Y-%m-%d %H:%M:%S.%f")
+    expected = np.array(
+        ["2017-01-01 00:00:00.000000", "NaT", "2017-01-03 00:00:00.000000"],
+        dtype=object,
+    )
+    tm.assert_numpy_array_equal(result, expected)
+
+    # invalid format
+    result = index._get_values_for_csv(na_rep="NaT", date_format="foo")
+    expected = np.array(["foo", "NaT", "foo"], dtype=object)
+    tm.assert_numpy_array_equal(result, expected)
+
+
+class TestDatetimeIndexRendering:
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_with_timezone_repr(self, tzstr):
+        rng = pd.date_range("4/13/2010", "5/6/2010")
+
+        rng_eastern = rng.tz_localize(tzstr)
+
+        rng_repr = repr(rng_eastern)
+        assert "2010-04-13 00:00:00" in rng_repr
+
+    def test_dti_repr_dates(self):
+        text = str(pd.to_datetime([datetime(2013, 1, 1), datetime(2014, 1, 1)]))
+        assert "['2013-01-01'," in text
+        assert ", '2014-01-01']" in text
+
+    def test_dti_repr_mixed(self):
+        text = str(
+            pd.to_datetime(
+                [datetime(2013, 1, 1), datetime(2014, 1, 1, 12), datetime(2014, 1, 1)]
+            )
+        )
+        assert "'2013-01-01 00:00:00'," in text
+        assert "'2014-01-01 00:00:00']" in text
+
+    def test_dti_repr_short(self):
+        dr = pd.date_range(start="1/1/2012", periods=1)
+        repr(dr)
+
+        dr = pd.date_range(start="1/1/2012", periods=2)
+        repr(dr)
+
+        dr = pd.date_range(start="1/1/2012", periods=3)
+        repr(dr)
+
+    @pytest.mark.parametrize(
+        "dates, freq, expected_repr",
+        [
+            (
+                ["2012-01-01 00:00:00"],
+                "60min",
+                (
+                    "DatetimeIndex(['2012-01-01 00:00:00'], "
+                    "dtype='datetime64[ns]', freq='60min')"
+                ),
+            ),
+            (
+                ["2012-01-01 00:00:00", "2012-01-01 01:00:00"],
+                "60min",
+                "DatetimeIndex(['2012-01-01 00:00:00', '2012-01-01 01:00:00'], "
+                "dtype='datetime64[ns]', freq='60min')",
+            ),
+            (
+                ["2012-01-01"],
+                "24h",
+                "DatetimeIndex(['2012-01-01'], dtype='datetime64[ns]', freq='24h')",
+            ),
+        ],
+    )
+    def test_dti_repr_time_midnight(self, dates, freq, expected_repr, unit):
+        # GH53634
+        dti = DatetimeIndex(dates, freq).as_unit(unit)
+        actual_repr = repr(dti)
+        assert actual_repr == expected_repr.replace("[ns]", f"[{unit}]")
+
+    def test_dti_representation(self, unit):
+        idxs = []
+        idxs.append(DatetimeIndex([], freq="D"))
+        idxs.append(DatetimeIndex(["2011-01-01"], freq="D"))
+        idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D"))
+        idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D"))
+        idxs.append(
+            DatetimeIndex(
+                ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
+                freq="h",
+                tz="Asia/Tokyo",
+            )
+        )
+        idxs.append(
+            DatetimeIndex(
+                ["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="US/Eastern"
+            )
+        )
+        idxs.append(
+            DatetimeIndex(["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="UTC")
+        )
+
+        exp = []
+        exp.append("DatetimeIndex([], dtype='datetime64[ns]', freq='D')")
+        exp.append("DatetimeIndex(['2011-01-01'], dtype='datetime64[ns]', freq='D')")
+        exp.append(
+            "DatetimeIndex(['2011-01-01', '2011-01-02'], "
+            "dtype='datetime64[ns]', freq='D')"
+        )
+        exp.append(
+            "DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'], "
+            "dtype='datetime64[ns]', freq='D')"
+        )
+        exp.append(
+            "DatetimeIndex(['2011-01-01 09:00:00+09:00', "
+            "'2011-01-01 10:00:00+09:00', '2011-01-01 11:00:00+09:00']"
+            ", dtype='datetime64[ns, Asia/Tokyo]', freq='h')"
+        )
+        exp.append(
+            "DatetimeIndex(['2011-01-01 09:00:00-05:00', "
+            "'2011-01-01 10:00:00-05:00', 'NaT'], "
+            "dtype='datetime64[ns, US/Eastern]', freq=None)"
+        )
+        exp.append(
+            "DatetimeIndex(['2011-01-01 09:00:00+00:00', "
+            "'2011-01-01 10:00:00+00:00', 'NaT'], "
+            "dtype='datetime64[ns, UTC]', freq=None)"
+            ""
+        )
+
+        with pd.option_context("display.width", 300):
+            for index, expected in zip(idxs, exp):
+                index = index.as_unit(unit)
+                expected = expected.replace("[ns", f"[{unit}")
+                result = repr(index)
+                assert result == expected
+                result = str(index)
+                assert result == expected
+
+    # TODO: this is a Series.__repr__ test
+    def test_dti_representation_to_series(self, unit):
+        idx1 = DatetimeIndex([], freq="D")
+        idx2 = DatetimeIndex(["2011-01-01"], freq="D")
+        idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
+        idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
+        idx5 = DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
+            freq="h",
+            tz="Asia/Tokyo",
+        )
+        idx6 = DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="US/Eastern"
+        )
+        idx7 = DatetimeIndex(["2011-01-01 09:00", "2011-01-02 10:15"])
+
+        exp1 = """Series([], dtype: datetime64[ns])"""
+
+        exp2 = "0   2011-01-01\ndtype: datetime64[ns]"
+
+        exp3 = "0   2011-01-01\n1   2011-01-02\ndtype: datetime64[ns]"
+
+        exp4 = (
+            "0   2011-01-01\n"
+            "1   2011-01-02\n"
+            "2   2011-01-03\n"
+            "dtype: datetime64[ns]"
+        )
+
+        exp5 = (
+            "0   2011-01-01 09:00:00+09:00\n"
+            "1   2011-01-01 10:00:00+09:00\n"
+            "2   2011-01-01 11:00:00+09:00\n"
+            "dtype: datetime64[ns, Asia/Tokyo]"
+        )
+
+        exp6 = (
+            "0   2011-01-01 09:00:00-05:00\n"
+            "1   2011-01-01 10:00:00-05:00\n"
+            "2                         NaT\n"
+            "dtype: datetime64[ns, US/Eastern]"
+        )
+
+        exp7 = (
+            "0   2011-01-01 09:00:00\n"
+            "1   2011-01-02 10:15:00\n"
+            "dtype: datetime64[ns]"
+        )
+
+        with pd.option_context("display.width", 300):
+            for idx, expected in zip(
+                [idx1, idx2, idx3, idx4, idx5, idx6, idx7],
+                [exp1, exp2, exp3, exp4, exp5, exp6, exp7],
+            ):
+                ser = Series(idx.as_unit(unit))
+                result = repr(ser)
+                assert result == expected.replace("[ns", f"[{unit}")
+
+    def test_dti_summary(self):
+        # GH#9116
+        idx1 = DatetimeIndex([], freq="D")
+        idx2 = DatetimeIndex(["2011-01-01"], freq="D")
+        idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
+        idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
+        idx5 = DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
+            freq="h",
+            tz="Asia/Tokyo",
+        )
+        idx6 = DatetimeIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", NaT], tz="US/Eastern"
+        )
+
+        exp1 = "DatetimeIndex: 0 entries\nFreq: D"
+
+        exp2 = "DatetimeIndex: 1 entries, 2011-01-01 to 2011-01-01\nFreq: D"
+
+        exp3 = "DatetimeIndex: 2 entries, 2011-01-01 to 2011-01-02\nFreq: D"
+
+        exp4 = "DatetimeIndex: 3 entries, 2011-01-01 to 2011-01-03\nFreq: D"
+
+        exp5 = (
+            "DatetimeIndex: 3 entries, 2011-01-01 09:00:00+09:00 "
+            "to 2011-01-01 11:00:00+09:00\n"
+            "Freq: h"
+        )
+
+        exp6 = """DatetimeIndex: 3 entries, 2011-01-01 09:00:00-05:00 to NaT"""
+
+        for idx, expected in zip(
+            [idx1, idx2, idx3, idx4, idx5, idx6], [exp1, exp2, exp3, exp4, exp5, exp6]
+        ):
+            result = idx._summary()
+            assert result == expected
+
+    @pytest.mark.parametrize("tz", [None, pytz.utc, dateutil.tz.tzutc()])
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_dti_business_repr_etc_smoke(self, tz, freq):
+        # only really care that it works
+        dti = pd.bdate_range(
+            datetime(2009, 1, 1), datetime(2010, 1, 1), tz=tz, freq=freq
+        )
+        repr(dti)
+        dti._summary()
+        dti[2:2]._summary()
+
+
+class TestFormat:
+    def test_format(self):
+        # GH#35439
+        idx = pd.date_range("20130101", periods=5)
+        expected = [f"{x:%Y-%m-%d}" for x in idx]
+        msg = r"DatetimeIndex\.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert idx.format() == expected
+
+    def test_format_with_name_time_info(self):
+        # bug I fixed 12/20/2011
+        dates = pd.date_range("2011-01-01 04:00:00", periods=10, name="something")
+
+        msg = "DatetimeIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = dates.format(name=True)
+        assert formatted[0] == "something"
+
+    def test_format_datetime_with_time(self):
+        dti = DatetimeIndex([datetime(2012, 2, 7), datetime(2012, 2, 7, 23)])
+
+        msg = "DatetimeIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = dti.format()
+        expected = ["2012-02-07 00:00:00", "2012-02-07 23:00:00"]
+        assert len(result) == 2
+        assert result == expected
+
+    def test_format_datetime(self):
+        msg = "DatetimeIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = pd.to_datetime([datetime(2003, 1, 1, 12), NaT]).format()
+        assert formatted[0] == "2003-01-01 12:00:00"
+        assert formatted[1] == "NaT"
+
+    def test_format_date(self):
+        msg = "DatetimeIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = pd.to_datetime([datetime(2003, 1, 1), NaT]).format()
+        assert formatted[0] == "2003-01-01"
+        assert formatted[1] == "NaT"
+
+    def test_format_date_tz(self):
+        dti = pd.to_datetime([datetime(2013, 1, 1)], utc=True)
+        msg = "DatetimeIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = dti.format()
+        assert formatted[0] == "2013-01-01 00:00:00+00:00"
+
+        dti = pd.to_datetime([datetime(2013, 1, 1), NaT], utc=True)
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = dti.format()
+        assert formatted[0] == "2013-01-01 00:00:00+00:00"
+
+    def test_format_date_explicit_date_format(self):
+        dti = pd.to_datetime([datetime(2003, 2, 1), NaT])
+        msg = "DatetimeIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = dti.format(date_format="%m-%d-%Y", na_rep="UT")
+        assert formatted[0] == "02-01-2003"
+        assert formatted[1] == "UT"

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_freq_attr.py

@@ -0,0 +1,61 @@
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    date_range,
+)
+
+from pandas.tseries.offsets import (
+    BDay,
+    DateOffset,
+    Day,
+    Hour,
+)
+
+
+class TestFreq:
+    def test_freq_setter_errors(self):
+        # GH#20678
+        idx = DatetimeIndex(["20180101", "20180103", "20180105"])
+
+        # setting with an incompatible freq
+        msg = (
+            "Inferred frequency 2D from passed values does not conform to "
+            "passed frequency 5D"
+        )
+        with pytest.raises(ValueError, match=msg):
+            idx._data.freq = "5D"
+
+        # setting with non-freq string
+        with pytest.raises(ValueError, match="Invalid frequency"):
+            idx._data.freq = "foo"
+
+    @pytest.mark.parametrize("values", [["20180101", "20180103", "20180105"], []])
+    @pytest.mark.parametrize("freq", ["2D", Day(2), "2B", BDay(2), "48h", Hour(48)])
+    @pytest.mark.parametrize("tz", [None, "US/Eastern"])
+    def test_freq_setter(self, values, freq, tz):
+        # GH#20678
+        idx = DatetimeIndex(values, tz=tz)
+
+        # can set to an offset, converting from string if necessary
+        idx._data.freq = freq
+        assert idx.freq == freq
+        assert isinstance(idx.freq, DateOffset)
+
+        # can reset to None
+        idx._data.freq = None
+        assert idx.freq is None
+
+    def test_freq_view_safe(self):
+        # Setting the freq for one DatetimeIndex shouldn't alter the freq
+        #  for another that views the same data
+
+        dti = date_range("2016-01-01", periods=5)
+        dta = dti._data
+
+        dti2 = DatetimeIndex(dta)._with_freq(None)
+        assert dti2.freq is None
+
+        # Original was not altered
+        assert dti.freq == "D"
+        assert dta.freq == "D"

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_indexing.py

@@ -0,0 +1,717 @@
+from datetime import (
+    date,
+    datetime,
+    time,
+    timedelta,
+)
+
+import numpy as np
+import pytest
+
+from pandas._libs import index as libindex
+from pandas.compat.numpy import np_long
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    Index,
+    Timestamp,
+    bdate_range,
+    date_range,
+    notna,
+)
+import pandas._testing as tm
+
+from pandas.tseries.frequencies import to_offset
+
+START, END = datetime(2009, 1, 1), datetime(2010, 1, 1)
+
+
+class TestGetItem:
+    def test_getitem_slice_keeps_name(self):
+        # GH4226
+        st = Timestamp("2013-07-01 00:00:00", tz="America/Los_Angeles")
+        et = Timestamp("2013-07-02 00:00:00", tz="America/Los_Angeles")
+        dr = date_range(st, et, freq="h", name="timebucket")
+        assert dr[1:].name == dr.name
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo"])
+    def test_getitem(self, tz):
+        idx = date_range("2011-01-01", "2011-01-31", freq="D", tz=tz, name="idx")
+
+        result = idx[0]
+        assert result == Timestamp("2011-01-01", tz=idx.tz)
+
+        result = idx[0:5]
+        expected = date_range(
+            "2011-01-01", "2011-01-05", freq="D", tz=idx.tz, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+        result = idx[0:10:2]
+        expected = date_range(
+            "2011-01-01", "2011-01-09", freq="2D", tz=idx.tz, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+        result = idx[-20:-5:3]
+        expected = date_range(
+            "2011-01-12", "2011-01-24", freq="3D", tz=idx.tz, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+        result = idx[4::-1]
+        expected = DatetimeIndex(
+            ["2011-01-05", "2011-01-04", "2011-01-03", "2011-01-02", "2011-01-01"],
+            dtype=idx.dtype,
+            freq="-1D",
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_dti_business_getitem(self, freq):
+        rng = bdate_range(START, END, freq=freq)
+        smaller = rng[:5]
+        exp = DatetimeIndex(rng.view(np.ndarray)[:5], freq=freq)
+        tm.assert_index_equal(smaller, exp)
+        assert smaller.freq == exp.freq
+        assert smaller.freq == rng.freq
+
+        sliced = rng[::5]
+        assert sliced.freq == to_offset(freq) * 5
+
+        fancy_indexed = rng[[4, 3, 2, 1, 0]]
+        assert len(fancy_indexed) == 5
+        assert isinstance(fancy_indexed, DatetimeIndex)
+        assert fancy_indexed.freq is None
+
+        # 32-bit vs. 64-bit platforms
+        assert rng[4] == rng[np_long(4)]
+
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_dti_business_getitem_matplotlib_hackaround(self, freq):
+        rng = bdate_range(START, END, freq=freq)
+        with pytest.raises(ValueError, match="Multi-dimensional indexing"):
+            # GH#30588 multi-dimensional indexing deprecated
+            rng[:, None]
+
+    def test_getitem_int_list(self):
+        dti = date_range(start="1/1/2005", end="12/1/2005", freq="ME")
+        dti2 = dti[[1, 3, 5]]
+
+        v1 = dti2[0]
+        v2 = dti2[1]
+        v3 = dti2[2]
+
+        assert v1 == Timestamp("2/28/2005")
+        assert v2 == Timestamp("4/30/2005")
+        assert v3 == Timestamp("6/30/2005")
+
+        # getitem with non-slice drops freq
+        assert dti2.freq is None
+
+
+class TestWhere:
+    def test_where_doesnt_retain_freq(self):
+        dti = date_range("20130101", periods=3, freq="D", name="idx")
+        cond = [True, True, False]
+        expected = DatetimeIndex([dti[0], dti[1], dti[0]], freq=None, name="idx")
+
+        result = dti.where(cond, dti[::-1])
+        tm.assert_index_equal(result, expected)
+
+    def test_where_other(self):
+        # other is ndarray or Index
+        i = date_range("20130101", periods=3, tz="US/Eastern")
+
+        for arr in [np.nan, pd.NaT]:
+            result = i.where(notna(i), other=arr)
+            expected = i
+            tm.assert_index_equal(result, expected)
+
+        i2 = i.copy()
+        i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
+        result = i.where(notna(i2), i2)
+        tm.assert_index_equal(result, i2)
+
+        i2 = i.copy()
+        i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
+        result = i.where(notna(i2), i2._values)
+        tm.assert_index_equal(result, i2)
+
+    def test_where_invalid_dtypes(self):
+        dti = date_range("20130101", periods=3, tz="US/Eastern")
+
+        tail = dti[2:].tolist()
+        i2 = Index([pd.NaT, pd.NaT] + tail)
+
+        mask = notna(i2)
+
+        # passing tz-naive ndarray to tzaware DTI
+        result = dti.where(mask, i2.values)
+        expected = Index([pd.NaT.asm8, pd.NaT.asm8] + tail, dtype=object)
+        tm.assert_index_equal(result, expected)
+
+        # passing tz-aware DTI to tznaive DTI
+        naive = dti.tz_localize(None)
+        result = naive.where(mask, i2)
+        expected = Index([i2[0], i2[1]] + naive[2:].tolist(), dtype=object)
+        tm.assert_index_equal(result, expected)
+
+        pi = i2.tz_localize(None).to_period("D")
+        result = dti.where(mask, pi)
+        expected = Index([pi[0], pi[1]] + tail, dtype=object)
+        tm.assert_index_equal(result, expected)
+
+        tda = i2.asi8.view("timedelta64[ns]")
+        result = dti.where(mask, tda)
+        expected = Index([tda[0], tda[1]] + tail, dtype=object)
+        assert isinstance(expected[0], np.timedelta64)
+        tm.assert_index_equal(result, expected)
+
+        result = dti.where(mask, i2.asi8)
+        expected = Index([pd.NaT._value, pd.NaT._value] + tail, dtype=object)
+        assert isinstance(expected[0], int)
+        tm.assert_index_equal(result, expected)
+
+        # non-matching scalar
+        td = pd.Timedelta(days=4)
+        result = dti.where(mask, td)
+        expected = Index([td, td] + tail, dtype=object)
+        assert expected[0] is td
+        tm.assert_index_equal(result, expected)
+
+    def test_where_mismatched_nat(self, tz_aware_fixture):
+        tz = tz_aware_fixture
+        dti = date_range("2013-01-01", periods=3, tz=tz)
+        cond = np.array([True, False, True])
+
+        tdnat = np.timedelta64("NaT", "ns")
+        expected = Index([dti[0], tdnat, dti[2]], dtype=object)
+        assert expected[1] is tdnat
+
+        result = dti.where(cond, tdnat)
+        tm.assert_index_equal(result, expected)
+
+    def test_where_tz(self):
+        i = date_range("20130101", periods=3, tz="US/Eastern")
+        result = i.where(notna(i))
+        expected = i
+        tm.assert_index_equal(result, expected)
+
+        i2 = i.copy()
+        i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
+        result = i.where(notna(i2))
+        expected = i2
+        tm.assert_index_equal(result, expected)
+
+
+class TestTake:
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_take_dont_lose_meta(self, tzstr):
+        rng = date_range("1/1/2000", periods=20, tz=tzstr)
+
+        result = rng.take(range(5))
+        assert result.tz == rng.tz
+        assert result.freq == rng.freq
+
+    def test_take_nan_first_datetime(self):
+        index = DatetimeIndex([pd.NaT, Timestamp("20130101"), Timestamp("20130102")])
+        result = index.take([-1, 0, 1])
+        expected = DatetimeIndex([index[-1], index[0], index[1]])
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo"])
+    def test_take(self, tz):
+        # GH#10295
+        idx = date_range("2011-01-01", "2011-01-31", freq="D", name="idx", tz=tz)
+
+        result = idx.take([0])
+        assert result == Timestamp("2011-01-01", tz=idx.tz)
+
+        result = idx.take([0, 1, 2])
+        expected = date_range(
+            "2011-01-01", "2011-01-03", freq="D", tz=idx.tz, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+        result = idx.take([0, 2, 4])
+        expected = date_range(
+            "2011-01-01", "2011-01-05", freq="2D", tz=idx.tz, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+        result = idx.take([7, 4, 1])
+        expected = date_range(
+            "2011-01-08", "2011-01-02", freq="-3D", tz=idx.tz, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
+        result = idx.take([3, 2, 5])
+        expected = DatetimeIndex(
+            ["2011-01-04", "2011-01-03", "2011-01-06"],
+            dtype=idx.dtype,
+            freq=None,
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq is None
+
+        result = idx.take([-3, 2, 5])
+        expected = DatetimeIndex(
+            ["2011-01-29", "2011-01-03", "2011-01-06"],
+            dtype=idx.dtype,
+            freq=None,
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.freq is None
+
+    def test_take_invalid_kwargs(self):
+        idx = date_range("2011-01-01", "2011-01-31", freq="D", name="idx")
+        indices = [1, 6, 5, 9, 10, 13, 15, 3]
+
+        msg = r"take\(\) got an unexpected keyword argument 'foo'"
+        with pytest.raises(TypeError, match=msg):
+            idx.take(indices, foo=2)
+
+        msg = "the 'out' parameter is not supported"
+        with pytest.raises(ValueError, match=msg):
+            idx.take(indices, out=indices)
+
+        msg = "the 'mode' parameter is not supported"
+        with pytest.raises(ValueError, match=msg):
+            idx.take(indices, mode="clip")
+
+    # TODO: This method came from test_datetime; de-dup with version above
+    @pytest.mark.parametrize("tz", [None, "US/Eastern", "Asia/Tokyo"])
+    def test_take2(self, tz):
+        dates = [
+            datetime(2010, 1, 1, 14),
+            datetime(2010, 1, 1, 15),
+            datetime(2010, 1, 1, 17),
+            datetime(2010, 1, 1, 21),
+        ]
+
+        idx = date_range(
+            start="2010-01-01 09:00",
+            end="2010-02-01 09:00",
+            freq="h",
+            tz=tz,
+            name="idx",
+        )
+        expected = DatetimeIndex(dates, freq=None, name="idx", dtype=idx.dtype)
+
+        taken1 = idx.take([5, 6, 8, 12])
+        taken2 = idx[[5, 6, 8, 12]]
+
+        for taken in [taken1, taken2]:
+            tm.assert_index_equal(taken, expected)
+            assert isinstance(taken, DatetimeIndex)
+            assert taken.freq is None
+            assert taken.tz == expected.tz
+            assert taken.name == expected.name
+
+    def test_take_fill_value(self):
+        # GH#12631
+        idx = DatetimeIndex(["2011-01-01", "2011-02-01", "2011-03-01"], name="xxx")
+        result = idx.take(np.array([1, 0, -1]))
+        expected = DatetimeIndex(["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        # fill_value
+        result = idx.take(np.array([1, 0, -1]), fill_value=True)
+        expected = DatetimeIndex(["2011-02-01", "2011-01-01", "NaT"], name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        # allow_fill=False
+        result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
+        expected = DatetimeIndex(["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        msg = (
+            "When allow_fill=True and fill_value is not None, "
+            "all indices must be >= -1"
+        )
+        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)
+
+        msg = "out of bounds"
+        with pytest.raises(IndexError, match=msg):
+            idx.take(np.array([1, -5]))
+
+    def test_take_fill_value_with_timezone(self):
+        idx = DatetimeIndex(
+            ["2011-01-01", "2011-02-01", "2011-03-01"], name="xxx", tz="US/Eastern"
+        )
+        result = idx.take(np.array([1, 0, -1]))
+        expected = DatetimeIndex(
+            ["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx", tz="US/Eastern"
+        )
+        tm.assert_index_equal(result, expected)
+
+        # fill_value
+        result = idx.take(np.array([1, 0, -1]), fill_value=True)
+        expected = DatetimeIndex(
+            ["2011-02-01", "2011-01-01", "NaT"], name="xxx", tz="US/Eastern"
+        )
+        tm.assert_index_equal(result, expected)
+
+        # allow_fill=False
+        result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
+        expected = DatetimeIndex(
+            ["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx", tz="US/Eastern"
+        )
+        tm.assert_index_equal(result, expected)
+
+        msg = (
+            "When allow_fill=True and fill_value is not None, "
+            "all indices must be >= -1"
+        )
+        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)
+
+        msg = "out of bounds"
+        with pytest.raises(IndexError, match=msg):
+            idx.take(np.array([1, -5]))
+
+
+class TestGetLoc:
+    def test_get_loc_key_unit_mismatch(self):
+        idx = date_range("2000-01-01", periods=3)
+        key = idx[1].as_unit("ms")
+        loc = idx.get_loc(key)
+        assert loc == 1
+        assert key in idx
+
+    def test_get_loc_key_unit_mismatch_not_castable(self):
+        dta = date_range("2000-01-01", periods=3)._data.astype("M8[s]")
+        dti = DatetimeIndex(dta)
+        key = dta[0].as_unit("ns") + pd.Timedelta(1)
+
+        with pytest.raises(
+            KeyError, match=r"Timestamp\('2000-01-01 00:00:00.000000001'\)"
+        ):
+            dti.get_loc(key)
+
+        assert key not in dti
+
+    def test_get_loc_time_obj(self):
+        # time indexing
+        idx = date_range("2000-01-01", periods=24, freq="h")
+
+        result = idx.get_loc(time(12))
+        expected = np.array([12])
+        tm.assert_numpy_array_equal(result, expected, check_dtype=False)
+
+        result = idx.get_loc(time(12, 30))
+        expected = np.array([])
+        tm.assert_numpy_array_equal(result, expected, check_dtype=False)
+
+    @pytest.mark.parametrize("offset", [-10, 10])
+    def test_get_loc_time_obj2(self, monkeypatch, offset):
+        # GH#8667
+        size_cutoff = 50
+        n = size_cutoff + offset
+        key = time(15, 11, 30)
+        start = key.hour * 3600 + key.minute * 60 + key.second
+        step = 24 * 3600
+
+        with monkeypatch.context():
+            monkeypatch.setattr(libindex, "_SIZE_CUTOFF", size_cutoff)
+            idx = date_range("2014-11-26", periods=n, freq="s")
+            ts = pd.Series(np.random.default_rng(2).standard_normal(n), index=idx)
+            locs = np.arange(start, n, step, dtype=np.intp)
+
+            result = ts.index.get_loc(key)
+            tm.assert_numpy_array_equal(result, locs)
+            tm.assert_series_equal(ts[key], ts.iloc[locs])
+
+            left, right = ts.copy(), ts.copy()
+            left[key] *= -10
+            right.iloc[locs] *= -10
+            tm.assert_series_equal(left, right)
+
+    def test_get_loc_time_nat(self):
+        # GH#35114
+        # Case where key's total microseconds happens to match iNaT % 1e6 // 1000
+        tic = time(minute=12, second=43, microsecond=145224)
+        dti = DatetimeIndex([pd.NaT])
+
+        loc = dti.get_loc(tic)
+        expected = np.array([], dtype=np.intp)
+        tm.assert_numpy_array_equal(loc, expected)
+
+    def test_get_loc_nat(self):
+        # GH#20464
+        index = DatetimeIndex(["1/3/2000", "NaT"])
+        assert index.get_loc(pd.NaT) == 1
+
+        assert index.get_loc(None) == 1
+
+        assert index.get_loc(np.nan) == 1
+
+        assert index.get_loc(pd.NA) == 1
+
+        assert index.get_loc(np.datetime64("NaT")) == 1
+
+        with pytest.raises(KeyError, match="NaT"):
+            index.get_loc(np.timedelta64("NaT"))
+
+    @pytest.mark.parametrize("key", [pd.Timedelta(0), pd.Timedelta(1), timedelta(0)])
+    def test_get_loc_timedelta_invalid_key(self, key):
+        # GH#20464
+        dti = date_range("1970-01-01", periods=10)
+        msg = "Cannot index DatetimeIndex with [Tt]imedelta"
+        with pytest.raises(TypeError, match=msg):
+            dti.get_loc(key)
+
+    def test_get_loc_reasonable_key_error(self):
+        # GH#1062
+        index = DatetimeIndex(["1/3/2000"])
+        with pytest.raises(KeyError, match="2000"):
+            index.get_loc("1/1/2000")
+
+    def test_get_loc_year_str(self):
+        rng = date_range("1/1/2000", "1/1/2010")
+
+        result = rng.get_loc("2009")
+        expected = slice(3288, 3653)
+        assert result == expected
+
+
+class TestContains:
+    def test_dti_contains_with_duplicates(self):
+        d = datetime(2011, 12, 5, 20, 30)
+        ix = DatetimeIndex([d, d])
+        assert d in ix
+
+    @pytest.mark.parametrize(
+        "vals",
+        [
+            [0, 1, 0],
+            [0, 0, -1],
+            [0, -1, -1],
+            ["2015", "2015", "2016"],
+            ["2015", "2015", "2014"],
+        ],
+    )
+    def test_contains_nonunique(self, vals):
+        # GH#9512
+        idx = DatetimeIndex(vals)
+        assert idx[0] in idx
+
+
+class TestGetIndexer:
+    def test_get_indexer_date_objs(self):
+        rng = date_range("1/1/2000", periods=20)
+
+        result = rng.get_indexer(rng.map(lambda x: x.date()))
+        expected = rng.get_indexer(rng)
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_get_indexer(self):
+        idx = date_range("2000-01-01", periods=3)
+        exp = np.array([0, 1, 2], dtype=np.intp)
+        tm.assert_numpy_array_equal(idx.get_indexer(idx), exp)
+
+        target = idx[0] + pd.to_timedelta(["-1 hour", "12 hours", "1 day 1 hour"])
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
+        )
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
+        )
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
+        )
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "nearest", tolerance=pd.Timedelta("1 hour")),
+            np.array([0, -1, 1], dtype=np.intp),
+        )
+        tol_raw = [
+            pd.Timedelta("1 hour"),
+            pd.Timedelta("1 hour"),
+            pd.Timedelta("1 hour").to_timedelta64(),
+        ]
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(
+                target, "nearest", tolerance=[np.timedelta64(x) for x in tol_raw]
+            ),
+            np.array([0, -1, 1], dtype=np.intp),
+        )
+        tol_bad = [
+            pd.Timedelta("2 hour").to_timedelta64(),
+            pd.Timedelta("1 hour").to_timedelta64(),
+            "foo",
+        ]
+        msg = "Could not convert 'foo' to NumPy timedelta"
+        with pytest.raises(ValueError, match=msg):
+            idx.get_indexer(target, "nearest", tolerance=tol_bad)
+        with pytest.raises(ValueError, match="abbreviation w/o a number"):
+            idx.get_indexer(idx[[0]], method="nearest", tolerance="foo")
+
+    @pytest.mark.parametrize(
+        "target",
+        [
+            [date(2020, 1, 1), Timestamp("2020-01-02")],
+            [Timestamp("2020-01-01"), date(2020, 1, 2)],
+        ],
+    )
+    def test_get_indexer_mixed_dtypes(self, target):
+        # https://github.com/pandas-dev/pandas/issues/33741
+        values = DatetimeIndex([Timestamp("2020-01-01"), Timestamp("2020-01-02")])
+        result = values.get_indexer(target)
+        expected = np.array([0, 1], dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "target, positions",
+        [
+            ([date(9999, 1, 1), Timestamp("2020-01-01")], [-1, 0]),
+            ([Timestamp("2020-01-01"), date(9999, 1, 1)], [0, -1]),
+            ([date(9999, 1, 1), date(9999, 1, 1)], [-1, -1]),
+        ],
+    )
+    def test_get_indexer_out_of_bounds_date(self, target, positions):
+        values = DatetimeIndex([Timestamp("2020-01-01"), Timestamp("2020-01-02")])
+
+        result = values.get_indexer(target)
+        expected = np.array(positions, dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_get_indexer_pad_requires_monotonicity(self):
+        rng = date_range("1/1/2000", "3/1/2000", freq="B")
+
+        # neither monotonic increasing or decreasing
+        rng2 = rng[[1, 0, 2]]
+
+        msg = "index must be monotonic increasing or decreasing"
+        with pytest.raises(ValueError, match=msg):
+            rng2.get_indexer(rng, method="pad")
+
+
+class TestMaybeCastSliceBound:
+    def test_maybe_cast_slice_bounds_empty(self):
+        # GH#14354
+        empty_idx = date_range(freq="1h", periods=0, end="2015")
+
+        right = empty_idx._maybe_cast_slice_bound("2015-01-02", "right")
+        exp = Timestamp("2015-01-02 23:59:59.999999999")
+        assert right == exp
+
+        left = empty_idx._maybe_cast_slice_bound("2015-01-02", "left")
+        exp = Timestamp("2015-01-02 00:00:00")
+        assert left == exp
+
+    def test_maybe_cast_slice_duplicate_monotonic(self):
+        # https://github.com/pandas-dev/pandas/issues/16515
+        idx = DatetimeIndex(["2017", "2017"])
+        result = idx._maybe_cast_slice_bound("2017-01-01", "left")
+        expected = Timestamp("2017-01-01")
+        assert result == expected
+
+
+class TestGetSliceBounds:
+    @pytest.mark.parametrize("box", [date, datetime, Timestamp])
+    @pytest.mark.parametrize("side, expected", [("left", 4), ("right", 5)])
+    def test_get_slice_bounds_datetime_within(
+        self, box, side, expected, tz_aware_fixture
+    ):
+        # GH 35690
+        tz = tz_aware_fixture
+        index = bdate_range("2000-01-03", "2000-02-11").tz_localize(tz)
+        key = box(year=2000, month=1, day=7)
+
+        if tz is not None:
+            with pytest.raises(TypeError, match="Cannot compare tz-naive"):
+                # GH#36148 we require tzawareness-compat as of 2.0
+                index.get_slice_bound(key, side=side)
+        else:
+            result = index.get_slice_bound(key, side=side)
+            assert result == expected
+
+    @pytest.mark.parametrize("box", [datetime, Timestamp])
+    @pytest.mark.parametrize("side", ["left", "right"])
+    @pytest.mark.parametrize("year, expected", [(1999, 0), (2020, 30)])
+    def test_get_slice_bounds_datetime_outside(
+        self, box, side, year, expected, tz_aware_fixture
+    ):
+        # GH 35690
+        tz = tz_aware_fixture
+        index = bdate_range("2000-01-03", "2000-02-11").tz_localize(tz)
+        key = box(year=year, month=1, day=7)
+
+        if tz is not None:
+            with pytest.raises(TypeError, match="Cannot compare tz-naive"):
+                # GH#36148 we require tzawareness-compat as of 2.0
+                index.get_slice_bound(key, side=side)
+        else:
+            result = index.get_slice_bound(key, side=side)
+            assert result == expected
+
+    @pytest.mark.parametrize("box", [datetime, Timestamp])
+    def test_slice_datetime_locs(self, box, tz_aware_fixture):
+        # GH 34077
+        tz = tz_aware_fixture
+        index = DatetimeIndex(["2010-01-01", "2010-01-03"]).tz_localize(tz)
+        key = box(2010, 1, 1)
+
+        if tz is not None:
+            with pytest.raises(TypeError, match="Cannot compare tz-naive"):
+                # GH#36148 we require tzawareness-compat as of 2.0
+                index.slice_locs(key, box(2010, 1, 2))
+        else:
+            result = index.slice_locs(key, box(2010, 1, 2))
+            expected = (0, 1)
+            assert result == expected
+
+
+class TestIndexerBetweenTime:
+    def test_indexer_between_time(self):
+        # GH#11818
+        rng = date_range("1/1/2000", "1/5/2000", freq="5min")
+        msg = r"Cannot convert arg \[datetime\.datetime\(2010, 1, 2, 1, 0\)\] to a time"
+        with pytest.raises(ValueError, match=msg):
+            rng.indexer_between_time(datetime(2010, 1, 2, 1), datetime(2010, 1, 2, 5))
+
+    @pytest.mark.parametrize("unit", ["us", "ms", "s"])
+    def test_indexer_between_time_non_nano(self, unit):
+        # For simple cases like this, the non-nano indexer_between_time
+        #  should match the nano result
+
+        rng = date_range("1/1/2000", "1/5/2000", freq="5min")
+        arr_nano = rng._data._ndarray
+
+        arr = arr_nano.astype(f"M8[{unit}]")
+
+        dta = type(rng._data)._simple_new(arr, dtype=arr.dtype)
+        dti = DatetimeIndex(dta)
+        assert dti.dtype == arr.dtype
+
+        tic = time(1, 25)
+        toc = time(2, 29)
+
+        result = dti.indexer_between_time(tic, toc)
+        expected = rng.indexer_between_time(tic, toc)
+        tm.assert_numpy_array_equal(result, expected)
+
+        # case with non-zero micros in arguments
+        tic = time(1, 25, 0, 45678)
+        toc = time(2, 29, 0, 1234)
+
+        result = dti.indexer_between_time(tic, toc)
+        expected = rng.indexer_between_time(tic, toc)
+        tm.assert_numpy_array_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_iter.py

@@ -0,0 +1,76 @@
+import dateutil.tz
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    date_range,
+    to_datetime,
+)
+from pandas.core.arrays import datetimes
+
+
+class TestDatetimeIndexIteration:
+    @pytest.mark.parametrize(
+        "tz", [None, "UTC", "US/Central", dateutil.tz.tzoffset(None, -28800)]
+    )
+    def test_iteration_preserves_nanoseconds(self, tz):
+        # GH#19603
+        index = DatetimeIndex(
+            ["2018-02-08 15:00:00.168456358", "2018-02-08 15:00:00.168456359"], tz=tz
+        )
+        for i, ts in enumerate(index):
+            assert ts == index[i]  # pylint: disable=unnecessary-list-index-lookup
+
+    def test_iter_readonly(self):
+        # GH#28055 ints_to_pydatetime with readonly array
+        arr = np.array([np.datetime64("2012-02-15T12:00:00.000000000")])
+        arr.setflags(write=False)
+        dti = to_datetime(arr)
+        list(dti)
+
+    def test_iteration_preserves_tz(self):
+        # see GH#8890
+        index = date_range("2012-01-01", periods=3, freq="h", tz="US/Eastern")
+
+        for i, ts in enumerate(index):
+            result = ts
+            expected = index[i]  # pylint: disable=unnecessary-list-index-lookup
+            assert result == expected
+
+    def test_iteration_preserves_tz2(self):
+        index = date_range(
+            "2012-01-01", periods=3, freq="h", tz=dateutil.tz.tzoffset(None, -28800)
+        )
+
+        for i, ts in enumerate(index):
+            result = ts
+            expected = index[i]  # pylint: disable=unnecessary-list-index-lookup
+            assert result._repr_base == expected._repr_base
+            assert result == expected
+
+    def test_iteration_preserves_tz3(self):
+        # GH#9100
+        index = DatetimeIndex(
+            ["2014-12-01 03:32:39.987000-08:00", "2014-12-01 04:12:34.987000-08:00"]
+        )
+        for i, ts in enumerate(index):
+            result = ts
+            expected = index[i]  # pylint: disable=unnecessary-list-index-lookup
+            assert result._repr_base == expected._repr_base
+            assert result == expected
+
+    @pytest.mark.parametrize("offset", [-5, -1, 0, 1])
+    def test_iteration_over_chunksize(self, offset, monkeypatch):
+        # GH#21012
+        chunksize = 5
+        index = date_range(
+            "2000-01-01 00:00:00", periods=chunksize - offset, freq="min"
+        )
+        num = 0
+        with monkeypatch.context() as m:
+            m.setattr(datetimes, "_ITER_CHUNKSIZE", chunksize)
+            for stamp in index:
+                assert index[num] == stamp
+                num += 1
+        assert num == len(index)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_join.py

@@ -0,0 +1,149 @@
+from datetime import (
+    datetime,
+    timezone,
+)
+
+import numpy as np
+import pytest
+
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    Index,
+    Timestamp,
+    date_range,
+    period_range,
+    to_datetime,
+)
+import pandas._testing as tm
+
+from pandas.tseries.offsets import (
+    BDay,
+    BMonthEnd,
+)
+
+
+class TestJoin:
+    def test_does_not_convert_mixed_integer(self):
+        df = DataFrame(np.ones((3, 2)), columns=date_range("2020-01-01", periods=2))
+        cols = df.columns.join(df.index, how="outer")
+        joined = cols.join(df.columns)
+        assert cols.dtype == np.dtype("O")
+        assert cols.dtype == joined.dtype
+        tm.assert_numpy_array_equal(cols.values, joined.values)
+
+    def test_join_self(self, join_type):
+        index = date_range("1/1/2000", periods=10)
+        joined = index.join(index, how=join_type)
+        assert index is joined
+
+    def test_join_with_period_index(self, join_type):
+        df = DataFrame(
+            np.ones((10, 2)),
+            index=date_range("2020-01-01", periods=10),
+            columns=period_range("2020-01-01", periods=2),
+        )
+        s = df.iloc[:5, 0]
+
+        expected = df.columns.astype("O").join(s.index, how=join_type)
+        result = df.columns.join(s.index, how=join_type)
+        tm.assert_index_equal(expected, result)
+
+    def test_join_object_index(self):
+        rng = date_range("1/1/2000", periods=10)
+        idx = Index(["a", "b", "c", "d"])
+
+        result = rng.join(idx, how="outer")
+        assert isinstance(result[0], Timestamp)
+
+    def test_join_utc_convert(self, join_type):
+        rng = date_range("1/1/2011", periods=100, freq="h", tz="utc")
+
+        left = rng.tz_convert("US/Eastern")
+        right = rng.tz_convert("Europe/Berlin")
+
+        result = left.join(left[:-5], how=join_type)
+        assert isinstance(result, DatetimeIndex)
+        assert result.tz == left.tz
+
+        result = left.join(right[:-5], how=join_type)
+        assert isinstance(result, DatetimeIndex)
+        assert result.tz is timezone.utc
+
+    def test_datetimeindex_union_join_empty(self, sort):
+        dti = date_range(start="1/1/2001", end="2/1/2001", freq="D")
+        empty = Index([])
+
+        result = dti.union(empty, sort=sort)
+        expected = dti.astype("O")
+        tm.assert_index_equal(result, expected)
+
+        result = dti.join(empty)
+        assert isinstance(result, DatetimeIndex)
+        tm.assert_index_equal(result, dti)
+
+    def test_join_nonunique(self):
+        idx1 = to_datetime(["2012-11-06 16:00:11.477563", "2012-11-06 16:00:11.477563"])
+        idx2 = to_datetime(["2012-11-06 15:11:09.006507", "2012-11-06 15:11:09.006507"])
+        rs = idx1.join(idx2, how="outer")
+        assert rs.is_monotonic_increasing
+
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_outer_join(self, freq):
+        # should just behave as union
+        start, end = datetime(2009, 1, 1), datetime(2010, 1, 1)
+        rng = date_range(start=start, end=end, freq=freq)
+
+        # overlapping
+        left = rng[:10]
+        right = rng[5:10]
+
+        the_join = left.join(right, how="outer")
+        assert isinstance(the_join, DatetimeIndex)
+
+        # non-overlapping, gap in middle
+        left = rng[:5]
+        right = rng[10:]
+
+        the_join = left.join(right, how="outer")
+        assert isinstance(the_join, DatetimeIndex)
+        assert the_join.freq is None
+
+        # non-overlapping, no gap
+        left = rng[:5]
+        right = rng[5:10]
+
+        the_join = left.join(right, how="outer")
+        assert isinstance(the_join, DatetimeIndex)
+
+        # overlapping, but different offset
+        other = date_range(start, end, freq=BMonthEnd())
+
+        the_join = rng.join(other, how="outer")
+        assert isinstance(the_join, DatetimeIndex)
+        assert the_join.freq is None
+
+    def test_naive_aware_conflicts(self):
+        start, end = datetime(2009, 1, 1), datetime(2010, 1, 1)
+        naive = date_range(start, end, freq=BDay(), tz=None)
+        aware = date_range(start, end, freq=BDay(), tz="Asia/Hong_Kong")
+
+        msg = "tz-naive.*tz-aware"
+        with pytest.raises(TypeError, match=msg):
+            naive.join(aware)
+
+        with pytest.raises(TypeError, match=msg):
+            aware.join(naive)
+
+    @pytest.mark.parametrize("tz", [None, "US/Pacific"])
+    def test_join_preserves_freq(self, tz):
+        # GH#32157
+        dti = date_range("2016-01-01", periods=10, tz=tz)
+        result = dti[:5].join(dti[5:], how="outer")
+        assert result.freq == dti.freq
+        tm.assert_index_equal(result, dti)
+
+        result = dti[:5].join(dti[6:], how="outer")
+        assert result.freq is None
+        expected = dti.delete(5)
+        tm.assert_index_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_npfuncs.py

@@ -0,0 +1,13 @@
+import numpy as np
+
+from pandas import date_range
+import pandas._testing as tm
+
+
+class TestSplit:
+    def test_split_non_utc(self):
+        # GH#14042
+        indices = date_range("2016-01-01 00:00:00+0200", freq="s", periods=10)
+        result = np.split(indices, indices_or_sections=[])[0]
+        expected = indices._with_freq(None)
+        tm.assert_index_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_ops.py

@@ -0,0 +1,56 @@
+from datetime import datetime
+
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    bdate_range,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndexOps:
+    def test_infer_freq(self, freq_sample):
+        # GH 11018
+        idx = date_range("2011-01-01 09:00:00", freq=freq_sample, periods=10)
+        result = DatetimeIndex(idx.asi8, freq="infer")
+        tm.assert_index_equal(idx, result)
+        assert result.freq == freq_sample
+
+
+@pytest.mark.parametrize("freq", ["B", "C"])
+class TestBusinessDatetimeIndex:
+    @pytest.fixture
+    def rng(self, freq):
+        START, END = datetime(2009, 1, 1), datetime(2010, 1, 1)
+        return bdate_range(START, END, freq=freq)
+
+    def test_comparison(self, rng):
+        d = rng[10]
+
+        comp = rng > d
+        assert comp[11]
+        assert not comp[9]
+
+    def test_copy(self, rng):
+        cp = rng.copy()
+        tm.assert_index_equal(cp, rng)
+
+    def test_identical(self, rng):
+        t1 = rng.copy()
+        t2 = rng.copy()
+        assert t1.identical(t2)
+
+        # name
+        t1 = t1.rename("foo")
+        assert t1.equals(t2)
+        assert not t1.identical(t2)
+        t2 = t2.rename("foo")
+        assert t1.identical(t2)
+
+        # freq
+        t2v = Index(t2.values)
+        assert t1.equals(t2v)
+        assert not t1.identical(t2v)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_partial_slicing.py

@@ -0,0 +1,466 @@
+""" test partial slicing on Series/Frame """
+
+from datetime import datetime
+
+import numpy as np
+import pytest
+
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    Index,
+    MultiIndex,
+    Series,
+    Timedelta,
+    Timestamp,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestSlicing:
+    def test_string_index_series_name_converted(self):
+        # GH#1644
+        df = DataFrame(
+            np.random.default_rng(2).standard_normal((10, 4)),
+            index=date_range("1/1/2000", periods=10),
+        )
+
+        result = df.loc["1/3/2000"]
+        assert result.name == df.index[2]
+
+        result = df.T["1/3/2000"]
+        assert result.name == df.index[2]
+
+    def test_stringified_slice_with_tz(self):
+        # GH#2658
+        start = "2013-01-07"
+        idx = date_range(start=start, freq="1d", periods=10, tz="US/Eastern")
+        df = DataFrame(np.arange(10), index=idx)
+        df["2013-01-14 23:44:34.437768-05:00":]  # no exception here
+
+    def test_return_type_doesnt_depend_on_monotonicity(self):
+        # GH#24892 we get Series back regardless of whether our DTI is monotonic
+        dti = date_range(start="2015-5-13 23:59:00", freq="min", periods=3)
+        ser = Series(range(3), index=dti)
+
+        # non-monotonic index
+        ser2 = Series(range(3), index=[dti[1], dti[0], dti[2]])
+
+        # key with resolution strictly lower than "min"
+        key = "2015-5-14 00"
+
+        # monotonic increasing index
+        result = ser.loc[key]
+        expected = ser.iloc[1:]
+        tm.assert_series_equal(result, expected)
+
+        # monotonic decreasing index
+        result = ser.iloc[::-1].loc[key]
+        expected = ser.iloc[::-1][:-1]
+        tm.assert_series_equal(result, expected)
+
+        # non-monotonic index
+        result2 = ser2.loc[key]
+        expected2 = ser2.iloc[::2]
+        tm.assert_series_equal(result2, expected2)
+
+    def test_return_type_doesnt_depend_on_monotonicity_higher_reso(self):
+        # GH#24892 we get Series back regardless of whether our DTI is monotonic
+        dti = date_range(start="2015-5-13 23:59:00", freq="min", periods=3)
+        ser = Series(range(3), index=dti)
+
+        # non-monotonic index
+        ser2 = Series(range(3), index=[dti[1], dti[0], dti[2]])
+
+        # key with resolution strictly *higher) than "min"
+        key = "2015-5-14 00:00:00"
+
+        # monotonic increasing index
+        result = ser.loc[key]
+        assert result == 1
+
+        # monotonic decreasing index
+        result = ser.iloc[::-1].loc[key]
+        assert result == 1
+
+        # non-monotonic index
+        result2 = ser2.loc[key]
+        assert result2 == 0
+
+    def test_monotone_DTI_indexing_bug(self):
+        # GH 19362
+        # Testing accessing the first element in a monotonic descending
+        # partial string indexing.
+
+        df = DataFrame(list(range(5)))
+        date_list = [
+            "2018-01-02",
+            "2017-02-10",
+            "2016-03-10",
+            "2015-03-15",
+            "2014-03-16",
+        ]
+        date_index = DatetimeIndex(date_list)
+        df["date"] = date_index
+        expected = DataFrame({0: list(range(5)), "date": date_index})
+        tm.assert_frame_equal(df, expected)
+
+        # We get a slice because df.index's resolution is hourly and we
+        #  are slicing with a daily-resolution string.  If both were daily,
+        #  we would get a single item back
+        dti = date_range("20170101 01:00:00", periods=3)
+        df = DataFrame({"A": [1, 2, 3]}, index=dti[::-1])
+
+        expected = DataFrame({"A": 1}, index=dti[-1:][::-1])
+        result = df.loc["2017-01-03"]
+        tm.assert_frame_equal(result, expected)
+
+        result2 = df.iloc[::-1].loc["2017-01-03"]
+        expected2 = expected.iloc[::-1]
+        tm.assert_frame_equal(result2, expected2)
+
+    def test_slice_year(self):
+        dti = date_range(freq="B", start=datetime(2005, 1, 1), periods=500)
+
+        s = Series(np.arange(len(dti)), index=dti)
+        result = s["2005"]
+        expected = s[s.index.year == 2005]
+        tm.assert_series_equal(result, expected)
+
+        df = DataFrame(np.random.default_rng(2).random((len(dti), 5)), index=dti)
+        result = df.loc["2005"]
+        expected = df[df.index.year == 2005]
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "partial_dtime",
+        [
+            "2019",
+            "2019Q4",
+            "Dec 2019",
+            "2019-12-31",
+            "2019-12-31 23",
+            "2019-12-31 23:59",
+        ],
+    )
+    def test_slice_end_of_period_resolution(self, partial_dtime):
+        # GH#31064
+        dti = date_range("2019-12-31 23:59:55.999999999", periods=10, freq="s")
+
+        ser = Series(range(10), index=dti)
+        result = ser[partial_dtime]
+        expected = ser.iloc[:5]
+        tm.assert_series_equal(result, expected)
+
+    def test_slice_quarter(self):
+        dti = date_range(freq="D", start=datetime(2000, 6, 1), periods=500)
+
+        s = Series(np.arange(len(dti)), index=dti)
+        assert len(s["2001Q1"]) == 90
+
+        df = DataFrame(np.random.default_rng(2).random((len(dti), 5)), index=dti)
+        assert len(df.loc["1Q01"]) == 90
+
+    def test_slice_month(self):
+        dti = date_range(freq="D", start=datetime(2005, 1, 1), periods=500)
+        s = Series(np.arange(len(dti)), index=dti)
+        assert len(s["2005-11"]) == 30
+
+        df = DataFrame(np.random.default_rng(2).random((len(dti), 5)), index=dti)
+        assert len(df.loc["2005-11"]) == 30
+
+        tm.assert_series_equal(s["2005-11"], s["11-2005"])
+
+    def test_partial_slice(self):
+        rng = date_range(freq="D", start=datetime(2005, 1, 1), periods=500)
+        s = Series(np.arange(len(rng)), index=rng)
+
+        result = s["2005-05":"2006-02"]
+        expected = s["20050501":"20060228"]
+        tm.assert_series_equal(result, expected)
+
+        result = s["2005-05":]
+        expected = s["20050501":]
+        tm.assert_series_equal(result, expected)
+
+        result = s[:"2006-02"]
+        expected = s[:"20060228"]
+        tm.assert_series_equal(result, expected)
+
+        result = s["2005-1-1"]
+        assert result == s.iloc[0]
+
+        with pytest.raises(KeyError, match=r"^'2004-12-31'$"):
+            s["2004-12-31"]
+
+    def test_partial_slice_daily(self):
+        rng = date_range(freq="h", start=datetime(2005, 1, 31), periods=500)
+        s = Series(np.arange(len(rng)), index=rng)
+
+        result = s["2005-1-31"]
+        tm.assert_series_equal(result, s.iloc[:24])
+
+        with pytest.raises(KeyError, match=r"^'2004-12-31 00'$"):
+            s["2004-12-31 00"]
+
+    def test_partial_slice_hourly(self):
+        rng = date_range(freq="min", start=datetime(2005, 1, 1, 20, 0, 0), periods=500)
+        s = Series(np.arange(len(rng)), index=rng)
+
+        result = s["2005-1-1"]
+        tm.assert_series_equal(result, s.iloc[: 60 * 4])
+
+        result = s["2005-1-1 20"]
+        tm.assert_series_equal(result, s.iloc[:60])
+
+        assert s["2005-1-1 20:00"] == s.iloc[0]
+        with pytest.raises(KeyError, match=r"^'2004-12-31 00:15'$"):
+            s["2004-12-31 00:15"]
+
+    def test_partial_slice_minutely(self):
+        rng = date_range(freq="s", start=datetime(2005, 1, 1, 23, 59, 0), periods=500)
+        s = Series(np.arange(len(rng)), index=rng)
+
+        result = s["2005-1-1 23:59"]
+        tm.assert_series_equal(result, s.iloc[:60])
+
+        result = s["2005-1-1"]
+        tm.assert_series_equal(result, s.iloc[:60])
+
+        assert s[Timestamp("2005-1-1 23:59:00")] == s.iloc[0]
+        with pytest.raises(KeyError, match=r"^'2004-12-31 00:00:00'$"):
+            s["2004-12-31 00:00:00"]
+
+    def test_partial_slice_second_precision(self):
+        rng = date_range(
+            start=datetime(2005, 1, 1, 0, 0, 59, microsecond=999990),
+            periods=20,
+            freq="us",
+        )
+        s = Series(np.arange(20), rng)
+
+        tm.assert_series_equal(s["2005-1-1 00:00"], s.iloc[:10])
+        tm.assert_series_equal(s["2005-1-1 00:00:59"], s.iloc[:10])
+
+        tm.assert_series_equal(s["2005-1-1 00:01"], s.iloc[10:])
+        tm.assert_series_equal(s["2005-1-1 00:01:00"], s.iloc[10:])
+
+        assert s[Timestamp("2005-1-1 00:00:59.999990")] == s.iloc[0]
+        with pytest.raises(KeyError, match="2005-1-1 00:00:00"):
+            s["2005-1-1 00:00:00"]
+
+    def test_partial_slicing_dataframe(self):
+        # GH14856
+        # Test various combinations of string slicing resolution vs.
+        # index resolution
+        # - If string resolution is less precise than index resolution,
+        # string is considered a slice
+        # - If string resolution is equal to or more precise than index
+        # resolution, string is considered an exact match
+        formats = [
+            "%Y",
+            "%Y-%m",
+            "%Y-%m-%d",
+            "%Y-%m-%d %H",
+            "%Y-%m-%d %H:%M",
+            "%Y-%m-%d %H:%M:%S",
+        ]
+        resolutions = ["year", "month", "day", "hour", "minute", "second"]
+        for rnum, resolution in enumerate(resolutions[2:], 2):
+            # we check only 'day', 'hour', 'minute' and 'second'
+            unit = Timedelta("1 " + resolution)
+            middate = datetime(2012, 1, 1, 0, 0, 0)
+            index = DatetimeIndex([middate - unit, middate, middate + unit])
+            values = [1, 2, 3]
+            df = DataFrame({"a": values}, index, dtype=np.int64)
+            assert df.index.resolution == resolution
+
+            # Timestamp with the same resolution as index
+            # Should be exact match for Series (return scalar)
+            # and raise KeyError for Frame
+            for timestamp, expected in zip(index, values):
+                ts_string = timestamp.strftime(formats[rnum])
+                # make ts_string as precise as index
+                result = df["a"][ts_string]
+                assert isinstance(result, np.int64)
+                assert result == expected
+                msg = rf"^'{ts_string}'$"
+                with pytest.raises(KeyError, match=msg):
+                    df[ts_string]
+
+            # Timestamp with resolution less precise than index
+            for fmt in formats[:rnum]:
+                for element, theslice in [[0, slice(None, 1)], [1, slice(1, None)]]:
+                    ts_string = index[element].strftime(fmt)
+
+                    # Series should return slice
+                    result = df["a"][ts_string]
+                    expected = df["a"][theslice]
+                    tm.assert_series_equal(result, expected)
+
+                    # pre-2.0 df[ts_string] was overloaded to interpret this
+                    #  as slicing along index
+                    with pytest.raises(KeyError, match=ts_string):
+                        df[ts_string]
+
+            # Timestamp with resolution more precise than index
+            # Compatible with existing key
+            # Should return scalar for Series
+            # and raise KeyError for Frame
+            for fmt in formats[rnum + 1 :]:
+                ts_string = index[1].strftime(fmt)
+                result = df["a"][ts_string]
+                assert isinstance(result, np.int64)
+                assert result == 2
+                msg = rf"^'{ts_string}'$"
+                with pytest.raises(KeyError, match=msg):
+                    df[ts_string]
+
+            # Not compatible with existing key
+            # Should raise KeyError
+            for fmt, res in list(zip(formats, resolutions))[rnum + 1 :]:
+                ts = index[1] + Timedelta("1 " + res)
+                ts_string = ts.strftime(fmt)
+                msg = rf"^'{ts_string}'$"
+                with pytest.raises(KeyError, match=msg):
+                    df["a"][ts_string]
+                with pytest.raises(KeyError, match=msg):
+                    df[ts_string]
+
+    def test_partial_slicing_with_multiindex(self):
+        # GH 4758
+        # partial string indexing with a multi-index buggy
+        df = DataFrame(
+            {
+                "ACCOUNT": ["ACCT1", "ACCT1", "ACCT1", "ACCT2"],
+                "TICKER": ["ABC", "MNP", "XYZ", "XYZ"],
+                "val": [1, 2, 3, 4],
+            },
+            index=date_range("2013-06-19 09:30:00", periods=4, freq="5min"),
+        )
+        df_multi = df.set_index(["ACCOUNT", "TICKER"], append=True)
+
+        expected = DataFrame(
+            [[1]], index=Index(["ABC"], name="TICKER"), columns=["val"]
+        )
+        result = df_multi.loc[("2013-06-19 09:30:00", "ACCT1")]
+        tm.assert_frame_equal(result, expected)
+
+        expected = df_multi.loc[
+            (Timestamp("2013-06-19 09:30:00", tz=None), "ACCT1", "ABC")
+        ]
+        result = df_multi.loc[("2013-06-19 09:30:00", "ACCT1", "ABC")]
+        tm.assert_series_equal(result, expected)
+
+        # partial string indexing on first level, scalar indexing on the other two
+        result = df_multi.loc[("2013-06-19", "ACCT1", "ABC")]
+        expected = df_multi.iloc[:1].droplevel([1, 2])
+        tm.assert_frame_equal(result, expected)
+
+    def test_partial_slicing_with_multiindex_series(self):
+        # GH 4294
+        # partial slice on a series mi
+        ser = Series(
+            range(250),
+            index=MultiIndex.from_product(
+                [date_range("2000-1-1", periods=50), range(5)]
+            ),
+        )
+
+        s2 = ser[:-1].copy()
+        expected = s2["2000-1-4"]
+        result = s2[Timestamp("2000-1-4")]
+        tm.assert_series_equal(result, expected)
+
+        result = ser[Timestamp("2000-1-4")]
+        expected = ser["2000-1-4"]
+        tm.assert_series_equal(result, expected)
+
+        df2 = DataFrame(ser)
+        expected = df2.xs("2000-1-4")
+        result = df2.loc[Timestamp("2000-1-4")]
+        tm.assert_frame_equal(result, expected)
+
+    def test_partial_slice_requires_monotonicity(self):
+        # Disallowed since 2.0 (GH 37819)
+        ser = Series(np.arange(10), date_range("2014-01-01", periods=10))
+
+        nonmonotonic = ser.iloc[[3, 5, 4]]
+        timestamp = Timestamp("2014-01-10")
+        with pytest.raises(
+            KeyError, match="Value based partial slicing on non-monotonic"
+        ):
+            nonmonotonic["2014-01-10":]
+
+        with pytest.raises(KeyError, match=r"Timestamp\('2014-01-10 00:00:00'\)"):
+            nonmonotonic[timestamp:]
+
+        with pytest.raises(
+            KeyError, match="Value based partial slicing on non-monotonic"
+        ):
+            nonmonotonic.loc["2014-01-10":]
+
+        with pytest.raises(KeyError, match=r"Timestamp\('2014-01-10 00:00:00'\)"):
+            nonmonotonic.loc[timestamp:]
+
+    def test_loc_datetime_length_one(self):
+        # GH16071
+        df = DataFrame(
+            columns=["1"],
+            index=date_range("2016-10-01T00:00:00", "2016-10-01T23:59:59"),
+        )
+        result = df.loc[datetime(2016, 10, 1) :]
+        tm.assert_frame_equal(result, df)
+
+        result = df.loc["2016-10-01T00:00:00":]
+        tm.assert_frame_equal(result, df)
+
+    @pytest.mark.parametrize(
+        "start",
+        [
+            "2018-12-02 21:50:00+00:00",
+            Timestamp("2018-12-02 21:50:00+00:00"),
+            Timestamp("2018-12-02 21:50:00+00:00").to_pydatetime(),
+        ],
+    )
+    @pytest.mark.parametrize(
+        "end",
+        [
+            "2018-12-02 21:52:00+00:00",
+            Timestamp("2018-12-02 21:52:00+00:00"),
+            Timestamp("2018-12-02 21:52:00+00:00").to_pydatetime(),
+        ],
+    )
+    def test_getitem_with_datestring_with_UTC_offset(self, start, end):
+        # GH 24076
+        idx = date_range(
+            start="2018-12-02 14:50:00-07:00",
+            end="2018-12-02 14:50:00-07:00",
+            freq="1min",
+        )
+        df = DataFrame(1, index=idx, columns=["A"])
+        result = df[start:end]
+        expected = df.iloc[0:3, :]
+        tm.assert_frame_equal(result, expected)
+
+        # GH 16785
+        start = str(start)
+        end = str(end)
+        with pytest.raises(ValueError, match="Both dates must"):
+            df[start : end[:-4] + "1:00"]
+
+        with pytest.raises(ValueError, match="The index must be timezone"):
+            df = df.tz_localize(None)
+            df[start:end]
+
+    def test_slice_reduce_to_series(self):
+        # GH 27516
+        df = DataFrame(
+            {"A": range(24)}, index=date_range("2000", periods=24, freq="ME")
+        )
+        expected = Series(
+            range(12), index=date_range("2000", periods=12, freq="ME"), name="A"
+        )
+        result = df.loc["2000", "A"]
+        tm.assert_series_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_pickle.py

@@ -0,0 +1,45 @@
+import pytest
+
+from pandas import (
+    NaT,
+    date_range,
+    to_datetime,
+)
+import pandas._testing as tm
+
+
+class TestPickle:
+    def test_pickle(self):
+        # GH#4606
+        idx = to_datetime(["2013-01-01", NaT, "2014-01-06"])
+        idx_p = tm.round_trip_pickle(idx)
+        assert idx_p[0] == idx[0]
+        assert idx_p[1] is NaT
+        assert idx_p[2] == idx[2]
+
+    def test_pickle_dont_infer_freq(self):
+        # GH#11002
+        # don't infer freq
+        idx = date_range("1750-1-1", "2050-1-1", freq="7D")
+        idx_p = tm.round_trip_pickle(idx)
+        tm.assert_index_equal(idx, idx_p)
+
+    def test_pickle_after_set_freq(self):
+        dti = date_range("20130101", periods=3, tz="US/Eastern", name="foo")
+        dti = dti._with_freq(None)
+
+        res = tm.round_trip_pickle(dti)
+        tm.assert_index_equal(res, dti)
+
+    def test_roundtrip_pickle_with_tz(self):
+        # GH#8367
+        # round-trip of timezone
+        index = date_range("20130101", periods=3, tz="US/Eastern", name="foo")
+        unpickled = tm.round_trip_pickle(index)
+        tm.assert_index_equal(index, unpickled)
+
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_pickle_unpickle(self, freq):
+        rng = date_range("2009-01-01", "2010-01-01", freq=freq)
+        unpickled = tm.round_trip_pickle(rng)
+        assert unpickled.freq == freq

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_reindex.py

@@ -0,0 +1,56 @@
+from datetime import timedelta
+
+import numpy as np
+
+from pandas import (
+    DatetimeIndex,
+    date_range,
+)
+import pandas._testing as tm
+
+
+class TestDatetimeIndexReindex:
+    def test_reindex_preserves_tz_if_target_is_empty_list_or_array(self):
+        # GH#7774
+        index = date_range("2013-01-01", periods=3, tz="US/Eastern")
+        assert str(index.reindex([])[0].tz) == "US/Eastern"
+        assert str(index.reindex(np.array([]))[0].tz) == "US/Eastern"
+
+    def test_reindex_with_same_tz_nearest(self):
+        # GH#32740
+        rng_a = date_range("2010-01-01", "2010-01-02", periods=24, tz="utc")
+        rng_b = date_range("2010-01-01", "2010-01-02", periods=23, tz="utc")
+        result1, result2 = rng_a.reindex(
+            rng_b, method="nearest", tolerance=timedelta(seconds=20)
+        )
+        expected_list1 = [
+            "2010-01-01 00:00:00",
+            "2010-01-01 01:05:27.272727272",
+            "2010-01-01 02:10:54.545454545",
+            "2010-01-01 03:16:21.818181818",
+            "2010-01-01 04:21:49.090909090",
+            "2010-01-01 05:27:16.363636363",
+            "2010-01-01 06:32:43.636363636",
+            "2010-01-01 07:38:10.909090909",
+            "2010-01-01 08:43:38.181818181",
+            "2010-01-01 09:49:05.454545454",
+            "2010-01-01 10:54:32.727272727",
+            "2010-01-01 12:00:00",
+            "2010-01-01 13:05:27.272727272",
+            "2010-01-01 14:10:54.545454545",
+            "2010-01-01 15:16:21.818181818",
+            "2010-01-01 16:21:49.090909090",
+            "2010-01-01 17:27:16.363636363",
+            "2010-01-01 18:32:43.636363636",
+            "2010-01-01 19:38:10.909090909",
+            "2010-01-01 20:43:38.181818181",
+            "2010-01-01 21:49:05.454545454",
+            "2010-01-01 22:54:32.727272727",
+            "2010-01-02 00:00:00",
+        ]
+        expected1 = DatetimeIndex(
+            expected_list1, dtype="datetime64[ns, UTC]", freq=None
+        )
+        expected2 = np.array([0] + [-1] * 21 + [23], dtype=np.dtype("intp"))
+        tm.assert_index_equal(result1, expected1)
+        tm.assert_numpy_array_equal(result2, expected2)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_scalar_compat.py

@@ -0,0 +1,329 @@
+"""
+Tests for DatetimeIndex methods behaving like their Timestamp counterparts
+"""
+
+import calendar
+from datetime import (
+    date,
+    datetime,
+    time,
+)
+import locale
+import unicodedata
+
+import numpy as np
+import pytest
+
+from pandas._libs.tslibs import timezones
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    NaT,
+    Timestamp,
+    date_range,
+    offsets,
+)
+import pandas._testing as tm
+from pandas.core.arrays import DatetimeArray
+
+
+class TestDatetimeIndexOps:
+    def test_dti_no_millisecond_field(self):
+        msg = "type object 'DatetimeIndex' has no attribute 'millisecond'"
+        with pytest.raises(AttributeError, match=msg):
+            DatetimeIndex.millisecond
+
+        msg = "'DatetimeIndex' object has no attribute 'millisecond'"
+        with pytest.raises(AttributeError, match=msg):
+            DatetimeIndex([]).millisecond
+
+    def test_dti_time(self):
+        rng = date_range("1/1/2000", freq="12min", periods=10)
+        result = Index(rng).time
+        expected = [t.time() for t in rng]
+        assert (result == expected).all()
+
+    def test_dti_date(self):
+        rng = date_range("1/1/2000", freq="12h", periods=10)
+        result = Index(rng).date
+        expected = [t.date() for t in rng]
+        assert (result == expected).all()
+
+    @pytest.mark.parametrize(
+        "dtype",
+        [None, "datetime64[ns, CET]", "datetime64[ns, EST]", "datetime64[ns, UTC]"],
+    )
+    def test_dti_date2(self, dtype):
+        # Regression test for GH#21230
+        expected = np.array([date(2018, 6, 4), NaT])
+
+        index = DatetimeIndex(["2018-06-04 10:00:00", NaT], dtype=dtype)
+        result = index.date
+
+        tm.assert_numpy_array_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "dtype",
+        [None, "datetime64[ns, CET]", "datetime64[ns, EST]", "datetime64[ns, UTC]"],
+    )
+    def test_dti_time2(self, dtype):
+        # Regression test for GH#21267
+        expected = np.array([time(10, 20, 30), NaT])
+
+        index = DatetimeIndex(["2018-06-04 10:20:30", NaT], dtype=dtype)
+        result = index.time
+
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_dti_timetz(self, tz_naive_fixture):
+        # GH#21358
+        tz = timezones.maybe_get_tz(tz_naive_fixture)
+
+        expected = np.array([time(10, 20, 30, tzinfo=tz), NaT])
+
+        index = DatetimeIndex(["2018-06-04 10:20:30", NaT], tz=tz)
+        result = index.timetz
+
+        tm.assert_numpy_array_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "field",
+        [
+            "dayofweek",
+            "day_of_week",
+            "dayofyear",
+            "day_of_year",
+            "quarter",
+            "days_in_month",
+            "is_month_start",
+            "is_month_end",
+            "is_quarter_start",
+            "is_quarter_end",
+            "is_year_start",
+            "is_year_end",
+        ],
+    )
+    def test_dti_timestamp_fields(self, field):
+        # extra fields from DatetimeIndex like quarter and week
+        idx = date_range("2020-01-01", periods=10)
+        expected = getattr(idx, field)[-1]
+
+        result = getattr(Timestamp(idx[-1]), field)
+        assert result == expected
+
+    def test_dti_nanosecond(self):
+        dti = DatetimeIndex(np.arange(10))
+        expected = Index(np.arange(10, dtype=np.int32))
+
+        tm.assert_index_equal(dti.nanosecond, expected)
+
+    @pytest.mark.parametrize("prefix", ["", "dateutil/"])
+    def test_dti_hour_tzaware(self, prefix):
+        strdates = ["1/1/2012", "3/1/2012", "4/1/2012"]
+        rng = DatetimeIndex(strdates, tz=prefix + "US/Eastern")
+        assert (rng.hour == 0).all()
+
+        # a more unusual time zone, GH#1946
+        dr = date_range(
+            "2011-10-02 00:00", freq="h", periods=10, tz=prefix + "America/Atikokan"
+        )
+
+        expected = Index(np.arange(10, dtype=np.int32))
+        tm.assert_index_equal(dr.hour, expected)
+
+    # GH#12806
+    # error: Unsupported operand types for + ("List[None]" and "List[str]")
+    @pytest.mark.parametrize(
+        "time_locale", [None] + tm.get_locales()  # type: ignore[operator]
+    )
+    def test_day_name_month_name(self, time_locale):
+        # Test Monday -> Sunday and January -> December, in that sequence
+        if time_locale is None:
+            # If the time_locale is None, day-name and month_name should
+            # return the english attributes
+            expected_days = [
+                "Monday",
+                "Tuesday",
+                "Wednesday",
+                "Thursday",
+                "Friday",
+                "Saturday",
+                "Sunday",
+            ]
+            expected_months = [
+                "January",
+                "February",
+                "March",
+                "April",
+                "May",
+                "June",
+                "July",
+                "August",
+                "September",
+                "October",
+                "November",
+                "December",
+            ]
+        else:
+            with tm.set_locale(time_locale, locale.LC_TIME):
+                expected_days = calendar.day_name[:]
+                expected_months = calendar.month_name[1:]
+
+        # GH#11128
+        dti = date_range(freq="D", start=datetime(1998, 1, 1), periods=365)
+        english_days = [
+            "Monday",
+            "Tuesday",
+            "Wednesday",
+            "Thursday",
+            "Friday",
+            "Saturday",
+            "Sunday",
+        ]
+        for day, name, eng_name in zip(range(4, 11), expected_days, english_days):
+            name = name.capitalize()
+            assert dti.day_name(locale=time_locale)[day] == name
+            assert dti.day_name(locale=None)[day] == eng_name
+            ts = Timestamp(datetime(2016, 4, day))
+            assert ts.day_name(locale=time_locale) == name
+        dti = dti.append(DatetimeIndex([NaT]))
+        assert np.isnan(dti.day_name(locale=time_locale)[-1])
+        ts = Timestamp(NaT)
+        assert np.isnan(ts.day_name(locale=time_locale))
+
+        # GH#12805
+        dti = date_range(freq="ME", start="2012", end="2013")
+        result = dti.month_name(locale=time_locale)
+        expected = Index([month.capitalize() for month in expected_months])
+
+        # work around different normalization schemes GH#22342
+        result = result.str.normalize("NFD")
+        expected = expected.str.normalize("NFD")
+
+        tm.assert_index_equal(result, expected)
+
+        for item, expected in zip(dti, expected_months):
+            result = item.month_name(locale=time_locale)
+            expected = expected.capitalize()
+
+            result = unicodedata.normalize("NFD", result)
+            expected = unicodedata.normalize("NFD", result)
+
+            assert result == expected
+        dti = dti.append(DatetimeIndex([NaT]))
+        assert np.isnan(dti.month_name(locale=time_locale)[-1])
+
+    def test_dti_week(self):
+        # GH#6538: Check that DatetimeIndex and its TimeStamp elements
+        # return the same weekofyear accessor close to new year w/ tz
+        dates = ["2013/12/29", "2013/12/30", "2013/12/31"]
+        dates = DatetimeIndex(dates, tz="Europe/Brussels")
+        expected = [52, 1, 1]
+        assert dates.isocalendar().week.tolist() == expected
+        assert [d.weekofyear for d in dates] == expected
+
+    @pytest.mark.parametrize("tz", [None, "US/Eastern"])
+    def test_dti_fields(self, tz):
+        # GH#13303
+        dti = date_range(freq="D", start=datetime(1998, 1, 1), periods=365, tz=tz)
+        assert dti.year[0] == 1998
+        assert dti.month[0] == 1
+        assert dti.day[0] == 1
+        assert dti.hour[0] == 0
+        assert dti.minute[0] == 0
+        assert dti.second[0] == 0
+        assert dti.microsecond[0] == 0
+        assert dti.dayofweek[0] == 3
+
+        assert dti.dayofyear[0] == 1
+        assert dti.dayofyear[120] == 121
+
+        assert dti.isocalendar().week.iloc[0] == 1
+        assert dti.isocalendar().week.iloc[120] == 18
+
+        assert dti.quarter[0] == 1
+        assert dti.quarter[120] == 2
+
+        assert dti.days_in_month[0] == 31
+        assert dti.days_in_month[90] == 30
+
+        assert dti.is_month_start[0]
+        assert not dti.is_month_start[1]
+        assert dti.is_month_start[31]
+        assert dti.is_quarter_start[0]
+        assert dti.is_quarter_start[90]
+        assert dti.is_year_start[0]
+        assert not dti.is_year_start[364]
+        assert not dti.is_month_end[0]
+        assert dti.is_month_end[30]
+        assert not dti.is_month_end[31]
+        assert dti.is_month_end[364]
+        assert not dti.is_quarter_end[0]
+        assert not dti.is_quarter_end[30]
+        assert dti.is_quarter_end[89]
+        assert dti.is_quarter_end[364]
+        assert not dti.is_year_end[0]
+        assert dti.is_year_end[364]
+
+        assert len(dti.year) == 365
+        assert len(dti.month) == 365
+        assert len(dti.day) == 365
+        assert len(dti.hour) == 365
+        assert len(dti.minute) == 365
+        assert len(dti.second) == 365
+        assert len(dti.microsecond) == 365
+        assert len(dti.dayofweek) == 365
+        assert len(dti.dayofyear) == 365
+        assert len(dti.isocalendar()) == 365
+        assert len(dti.quarter) == 365
+        assert len(dti.is_month_start) == 365
+        assert len(dti.is_month_end) == 365
+        assert len(dti.is_quarter_start) == 365
+        assert len(dti.is_quarter_end) == 365
+        assert len(dti.is_year_start) == 365
+        assert len(dti.is_year_end) == 365
+
+        dti.name = "name"
+
+        # non boolean accessors -> return Index
+        for accessor in DatetimeArray._field_ops:
+            res = getattr(dti, accessor)
+            assert len(res) == 365
+            assert isinstance(res, Index)
+            assert res.name == "name"
+
+        # boolean accessors -> return array
+        for accessor in DatetimeArray._bool_ops:
+            res = getattr(dti, accessor)
+            assert len(res) == 365
+            assert isinstance(res, np.ndarray)
+
+        # test boolean indexing
+        res = dti[dti.is_quarter_start]
+        exp = dti[[0, 90, 181, 273]]
+        tm.assert_index_equal(res, exp)
+        res = dti[dti.is_leap_year]
+        exp = DatetimeIndex([], freq="D", tz=dti.tz, name="name").as_unit("ns")
+        tm.assert_index_equal(res, exp)
+
+    def test_dti_is_year_quarter_start(self):
+        dti = date_range(freq="BQE-FEB", start=datetime(1998, 1, 1), periods=4)
+
+        assert sum(dti.is_quarter_start) == 0
+        assert sum(dti.is_quarter_end) == 4
+        assert sum(dti.is_year_start) == 0
+        assert sum(dti.is_year_end) == 1
+
+    def test_dti_is_month_start(self):
+        dti = DatetimeIndex(["2000-01-01", "2000-01-02", "2000-01-03"])
+
+        assert dti.is_month_start[0] == 1
+
+    def test_dti_is_month_start_custom(self):
+        # Ensure is_start/end accessors throw ValueError for CustomBusinessDay,
+        bday_egypt = offsets.CustomBusinessDay(weekmask="Sun Mon Tue Wed Thu")
+        dti = date_range(datetime(2013, 4, 30), periods=5, freq=bday_egypt)
+        msg = "Custom business days is not supported by is_month_start"
+        with pytest.raises(ValueError, match=msg):
+            dti.is_month_start

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_setops.py

@@ -0,0 +1,666 @@
+from datetime import (
+    datetime,
+    timezone,
+)
+
+import numpy as np
+import pytest
+import pytz
+
+import pandas.util._test_decorators as td
+
+import pandas as pd
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    Index,
+    Series,
+    Timestamp,
+    bdate_range,
+    date_range,
+)
+import pandas._testing as tm
+
+from pandas.tseries.offsets import (
+    BMonthEnd,
+    Minute,
+    MonthEnd,
+)
+
+START, END = datetime(2009, 1, 1), datetime(2010, 1, 1)
+
+
+class TestDatetimeIndexSetOps:
+    tz = [
+        None,
+        "UTC",
+        "Asia/Tokyo",
+        "US/Eastern",
+        "dateutil/Asia/Singapore",
+        "dateutil/US/Pacific",
+    ]
+
+    # TODO: moved from test_datetimelike; dedup with version below
+    def test_union2(self, sort):
+        everything = date_range("2020-01-01", periods=10)
+        first = everything[:5]
+        second = everything[5:]
+        union = first.union(second, sort=sort)
+        tm.assert_index_equal(union, everything)
+
+    @pytest.mark.parametrize("box", [np.array, Series, list])
+    def test_union3(self, sort, box):
+        everything = date_range("2020-01-01", periods=10)
+        first = everything[:5]
+        second = everything[5:]
+
+        # GH 10149 support listlike inputs other than Index objects
+        expected = first.union(second, sort=sort)
+        case = box(second.values)
+        result = first.union(case, sort=sort)
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("tz", tz)
+    def test_union(self, tz, sort):
+        rng1 = date_range("1/1/2000", freq="D", periods=5, tz=tz)
+        other1 = date_range("1/6/2000", freq="D", periods=5, tz=tz)
+        expected1 = date_range("1/1/2000", freq="D", periods=10, tz=tz)
+        expected1_notsorted = DatetimeIndex(list(other1) + list(rng1))
+
+        rng2 = date_range("1/1/2000", freq="D", periods=5, tz=tz)
+        other2 = date_range("1/4/2000", freq="D", periods=5, tz=tz)
+        expected2 = date_range("1/1/2000", freq="D", periods=8, tz=tz)
+        expected2_notsorted = DatetimeIndex(list(other2) + list(rng2[:3]))
+
+        rng3 = date_range("1/1/2000", freq="D", periods=5, tz=tz)
+        other3 = DatetimeIndex([], tz=tz).as_unit("ns")
+        expected3 = date_range("1/1/2000", freq="D", periods=5, tz=tz)
+        expected3_notsorted = rng3
+
+        for rng, other, exp, exp_notsorted in [
+            (rng1, other1, expected1, expected1_notsorted),
+            (rng2, other2, expected2, expected2_notsorted),
+            (rng3, other3, expected3, expected3_notsorted),
+        ]:
+            result_union = rng.union(other, sort=sort)
+            tm.assert_index_equal(result_union, exp)
+
+            result_union = other.union(rng, sort=sort)
+            if sort is None:
+                tm.assert_index_equal(result_union, exp)
+            else:
+                tm.assert_index_equal(result_union, exp_notsorted)
+
+    def test_union_coverage(self, sort):
+        idx = DatetimeIndex(["2000-01-03", "2000-01-01", "2000-01-02"])
+        ordered = DatetimeIndex(idx.sort_values(), freq="infer")
+        result = ordered.union(idx, sort=sort)
+        tm.assert_index_equal(result, ordered)
+
+        result = ordered[:0].union(ordered, sort=sort)
+        tm.assert_index_equal(result, ordered)
+        assert result.freq == ordered.freq
+
+    def test_union_bug_1730(self, sort):
+        rng_a = date_range("1/1/2012", periods=4, freq="3h")
+        rng_b = date_range("1/1/2012", periods=4, freq="4h")
+
+        result = rng_a.union(rng_b, sort=sort)
+        exp = list(rng_a) + list(rng_b[1:])
+        if sort is None:
+            exp = DatetimeIndex(sorted(exp))
+        else:
+            exp = DatetimeIndex(exp)
+        tm.assert_index_equal(result, exp)
+
+    def test_union_bug_1745(self, sort):
+        left = DatetimeIndex(["2012-05-11 15:19:49.695000"])
+        right = DatetimeIndex(
+            [
+                "2012-05-29 13:04:21.322000",
+                "2012-05-11 15:27:24.873000",
+                "2012-05-11 15:31:05.350000",
+            ]
+        )
+
+        result = left.union(right, sort=sort)
+        exp = DatetimeIndex(
+            [
+                "2012-05-11 15:19:49.695000",
+                "2012-05-29 13:04:21.322000",
+                "2012-05-11 15:27:24.873000",
+                "2012-05-11 15:31:05.350000",
+            ]
+        )
+        if sort is None:
+            exp = exp.sort_values()
+        tm.assert_index_equal(result, exp)
+
+    def test_union_bug_4564(self, sort):
+        from pandas import DateOffset
+
+        left = date_range("2013-01-01", "2013-02-01")
+        right = left + DateOffset(minutes=15)
+
+        result = left.union(right, sort=sort)
+        exp = list(left) + list(right)
+        if sort is None:
+            exp = DatetimeIndex(sorted(exp))
+        else:
+            exp = DatetimeIndex(exp)
+        tm.assert_index_equal(result, exp)
+
+    def test_union_freq_both_none(self, sort):
+        # GH11086
+        expected = bdate_range("20150101", periods=10)
+        expected._data.freq = None
+
+        result = expected.union(expected, sort=sort)
+        tm.assert_index_equal(result, expected)
+        assert result.freq is None
+
+    def test_union_freq_infer(self):
+        # When taking the union of two DatetimeIndexes, we infer
+        #  a freq even if the arguments don't have freq.  This matches
+        #  TimedeltaIndex behavior.
+        dti = date_range("2016-01-01", periods=5)
+        left = dti[[0, 1, 3, 4]]
+        right = dti[[2, 3, 1]]
+
+        assert left.freq is None
+        assert right.freq is None
+
+        result = left.union(right)
+        tm.assert_index_equal(result, dti)
+        assert result.freq == "D"
+
+    def test_union_dataframe_index(self):
+        rng1 = date_range("1/1/1999", "1/1/2012", freq="MS")
+        s1 = Series(np.random.default_rng(2).standard_normal(len(rng1)), rng1)
+
+        rng2 = date_range("1/1/1980", "12/1/2001", freq="MS")
+        s2 = Series(np.random.default_rng(2).standard_normal(len(rng2)), rng2)
+        df = DataFrame({"s1": s1, "s2": s2})
+
+        exp = date_range("1/1/1980", "1/1/2012", freq="MS")
+        tm.assert_index_equal(df.index, exp)
+
+    def test_union_with_DatetimeIndex(self, sort):
+        i1 = Index(np.arange(0, 20, 2, dtype=np.int64))
+        i2 = date_range(start="2012-01-03 00:00:00", periods=10, freq="D")
+        # Works
+        i1.union(i2, sort=sort)
+        # Fails with "AttributeError: can't set attribute"
+        i2.union(i1, sort=sort)
+
+    def test_union_same_timezone_different_units(self):
+        # GH 55238
+        idx1 = date_range("2000-01-01", periods=3, tz="UTC").as_unit("ms")
+        idx2 = date_range("2000-01-01", periods=3, tz="UTC").as_unit("us")
+        result = idx1.union(idx2)
+        expected = date_range("2000-01-01", periods=3, tz="UTC").as_unit("us")
+        tm.assert_index_equal(result, expected)
+
+    # TODO: moved from test_datetimelike; de-duplicate with version below
+    def test_intersection2(self):
+        first = date_range("2020-01-01", periods=10)
+        second = first[5:]
+        intersect = first.intersection(second)
+        tm.assert_index_equal(intersect, second)
+
+        # GH 10149
+        cases = [klass(second.values) for klass in [np.array, Series, list]]
+        for case in cases:
+            result = first.intersection(case)
+            tm.assert_index_equal(result, second)
+
+        third = Index(["a", "b", "c"])
+        result = first.intersection(third)
+        expected = Index([], dtype=object)
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "tz", [None, "Asia/Tokyo", "US/Eastern", "dateutil/US/Pacific"]
+    )
+    def test_intersection(self, tz, sort):
+        # GH 4690 (with tz)
+        base = date_range("6/1/2000", "6/30/2000", freq="D", name="idx")
+
+        # if target has the same name, it is preserved
+        rng2 = date_range("5/15/2000", "6/20/2000", freq="D", name="idx")
+        expected2 = date_range("6/1/2000", "6/20/2000", freq="D", name="idx")
+
+        # if target name is different, it will be reset
+        rng3 = date_range("5/15/2000", "6/20/2000", freq="D", name="other")
+        expected3 = date_range("6/1/2000", "6/20/2000", freq="D", name=None)
+
+        rng4 = date_range("7/1/2000", "7/31/2000", freq="D", name="idx")
+        expected4 = DatetimeIndex([], freq="D", name="idx", dtype="M8[ns]")
+
+        for rng, expected in [
+            (rng2, expected2),
+            (rng3, expected3),
+            (rng4, expected4),
+        ]:
+            result = base.intersection(rng)
+            tm.assert_index_equal(result, expected)
+            assert result.freq == expected.freq
+
+        # non-monotonic
+        base = DatetimeIndex(
+            ["2011-01-05", "2011-01-04", "2011-01-02", "2011-01-03"], tz=tz, name="idx"
+        ).as_unit("ns")
+
+        rng2 = DatetimeIndex(
+            ["2011-01-04", "2011-01-02", "2011-02-02", "2011-02-03"], tz=tz, name="idx"
+        ).as_unit("ns")
+        expected2 = DatetimeIndex(
+            ["2011-01-04", "2011-01-02"], tz=tz, name="idx"
+        ).as_unit("ns")
+
+        rng3 = DatetimeIndex(
+            ["2011-01-04", "2011-01-02", "2011-02-02", "2011-02-03"],
+            tz=tz,
+            name="other",
+        ).as_unit("ns")
+        expected3 = DatetimeIndex(
+            ["2011-01-04", "2011-01-02"], tz=tz, name=None
+        ).as_unit("ns")
+
+        # GH 7880
+        rng4 = date_range("7/1/2000", "7/31/2000", freq="D", tz=tz, name="idx")
+        expected4 = DatetimeIndex([], tz=tz, name="idx").as_unit("ns")
+        assert expected4.freq is None
+
+        for rng, expected in [
+            (rng2, expected2),
+            (rng3, expected3),
+            (rng4, expected4),
+        ]:
+            result = base.intersection(rng, sort=sort)
+            if sort is None:
+                expected = expected.sort_values()
+            tm.assert_index_equal(result, expected)
+            assert result.freq == expected.freq
+
+    # parametrize over both anchored and non-anchored freqs, as they
+    #  have different code paths
+    @pytest.mark.parametrize("freq", ["min", "B"])
+    def test_intersection_empty(self, tz_aware_fixture, freq):
+        # empty same freq GH2129
+        tz = tz_aware_fixture
+        rng = date_range("6/1/2000", "6/15/2000", freq=freq, tz=tz)
+        result = rng[0:0].intersection(rng)
+        assert len(result) == 0
+        assert result.freq == rng.freq
+
+        result = rng.intersection(rng[0:0])
+        assert len(result) == 0
+        assert result.freq == rng.freq
+
+        # no overlap GH#33604
+        check_freq = freq != "min"  # We don't preserve freq on non-anchored offsets
+        result = rng[:3].intersection(rng[-3:])
+        tm.assert_index_equal(result, rng[:0])
+        if check_freq:
+            # We don't preserve freq on non-anchored offsets
+            assert result.freq == rng.freq
+
+        # swapped left and right
+        result = rng[-3:].intersection(rng[:3])
+        tm.assert_index_equal(result, rng[:0])
+        if check_freq:
+            # We don't preserve freq on non-anchored offsets
+            assert result.freq == rng.freq
+
+    def test_intersection_bug_1708(self):
+        from pandas import DateOffset
+
+        index_1 = date_range("1/1/2012", periods=4, freq="12h")
+        index_2 = index_1 + DateOffset(hours=1)
+
+        result = index_1.intersection(index_2)
+        assert len(result) == 0
+
+    @pytest.mark.parametrize("tz", tz)
+    def test_difference(self, tz, sort):
+        rng_dates = ["1/2/2000", "1/3/2000", "1/1/2000", "1/4/2000", "1/5/2000"]
+
+        rng1 = DatetimeIndex(rng_dates, tz=tz)
+        other1 = date_range("1/6/2000", freq="D", periods=5, tz=tz)
+        expected1 = DatetimeIndex(rng_dates, tz=tz)
+
+        rng2 = DatetimeIndex(rng_dates, tz=tz)
+        other2 = date_range("1/4/2000", freq="D", periods=5, tz=tz)
+        expected2 = DatetimeIndex(rng_dates[:3], tz=tz)
+
+        rng3 = DatetimeIndex(rng_dates, tz=tz)
+        other3 = DatetimeIndex([], tz=tz)
+        expected3 = DatetimeIndex(rng_dates, tz=tz)
+
+        for rng, other, expected in [
+            (rng1, other1, expected1),
+            (rng2, other2, expected2),
+            (rng3, other3, expected3),
+        ]:
+            result_diff = rng.difference(other, sort)
+            if sort is None and len(other):
+                # We dont sort (yet?) when empty GH#24959
+                expected = expected.sort_values()
+            tm.assert_index_equal(result_diff, expected)
+
+    def test_difference_freq(self, sort):
+        # GH14323: difference of DatetimeIndex should not preserve frequency
+
+        index = date_range("20160920", "20160925", freq="D")
+        other = date_range("20160921", "20160924", freq="D")
+        expected = DatetimeIndex(["20160920", "20160925"], dtype="M8[ns]", freq=None)
+        idx_diff = index.difference(other, sort)
+        tm.assert_index_equal(idx_diff, expected)
+        tm.assert_attr_equal("freq", idx_diff, expected)
+
+        # preserve frequency when the difference is a contiguous
+        # subset of the original range
+        other = date_range("20160922", "20160925", freq="D")
+        idx_diff = index.difference(other, sort)
+        expected = DatetimeIndex(["20160920", "20160921"], dtype="M8[ns]", freq="D")
+        tm.assert_index_equal(idx_diff, expected)
+        tm.assert_attr_equal("freq", idx_diff, expected)
+
+    def test_datetimeindex_diff(self, sort):
+        dti1 = date_range(freq="QE-JAN", start=datetime(1997, 12, 31), periods=100)
+        dti2 = date_range(freq="QE-JAN", start=datetime(1997, 12, 31), periods=98)
+        assert len(dti1.difference(dti2, sort)) == 2
+
+    @pytest.mark.parametrize("tz", [None, "Asia/Tokyo", "US/Eastern"])
+    def test_setops_preserve_freq(self, tz):
+        rng = date_range("1/1/2000", "1/1/2002", name="idx", tz=tz)
+
+        result = rng[:50].union(rng[50:100])
+        assert result.name == rng.name
+        assert result.freq == rng.freq
+        assert result.tz == rng.tz
+
+        result = rng[:50].union(rng[30:100])
+        assert result.name == rng.name
+        assert result.freq == rng.freq
+        assert result.tz == rng.tz
+
+        result = rng[:50].union(rng[60:100])
+        assert result.name == rng.name
+        assert result.freq is None
+        assert result.tz == rng.tz
+
+        result = rng[:50].intersection(rng[25:75])
+        assert result.name == rng.name
+        assert result.freqstr == "D"
+        assert result.tz == rng.tz
+
+        nofreq = DatetimeIndex(list(rng[25:75]), name="other")
+        result = rng[:50].union(nofreq)
+        assert result.name is None
+        assert result.freq == rng.freq
+        assert result.tz == rng.tz
+
+        result = rng[:50].intersection(nofreq)
+        assert result.name is None
+        assert result.freq == rng.freq
+        assert result.tz == rng.tz
+
+    def test_intersection_non_tick_no_fastpath(self):
+        # GH#42104
+        dti = DatetimeIndex(
+            [
+                "2018-12-31",
+                "2019-03-31",
+                "2019-06-30",
+                "2019-09-30",
+                "2019-12-31",
+                "2020-03-31",
+            ],
+            freq="QE-DEC",
+        )
+        result = dti[::2].intersection(dti[1::2])
+        expected = dti[:0]
+        tm.assert_index_equal(result, expected)
+
+    def test_dti_intersection(self):
+        rng = date_range("1/1/2011", periods=100, freq="h", tz="utc")
+
+        left = rng[10:90][::-1]
+        right = rng[20:80][::-1]
+
+        assert left.tz == rng.tz
+        result = left.intersection(right)
+        assert result.tz == left.tz
+
+    # Note: not difference, as there is no symmetry requirement there
+    @pytest.mark.parametrize("setop", ["union", "intersection", "symmetric_difference"])
+    def test_dti_setop_aware(self, setop):
+        # non-overlapping
+        # GH#39328 as of 2.0 we cast these to UTC instead of object
+        rng = date_range("2012-11-15 00:00:00", periods=6, freq="h", tz="US/Central")
+
+        rng2 = date_range("2012-11-15 12:00:00", periods=6, freq="h", tz="US/Eastern")
+
+        result = getattr(rng, setop)(rng2)
+
+        left = rng.tz_convert("UTC")
+        right = rng2.tz_convert("UTC")
+        expected = getattr(left, setop)(right)
+        tm.assert_index_equal(result, expected)
+        assert result.tz == left.tz
+        if len(result):
+            assert result[0].tz is timezone.utc
+            assert result[-1].tz is timezone.utc
+
+    def test_dti_union_mixed(self):
+        # GH#21671
+        rng = DatetimeIndex([Timestamp("2011-01-01"), pd.NaT])
+        rng2 = DatetimeIndex(["2012-01-01", "2012-01-02"], tz="Asia/Tokyo")
+        result = rng.union(rng2)
+        expected = Index(
+            [
+                Timestamp("2011-01-01"),
+                pd.NaT,
+                Timestamp("2012-01-01", tz="Asia/Tokyo"),
+                Timestamp("2012-01-02", tz="Asia/Tokyo"),
+            ],
+            dtype=object,
+        )
+        tm.assert_index_equal(result, expected)
+
+
+class TestBusinessDatetimeIndex:
+    def test_union(self, sort):
+        rng = bdate_range(START, END)
+        # overlapping
+        left = rng[:10]
+        right = rng[5:10]
+
+        the_union = left.union(right, sort=sort)
+        assert isinstance(the_union, DatetimeIndex)
+
+        # non-overlapping, gap in middle
+        left = rng[:5]
+        right = rng[10:]
+
+        the_union = left.union(right, sort=sort)
+        assert isinstance(the_union, Index)
+
+        # non-overlapping, no gap
+        left = rng[:5]
+        right = rng[5:10]
+
+        the_union = left.union(right, sort=sort)
+        assert isinstance(the_union, DatetimeIndex)
+
+        # order does not matter
+        if sort is None:
+            tm.assert_index_equal(right.union(left, sort=sort), the_union)
+        else:
+            expected = DatetimeIndex(list(right) + list(left))
+            tm.assert_index_equal(right.union(left, sort=sort), expected)
+
+        # overlapping, but different offset
+        rng = date_range(START, END, freq=BMonthEnd())
+
+        the_union = rng.union(rng, sort=sort)
+        assert isinstance(the_union, DatetimeIndex)
+
+    def test_union_not_cacheable(self, sort):
+        rng = date_range("1/1/2000", periods=50, freq=Minute())
+        rng1 = rng[10:]
+        rng2 = rng[:25]
+        the_union = rng1.union(rng2, sort=sort)
+        if sort is None:
+            tm.assert_index_equal(the_union, rng)
+        else:
+            expected = DatetimeIndex(list(rng[10:]) + list(rng[:10]))
+            tm.assert_index_equal(the_union, expected)
+
+        rng1 = rng[10:]
+        rng2 = rng[15:35]
+        the_union = rng1.union(rng2, sort=sort)
+        expected = rng[10:]
+        tm.assert_index_equal(the_union, expected)
+
+    def test_intersection(self):
+        rng = date_range("1/1/2000", periods=50, freq=Minute())
+        rng1 = rng[10:]
+        rng2 = rng[:25]
+        the_int = rng1.intersection(rng2)
+        expected = rng[10:25]
+        tm.assert_index_equal(the_int, expected)
+        assert isinstance(the_int, DatetimeIndex)
+        assert the_int.freq == rng.freq
+
+        the_int = rng1.intersection(rng2)
+        tm.assert_index_equal(the_int, expected)
+
+        # non-overlapping
+        the_int = rng[:10].intersection(rng[10:])
+        expected = DatetimeIndex([]).as_unit("ns")
+        tm.assert_index_equal(the_int, expected)
+
+    def test_intersection_bug(self):
+        # GH #771
+        a = bdate_range("11/30/2011", "12/31/2011")
+        b = bdate_range("12/10/2011", "12/20/2011")
+        result = a.intersection(b)
+        tm.assert_index_equal(result, b)
+        assert result.freq == b.freq
+
+    def test_intersection_list(self):
+        # GH#35876
+        # values is not an Index -> no name -> retain "a"
+        values = [Timestamp("2020-01-01"), Timestamp("2020-02-01")]
+        idx = DatetimeIndex(values, name="a")
+        res = idx.intersection(values)
+        tm.assert_index_equal(res, idx)
+
+    def test_month_range_union_tz_pytz(self, sort):
+        tz = pytz.timezone("US/Eastern")
+
+        early_start = datetime(2011, 1, 1)
+        early_end = datetime(2011, 3, 1)
+
+        late_start = datetime(2011, 3, 1)
+        late_end = datetime(2011, 5, 1)
+
+        early_dr = date_range(start=early_start, end=early_end, tz=tz, freq=MonthEnd())
+        late_dr = date_range(start=late_start, end=late_end, tz=tz, freq=MonthEnd())
+
+        early_dr.union(late_dr, sort=sort)
+
+    @td.skip_if_windows
+    def test_month_range_union_tz_dateutil(self, sort):
+        from pandas._libs.tslibs.timezones import dateutil_gettz
+
+        tz = dateutil_gettz("US/Eastern")
+
+        early_start = datetime(2011, 1, 1)
+        early_end = datetime(2011, 3, 1)
+
+        late_start = datetime(2011, 3, 1)
+        late_end = datetime(2011, 5, 1)
+
+        early_dr = date_range(start=early_start, end=early_end, tz=tz, freq=MonthEnd())
+        late_dr = date_range(start=late_start, end=late_end, tz=tz, freq=MonthEnd())
+
+        early_dr.union(late_dr, sort=sort)
+
+    @pytest.mark.parametrize("sort", [False, None])
+    def test_intersection_duplicates(self, sort):
+        # GH#38196
+        idx1 = Index(
+            [
+                Timestamp("2019-12-13"),
+                Timestamp("2019-12-12"),
+                Timestamp("2019-12-12"),
+            ]
+        )
+        result = idx1.intersection(idx1, sort=sort)
+        expected = Index([Timestamp("2019-12-13"), Timestamp("2019-12-12")])
+        tm.assert_index_equal(result, expected)
+
+
+class TestCustomDatetimeIndex:
+    def test_union(self, sort):
+        # overlapping
+        rng = bdate_range(START, END, freq="C")
+        left = rng[:10]
+        right = rng[5:10]
+
+        the_union = left.union(right, sort=sort)
+        assert isinstance(the_union, DatetimeIndex)
+
+        # non-overlapping, gap in middle
+        left = rng[:5]
+        right = rng[10:]
+
+        the_union = left.union(right, sort)
+        assert isinstance(the_union, Index)
+
+        # non-overlapping, no gap
+        left = rng[:5]
+        right = rng[5:10]
+
+        the_union = left.union(right, sort=sort)
+        assert isinstance(the_union, DatetimeIndex)
+
+        # order does not matter
+        if sort is None:
+            tm.assert_index_equal(right.union(left, sort=sort), the_union)
+
+        # overlapping, but different offset
+        rng = date_range(START, END, freq=BMonthEnd())
+
+        the_union = rng.union(rng, sort=sort)
+        assert isinstance(the_union, DatetimeIndex)
+
+    def test_intersection_bug(self):
+        # GH #771
+        a = bdate_range("11/30/2011", "12/31/2011", freq="C")
+        b = bdate_range("12/10/2011", "12/20/2011", freq="C")
+        result = a.intersection(b)
+        tm.assert_index_equal(result, b)
+        assert result.freq == b.freq
+
+    @pytest.mark.parametrize(
+        "tz", [None, "UTC", "Europe/Berlin", pytz.FixedOffset(-60)]
+    )
+    def test_intersection_dst_transition(self, tz):
+        # GH 46702: Europe/Berlin has DST transition
+        idx1 = date_range("2020-03-27", periods=5, freq="D", tz=tz)
+        idx2 = date_range("2020-03-30", periods=5, freq="D", tz=tz)
+        result = idx1.intersection(idx2)
+        expected = date_range("2020-03-30", periods=2, freq="D", tz=tz)
+        tm.assert_index_equal(result, expected)
+
+        # GH#45863 same problem for union
+        index1 = date_range("2021-10-28", periods=3, freq="D", tz="Europe/London")
+        index2 = date_range("2021-10-30", periods=4, freq="D", tz="Europe/London")
+        result = index1.union(index2)
+        expected = date_range("2021-10-28", periods=6, freq="D", tz="Europe/London")
+        tm.assert_index_equal(result, expected)

venv/lib/python3.12/site-packages/pandas/tests/indexes/datetimes/test_timezones.py

@@ -0,0 +1,251 @@
+"""
+Tests for DatetimeIndex timezone-related methods
+"""
+from datetime import (
+    datetime,
+    timedelta,
+    timezone,
+    tzinfo,
+)
+
+from dateutil.tz import gettz
+import numpy as np
+import pytest
+import pytz
+
+from pandas._libs.tslibs import (
+    conversion,
+    timezones,
+)
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    Timestamp,
+    bdate_range,
+    date_range,
+    isna,
+    to_datetime,
+)
+import pandas._testing as tm
+
+
+class FixedOffset(tzinfo):
+    """Fixed offset in minutes east from UTC."""
+
+    def __init__(self, offset, name) -> None:
+        self.__offset = timedelta(minutes=offset)
+        self.__name = name
+
+    def utcoffset(self, dt):
+        return self.__offset
+
+    def tzname(self, dt):
+        return self.__name
+
+    def dst(self, dt):
+        return timedelta(0)
+
+
+fixed_off_no_name = FixedOffset(-330, None)
+
+
+class TestDatetimeIndexTimezones:
+    # -------------------------------------------------------------
+    # Unsorted
+
+    def test_dti_drop_dont_lose_tz(self):
+        # GH#2621
+        ind = date_range("2012-12-01", periods=10, tz="utc")
+        ind = ind.drop(ind[-1])
+
+        assert ind.tz is not None
+
+    def test_dti_tz_conversion_freq(self, tz_naive_fixture):
+        # GH25241
+        t3 = DatetimeIndex(["2019-01-01 10:00"], freq="h")
+        assert t3.tz_localize(tz=tz_naive_fixture).freq == t3.freq
+        t4 = DatetimeIndex(["2019-01-02 12:00"], tz="UTC", freq="min")
+        assert t4.tz_convert(tz="UTC").freq == t4.freq
+
+    def test_drop_dst_boundary(self):
+        # see gh-18031
+        tz = "Europe/Brussels"
+        freq = "15min"
+
+        start = Timestamp("201710290100", tz=tz)
+        end = Timestamp("201710290300", tz=tz)
+        index = date_range(start=start, end=end, freq=freq)
+
+        expected = DatetimeIndex(
+            [
+                "201710290115",
+                "201710290130",
+                "201710290145",
+                "201710290200",
+                "201710290215",
+                "201710290230",
+                "201710290245",
+                "201710290200",
+                "201710290215",
+                "201710290230",
+                "201710290245",
+                "201710290300",
+            ],
+            dtype="M8[ns, Europe/Brussels]",
+            freq=freq,
+            ambiguous=[
+                True,
+                True,
+                True,
+                True,
+                True,
+                True,
+                True,
+                False,
+                False,
+                False,
+                False,
+                False,
+            ],
+        )
+        result = index.drop(index[0])
+        tm.assert_index_equal(result, expected)
+
+    def test_date_range_localize(self, unit):
+        rng = date_range(
+            "3/11/2012 03:00", periods=15, freq="h", tz="US/Eastern", unit=unit
+        )
+        rng2 = DatetimeIndex(
+            ["3/11/2012 03:00", "3/11/2012 04:00"], dtype=f"M8[{unit}, US/Eastern]"
+        )
+        rng3 = date_range("3/11/2012 03:00", periods=15, freq="h", unit=unit)
+        rng3 = rng3.tz_localize("US/Eastern")
+
+        tm.assert_index_equal(rng._with_freq(None), rng3)
+
+        # DST transition time
+        val = rng[0]
+        exp = Timestamp("3/11/2012 03:00", tz="US/Eastern")
+
+        assert val.hour == 3
+        assert exp.hour == 3
+        assert val == exp  # same UTC value
+        tm.assert_index_equal(rng[:2], rng2)
+
+    def test_date_range_localize2(self, unit):
+        # Right before the DST transition
+        rng = date_range(
+            "3/11/2012 00:00", periods=2, freq="h", tz="US/Eastern", unit=unit
+        )
+        rng2 = DatetimeIndex(
+            ["3/11/2012 00:00", "3/11/2012 01:00"],
+            dtype=f"M8[{unit}, US/Eastern]",
+            freq="h",
+        )
+        tm.assert_index_equal(rng, rng2)
+        exp = Timestamp("3/11/2012 00:00", tz="US/Eastern")
+        assert exp.hour == 0
+        assert rng[0] == exp
+        exp = Timestamp("3/11/2012 01:00", tz="US/Eastern")
+        assert exp.hour == 1
+        assert rng[1] == exp
+
+        rng = date_range(
+            "3/11/2012 00:00", periods=10, freq="h", tz="US/Eastern", unit=unit
+        )
+        assert rng[2].hour == 3
+
+    def test_timestamp_equality_different_timezones(self):
+        utc_range = date_range("1/1/2000", periods=20, tz="UTC")
+        eastern_range = utc_range.tz_convert("US/Eastern")
+        berlin_range = utc_range.tz_convert("Europe/Berlin")
+
+        for a, b, c in zip(utc_range, eastern_range, berlin_range):
+            assert a == b
+            assert b == c
+            assert a == c
+
+        assert (utc_range == eastern_range).all()
+        assert (utc_range == berlin_range).all()
+        assert (berlin_range == eastern_range).all()
+
+    def test_dti_equals_with_tz(self):
+        left = date_range("1/1/2011", periods=100, freq="h", tz="utc")
+        right = date_range("1/1/2011", periods=100, freq="h", tz="US/Eastern")
+
+        assert not left.equals(right)
+
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_dti_tz_nat(self, tzstr):
+        idx = DatetimeIndex([Timestamp("2013-1-1", tz=tzstr), pd.NaT])
+
+        assert isna(idx[1])
+        assert idx[0].tzinfo is not None
+
+    @pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_utc_box_timestamp_and_localize(self, tzstr):
+        tz = timezones.maybe_get_tz(tzstr)
+
+        rng = date_range("3/11/2012", "3/12/2012", freq="h", tz="utc")
+        rng_eastern = rng.tz_convert(tzstr)
+
+        expected = rng[-1].astimezone(tz)
+
+        stamp = rng_eastern[-1]
+        assert stamp == expected
+        assert stamp.tzinfo == expected.tzinfo
+
+        # right tzinfo
+        rng = date_range("3/13/2012", "3/14/2012", freq="h", tz="utc")
+        rng_eastern = rng.tz_convert(tzstr)
+        # test not valid for dateutil timezones.
+        # assert 'EDT' in repr(rng_eastern[0].tzinfo)
+        assert "EDT" in repr(rng_eastern[0].tzinfo) or "tzfile" in repr(
+            rng_eastern[0].tzinfo
+        )
+
+    @pytest.mark.parametrize("tz", [pytz.timezone("US/Central"), gettz("US/Central")])
+    def test_with_tz(self, tz):
+        # just want it to work
+        start = datetime(2011, 3, 12, tzinfo=pytz.utc)
+        dr = bdate_range(start, periods=50, freq=pd.offsets.Hour())
+        assert dr.tz is pytz.utc
+
+        # DateRange with naive datetimes
+        dr = bdate_range("1/1/2005", "1/1/2009", tz=pytz.utc)
+        dr = bdate_range("1/1/2005", "1/1/2009", tz=tz)
+
+        # normalized
+        central = dr.tz_convert(tz)
+        assert central.tz is tz
+        naive = central[0].to_pydatetime().replace(tzinfo=None)
+        comp = conversion.localize_pydatetime(naive, tz).tzinfo
+        assert central[0].tz is comp
+
+        # compare vs a localized tz
+        naive = dr[0].to_pydatetime().replace(tzinfo=None)
+        comp = conversion.localize_pydatetime(naive, tz).tzinfo
+        assert central[0].tz is comp
+
+        # datetimes with tzinfo set
+        dr = bdate_range(
+            datetime(2005, 1, 1, tzinfo=pytz.utc), datetime(2009, 1, 1, tzinfo=pytz.utc)
+        )
+        msg = "Start and end cannot both be tz-aware with different timezones"
+        with pytest.raises(Exception, match=msg):
+            bdate_range(datetime(2005, 1, 1, tzinfo=pytz.utc), "1/1/2009", tz=tz)
+
+    @pytest.mark.parametrize("tz", [pytz.timezone("US/Eastern"), gettz("US/Eastern")])
+    def test_dti_convert_tz_aware_datetime_datetime(self, tz):
+        # GH#1581
+        dates = [datetime(2000, 1, 1), datetime(2000, 1, 2), datetime(2000, 1, 3)]
+
+        dates_aware = [conversion.localize_pydatetime(x, tz) for x in dates]
+        result = DatetimeIndex(dates_aware).as_unit("ns")
+        assert timezones.tz_compare(result.tz, tz)
+
+        converted = to_datetime(dates_aware, utc=True).as_unit("ns")
+        ex_vals = np.array([Timestamp(x).as_unit("ns")._value for x in dates_aware])
+        tm.assert_numpy_array_equal(converted.asi8, ex_vals)
+        assert converted.tz is timezone.utc