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env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_drop_duplicates.py

@@ -0,0 +1,89 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    PeriodIndex,
+    Series,
+    date_range,
+    period_range,
+    timedelta_range,
+)
+import pandas._testing as tm
+
+
+class DropDuplicates:
+    def test_drop_duplicates_metadata(self, idx):
+        # GH#10115
+        result = idx.drop_duplicates()
+        tm.assert_index_equal(idx, result)
+        assert idx.freq == result.freq
+
+        idx_dup = idx.append(idx)
+        result = idx_dup.drop_duplicates()
+
+        expected = idx
+        if not isinstance(idx, PeriodIndex):
+            # freq is reset except for PeriodIndex
+            assert idx_dup.freq is None
+            assert result.freq is None
+            expected = idx._with_freq(None)
+        else:
+            assert result.freq == expected.freq
+
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "keep, expected, index",
+        [
+            (
+                "first",
+                np.concatenate(([False] * 10, [True] * 5)),
+                np.arange(0, 10, dtype=np.int64),
+            ),
+            (
+                "last",
+                np.concatenate(([True] * 5, [False] * 10)),
+                np.arange(5, 15, dtype=np.int64),
+            ),
+            (
+                False,
+                np.concatenate(([True] * 5, [False] * 5, [True] * 5)),
+                np.arange(5, 10, dtype=np.int64),
+            ),
+        ],
+    )
+    def test_drop_duplicates(self, keep, expected, index, idx):
+        # to check Index/Series compat
+        idx = idx.append(idx[:5])
+
+        tm.assert_numpy_array_equal(idx.duplicated(keep=keep), expected)
+        expected = idx[~expected]
+
+        result = idx.drop_duplicates(keep=keep)
+        tm.assert_index_equal(result, expected)
+
+        result = Series(idx).drop_duplicates(keep=keep)
+        expected = Series(expected, index=index)
+        tm.assert_series_equal(result, expected)
+
+
+class TestDropDuplicatesPeriodIndex(DropDuplicates):
+    @pytest.fixture(params=["D", "3D", "h", "2h", "min", "2min", "s", "3s"])
+    def freq(self, request):
+        return request.param
+
+    @pytest.fixture
+    def idx(self, freq):
+        return period_range("2011-01-01", periods=10, freq=freq, name="idx")
+
+
+class TestDropDuplicatesDatetimeIndex(DropDuplicates):
+    @pytest.fixture
+    def idx(self, freq_sample):
+        return date_range("2011-01-01", freq=freq_sample, periods=10, name="idx")
+
+
+class TestDropDuplicatesTimedeltaIndex(DropDuplicates):
+    @pytest.fixture
+    def idx(self, freq_sample):
+        return timedelta_range("1 day", periods=10, freq=freq_sample, name="idx")

env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_equals.py

@@ -0,0 +1,181 @@
+"""
+Tests shared for DatetimeIndex/TimedeltaIndex/PeriodIndex
+"""
+from datetime import (
+    datetime,
+    timedelta,
+)
+
+import numpy as np
+import pytest
+
+import pandas as pd
+from pandas import (
+    CategoricalIndex,
+    DatetimeIndex,
+    Index,
+    PeriodIndex,
+    TimedeltaIndex,
+    date_range,
+    period_range,
+    timedelta_range,
+)
+import pandas._testing as tm
+
+
+class EqualsTests:
+    def test_not_equals_numeric(self, index):
+        assert not index.equals(Index(index.asi8))
+        assert not index.equals(Index(index.asi8.astype("u8")))
+        assert not index.equals(Index(index.asi8).astype("f8"))
+
+    def test_equals(self, index):
+        assert index.equals(index)
+        assert index.equals(index.astype(object))
+        assert index.equals(CategoricalIndex(index))
+        assert index.equals(CategoricalIndex(index.astype(object)))
+
+    def test_not_equals_non_arraylike(self, index):
+        assert not index.equals(list(index))
+
+    def test_not_equals_strings(self, index):
+        other = Index([str(x) for x in index], dtype=object)
+        assert not index.equals(other)
+        assert not index.equals(CategoricalIndex(other))
+
+    def test_not_equals_misc_strs(self, index):
+        other = Index(list("abc"))
+        assert not index.equals(other)
+
+
+class TestPeriodIndexEquals(EqualsTests):
+    @pytest.fixture
+    def index(self):
+        return period_range("2013-01-01", periods=5, freq="D")
+
+    # TODO: de-duplicate with other test_equals2 methods
+    @pytest.mark.parametrize("freq", ["D", "M"])
+    def test_equals2(self, freq):
+        # GH#13107
+        idx = PeriodIndex(["2011-01-01", "2011-01-02", "NaT"], freq=freq)
+        assert idx.equals(idx)
+        assert idx.equals(idx.copy())
+        assert idx.equals(idx.astype(object))
+        assert idx.astype(object).equals(idx)
+        assert idx.astype(object).equals(idx.astype(object))
+        assert not idx.equals(list(idx))
+        assert not idx.equals(pd.Series(idx))
+
+        idx2 = PeriodIndex(["2011-01-01", "2011-01-02", "NaT"], freq="h")
+        assert not idx.equals(idx2)
+        assert not idx.equals(idx2.copy())
+        assert not idx.equals(idx2.astype(object))
+        assert not idx.astype(object).equals(idx2)
+        assert not idx.equals(list(idx2))
+        assert not idx.equals(pd.Series(idx2))
+
+        # same internal, different tz
+        idx3 = PeriodIndex._simple_new(
+            idx._values._simple_new(idx._values.asi8, dtype=pd.PeriodDtype("h"))
+        )
+        tm.assert_numpy_array_equal(idx.asi8, idx3.asi8)
+        assert not idx.equals(idx3)
+        assert not idx.equals(idx3.copy())
+        assert not idx.equals(idx3.astype(object))
+        assert not idx.astype(object).equals(idx3)
+        assert not idx.equals(list(idx3))
+        assert not idx.equals(pd.Series(idx3))
+
+
+class TestDatetimeIndexEquals(EqualsTests):
+    @pytest.fixture
+    def index(self):
+        return date_range("2013-01-01", periods=5)
+
+    def test_equals2(self):
+        # GH#13107
+        idx = DatetimeIndex(["2011-01-01", "2011-01-02", "NaT"])
+        assert idx.equals(idx)
+        assert idx.equals(idx.copy())
+        assert idx.equals(idx.astype(object))
+        assert idx.astype(object).equals(idx)
+        assert idx.astype(object).equals(idx.astype(object))
+        assert not idx.equals(list(idx))
+        assert not idx.equals(pd.Series(idx))
+
+        idx2 = DatetimeIndex(["2011-01-01", "2011-01-02", "NaT"], tz="US/Pacific")
+        assert not idx.equals(idx2)
+        assert not idx.equals(idx2.copy())
+        assert not idx.equals(idx2.astype(object))
+        assert not idx.astype(object).equals(idx2)
+        assert not idx.equals(list(idx2))
+        assert not idx.equals(pd.Series(idx2))
+
+        # same internal, different tz
+        idx3 = DatetimeIndex(idx.asi8, tz="US/Pacific")
+        tm.assert_numpy_array_equal(idx.asi8, idx3.asi8)
+        assert not idx.equals(idx3)
+        assert not idx.equals(idx3.copy())
+        assert not idx.equals(idx3.astype(object))
+        assert not idx.astype(object).equals(idx3)
+        assert not idx.equals(list(idx3))
+        assert not idx.equals(pd.Series(idx3))
+
+        # check that we do not raise when comparing with OutOfBounds objects
+        oob = Index([datetime(2500, 1, 1)] * 3, dtype=object)
+        assert not idx.equals(oob)
+        assert not idx2.equals(oob)
+        assert not idx3.equals(oob)
+
+        # check that we do not raise when comparing with OutOfBounds dt64
+        oob2 = oob.map(np.datetime64)
+        assert not idx.equals(oob2)
+        assert not idx2.equals(oob2)
+        assert not idx3.equals(oob2)
+
+    @pytest.mark.parametrize("freq", ["B", "C"])
+    def test_not_equals_bday(self, freq):
+        rng = date_range("2009-01-01", "2010-01-01", freq=freq)
+        assert not rng.equals(list(rng))
+
+
+class TestTimedeltaIndexEquals(EqualsTests):
+    @pytest.fixture
+    def index(self):
+        return timedelta_range("1 day", periods=10)
+
+    def test_equals2(self):
+        # GH#13107
+        idx = TimedeltaIndex(["1 days", "2 days", "NaT"])
+        assert idx.equals(idx)
+        assert idx.equals(idx.copy())
+        assert idx.equals(idx.astype(object))
+        assert idx.astype(object).equals(idx)
+        assert idx.astype(object).equals(idx.astype(object))
+        assert not idx.equals(list(idx))
+        assert not idx.equals(pd.Series(idx))
+
+        idx2 = TimedeltaIndex(["2 days", "1 days", "NaT"])
+        assert not idx.equals(idx2)
+        assert not idx.equals(idx2.copy())
+        assert not idx.equals(idx2.astype(object))
+        assert not idx.astype(object).equals(idx2)
+        assert not idx.astype(object).equals(idx2.astype(object))
+        assert not idx.equals(list(idx2))
+        assert not idx.equals(pd.Series(idx2))
+
+        # Check that we dont raise OverflowError on comparisons outside the
+        #  implementation range GH#28532
+        oob = Index([timedelta(days=10**6)] * 3, dtype=object)
+        assert not idx.equals(oob)
+        assert not idx2.equals(oob)
+
+        oob2 = Index([np.timedelta64(x) for x in oob], dtype=object)
+        assert (oob == oob2).all()
+        assert not idx.equals(oob2)
+        assert not idx2.equals(oob2)
+
+        oob3 = oob.map(np.timedelta64)
+        assert (oob3 == oob).all()
+        assert not idx.equals(oob3)
+        assert not idx2.equals(oob3)

env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_indexing.py

@@ -0,0 +1,45 @@
+import numpy as np
+import pytest
+
+import pandas as pd
+from pandas import (
+    DatetimeIndex,
+    Index,
+)
+import pandas._testing as tm
+
+dtlike_dtypes = [
+    np.dtype("timedelta64[ns]"),
+    np.dtype("datetime64[ns]"),
+    pd.DatetimeTZDtype("ns", "Asia/Tokyo"),
+    pd.PeriodDtype("ns"),
+]
+
+
+@pytest.mark.parametrize("ldtype", dtlike_dtypes)
+@pytest.mark.parametrize("rdtype", dtlike_dtypes)
+def test_get_indexer_non_unique_wrong_dtype(ldtype, rdtype):
+    vals = np.tile(3600 * 10**9 * np.arange(3), 2)
+
+    def construct(dtype):
+        if dtype is dtlike_dtypes[-1]:
+            # PeriodArray will try to cast ints to strings
+            return DatetimeIndex(vals).astype(dtype)
+        return Index(vals, dtype=dtype)
+
+    left = construct(ldtype)
+    right = construct(rdtype)
+
+    result = left.get_indexer_non_unique(right)
+
+    if ldtype is rdtype:
+        ex1 = np.array([0, 3, 1, 4, 2, 5] * 2, dtype=np.intp)
+        ex2 = np.array([], dtype=np.intp)
+        tm.assert_numpy_array_equal(result[0], ex1)
+        tm.assert_numpy_array_equal(result[1], ex2)
+
+    else:
+        no_matches = np.array([-1] * 6, dtype=np.intp)
+        missing = np.arange(6, dtype=np.intp)
+        tm.assert_numpy_array_equal(result[0], no_matches)
+        tm.assert_numpy_array_equal(result[1], missing)

env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_is_monotonic.py

@@ -0,0 +1,46 @@
+from pandas import (
+    Index,
+    NaT,
+    date_range,
+)
+
+
+def test_is_monotonic_with_nat():
+    # GH#31437
+    # PeriodIndex.is_monotonic_increasing should behave analogously to DatetimeIndex,
+    #  in particular never be monotonic when we have NaT
+    dti = date_range("2016-01-01", periods=3)
+    pi = dti.to_period("D")
+    tdi = Index(dti.view("timedelta64[ns]"))
+
+    for obj in [pi, pi._engine, dti, dti._engine, tdi, tdi._engine]:
+        if isinstance(obj, Index):
+            # i.e. not Engines
+            assert obj.is_monotonic_increasing
+        assert obj.is_monotonic_increasing
+        assert not obj.is_monotonic_decreasing
+        assert obj.is_unique
+
+    dti1 = dti.insert(0, NaT)
+    pi1 = dti1.to_period("D")
+    tdi1 = Index(dti1.view("timedelta64[ns]"))
+
+    for obj in [pi1, pi1._engine, dti1, dti1._engine, tdi1, tdi1._engine]:
+        if isinstance(obj, Index):
+            # i.e. not Engines
+            assert not obj.is_monotonic_increasing
+        assert not obj.is_monotonic_increasing
+        assert not obj.is_monotonic_decreasing
+        assert obj.is_unique
+
+    dti2 = dti.insert(3, NaT)
+    pi2 = dti2.to_period("h")
+    tdi2 = Index(dti2.view("timedelta64[ns]"))
+
+    for obj in [pi2, pi2._engine, dti2, dti2._engine, tdi2, tdi2._engine]:
+        if isinstance(obj, Index):
+            # i.e. not Engines
+            assert not obj.is_monotonic_increasing
+        assert not obj.is_monotonic_increasing
+        assert not obj.is_monotonic_decreasing
+        assert obj.is_unique

env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_nat.py

@@ -0,0 +1,53 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    PeriodIndex,
+    TimedeltaIndex,
+)
+import pandas._testing as tm
+
+
+class NATests:
+    def test_nat(self, index_without_na):
+        empty_index = index_without_na[:0]
+
+        index_with_na = index_without_na.copy(deep=True)
+        index_with_na._data[1] = NaT
+
+        assert empty_index._na_value is NaT
+        assert index_with_na._na_value is NaT
+        assert index_without_na._na_value is NaT
+
+        idx = index_without_na
+        assert idx._can_hold_na
+
+        tm.assert_numpy_array_equal(idx._isnan, np.array([False, False]))
+        assert idx.hasnans is False
+
+        idx = index_with_na
+        assert idx._can_hold_na
+
+        tm.assert_numpy_array_equal(idx._isnan, np.array([False, True]))
+        assert idx.hasnans is True
+
+
+class TestDatetimeIndexNA(NATests):
+    @pytest.fixture
+    def index_without_na(self, tz_naive_fixture):
+        tz = tz_naive_fixture
+        return DatetimeIndex(["2011-01-01", "2011-01-02"], tz=tz)
+
+
+class TestTimedeltaIndexNA(NATests):
+    @pytest.fixture
+    def index_without_na(self):
+        return TimedeltaIndex(["1 days", "2 days"])
+
+
+class TestPeriodIndexNA(NATests):
+    @pytest.fixture
+    def index_without_na(self):
+        return PeriodIndex(["2011-01-01", "2011-01-02"], freq="D")

env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_sort_values.py

@@ -0,0 +1,315 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    Index,
+    NaT,
+    PeriodIndex,
+    TimedeltaIndex,
+    timedelta_range,
+)
+import pandas._testing as tm
+
+
+def check_freq_ascending(ordered, orig, ascending):
+    """
+    Check the expected freq on a PeriodIndex/DatetimeIndex/TimedeltaIndex
+    when the original index is generated (or generate-able) with
+    period_range/date_range/timedelta_range.
+    """
+    if isinstance(ordered, PeriodIndex):
+        assert ordered.freq == orig.freq
+    elif isinstance(ordered, (DatetimeIndex, TimedeltaIndex)):
+        if ascending:
+            assert ordered.freq.n == orig.freq.n
+        else:
+            assert ordered.freq.n == -1 * orig.freq.n
+
+
+def check_freq_nonmonotonic(ordered, orig):
+    """
+    Check the expected freq on a PeriodIndex/DatetimeIndex/TimedeltaIndex
+    when the original index is _not_ generated (or generate-able) with
+    period_range/date_range//timedelta_range.
+    """
+    if isinstance(ordered, PeriodIndex):
+        assert ordered.freq == orig.freq
+    elif isinstance(ordered, (DatetimeIndex, TimedeltaIndex)):
+        assert ordered.freq is None
+
+
+class TestSortValues:
+    @pytest.fixture(params=[DatetimeIndex, TimedeltaIndex, PeriodIndex])
+    def non_monotonic_idx(self, request):
+        if request.param is DatetimeIndex:
+            return DatetimeIndex(["2000-01-04", "2000-01-01", "2000-01-02"])
+        elif request.param is PeriodIndex:
+            dti = DatetimeIndex(["2000-01-04", "2000-01-01", "2000-01-02"])
+            return dti.to_period("D")
+        else:
+            return TimedeltaIndex(
+                ["1 day 00:00:05", "1 day 00:00:01", "1 day 00:00:02"]
+            )
+
+    def test_argmin_argmax(self, non_monotonic_idx):
+        assert non_monotonic_idx.argmin() == 1
+        assert non_monotonic_idx.argmax() == 0
+
+    def test_sort_values(self, non_monotonic_idx):
+        idx = non_monotonic_idx
+        ordered = idx.sort_values()
+        assert ordered.is_monotonic_increasing
+        ordered = idx.sort_values(ascending=False)
+        assert ordered[::-1].is_monotonic_increasing
+
+        ordered, dexer = idx.sort_values(return_indexer=True)
+        assert ordered.is_monotonic_increasing
+        tm.assert_numpy_array_equal(dexer, np.array([1, 2, 0], dtype=np.intp))
+
+        ordered, dexer = idx.sort_values(return_indexer=True, ascending=False)
+        assert ordered[::-1].is_monotonic_increasing
+        tm.assert_numpy_array_equal(dexer, np.array([0, 2, 1], dtype=np.intp))
+
+    def check_sort_values_with_freq(self, idx):
+        ordered = idx.sort_values()
+        tm.assert_index_equal(ordered, idx)
+        check_freq_ascending(ordered, idx, True)
+
+        ordered = idx.sort_values(ascending=False)
+        expected = idx[::-1]
+        tm.assert_index_equal(ordered, expected)
+        check_freq_ascending(ordered, idx, False)
+
+        ordered, indexer = idx.sort_values(return_indexer=True)
+        tm.assert_index_equal(ordered, idx)
+        tm.assert_numpy_array_equal(indexer, np.array([0, 1, 2], dtype=np.intp))
+        check_freq_ascending(ordered, idx, True)
+
+        ordered, indexer = idx.sort_values(return_indexer=True, ascending=False)
+        expected = idx[::-1]
+        tm.assert_index_equal(ordered, expected)
+        tm.assert_numpy_array_equal(indexer, np.array([2, 1, 0], dtype=np.intp))
+        check_freq_ascending(ordered, idx, False)
+
+    @pytest.mark.parametrize("freq", ["D", "h"])
+    def test_sort_values_with_freq_timedeltaindex(self, freq):
+        # GH#10295
+        idx = timedelta_range(start=f"1{freq}", periods=3, freq=freq).rename("idx")
+
+        self.check_sort_values_with_freq(idx)
+
+    @pytest.mark.parametrize(
+        "idx",
+        [
+            DatetimeIndex(
+                ["2011-01-01", "2011-01-02", "2011-01-03"], freq="D", name="idx"
+            ),
+            DatetimeIndex(
+                ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"],
+                freq="h",
+                name="tzidx",
+                tz="Asia/Tokyo",
+            ),
+        ],
+    )
+    def test_sort_values_with_freq_datetimeindex(self, idx):
+        self.check_sort_values_with_freq(idx)
+
+    @pytest.mark.parametrize("freq", ["D", "2D", "4D"])
+    def test_sort_values_with_freq_periodindex(self, freq):
+        # here with_freq refers to being period_range-like
+        idx = PeriodIndex(
+            ["2011-01-01", "2011-01-02", "2011-01-03"], freq=freq, name="idx"
+        )
+        self.check_sort_values_with_freq(idx)
+
+    @pytest.mark.parametrize(
+        "idx",
+        [
+            PeriodIndex(["2011", "2012", "2013"], name="pidx", freq="Y"),
+            Index([2011, 2012, 2013], name="idx"),  # for compatibility check
+        ],
+    )
+    def test_sort_values_with_freq_periodindex2(self, idx):
+        # here with_freq indicates this is period_range-like
+        self.check_sort_values_with_freq(idx)
+
+    def check_sort_values_without_freq(self, idx, expected):
+        ordered = idx.sort_values(na_position="first")
+        tm.assert_index_equal(ordered, expected)
+        check_freq_nonmonotonic(ordered, idx)
+
+        if not idx.isna().any():
+            ordered = idx.sort_values()
+            tm.assert_index_equal(ordered, expected)
+            check_freq_nonmonotonic(ordered, idx)
+
+        ordered = idx.sort_values(ascending=False)
+        tm.assert_index_equal(ordered, expected[::-1])
+        check_freq_nonmonotonic(ordered, idx)
+
+        ordered, indexer = idx.sort_values(return_indexer=True, na_position="first")
+        tm.assert_index_equal(ordered, expected)
+
+        exp = np.array([0, 4, 3, 1, 2], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, exp)
+        check_freq_nonmonotonic(ordered, idx)
+
+        if not idx.isna().any():
+            ordered, indexer = idx.sort_values(return_indexer=True)
+            tm.assert_index_equal(ordered, expected)
+
+            exp = np.array([0, 4, 3, 1, 2], dtype=np.intp)
+            tm.assert_numpy_array_equal(indexer, exp)
+            check_freq_nonmonotonic(ordered, idx)
+
+        ordered, indexer = idx.sort_values(return_indexer=True, ascending=False)
+        tm.assert_index_equal(ordered, expected[::-1])
+
+        exp = np.array([2, 1, 3, 0, 4], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, exp)
+        check_freq_nonmonotonic(ordered, idx)
+
+    def test_sort_values_without_freq_timedeltaindex(self):
+        # GH#10295
+
+        idx = TimedeltaIndex(
+            ["1 hour", "3 hour", "5 hour", "2 hour ", "1 hour"], name="idx1"
+        )
+        expected = TimedeltaIndex(
+            ["1 hour", "1 hour", "2 hour", "3 hour", "5 hour"], name="idx1"
+        )
+        self.check_sort_values_without_freq(idx, expected)
+
+    @pytest.mark.parametrize(
+        "index_dates,expected_dates",
+        [
+            (
+                ["2011-01-01", "2011-01-03", "2011-01-05", "2011-01-02", "2011-01-01"],
+                ["2011-01-01", "2011-01-01", "2011-01-02", "2011-01-03", "2011-01-05"],
+            ),
+            (
+                ["2011-01-01", "2011-01-03", "2011-01-05", "2011-01-02", "2011-01-01"],
+                ["2011-01-01", "2011-01-01", "2011-01-02", "2011-01-03", "2011-01-05"],
+            ),
+            (
+                [NaT, "2011-01-03", "2011-01-05", "2011-01-02", NaT],
+                [NaT, NaT, "2011-01-02", "2011-01-03", "2011-01-05"],
+            ),
+        ],
+    )
+    def test_sort_values_without_freq_datetimeindex(
+        self, index_dates, expected_dates, tz_naive_fixture
+    ):
+        tz = tz_naive_fixture
+
+        # without freq
+        idx = DatetimeIndex(index_dates, tz=tz, name="idx")
+        expected = DatetimeIndex(expected_dates, tz=tz, name="idx")
+
+        self.check_sort_values_without_freq(idx, expected)
+
+    @pytest.mark.parametrize(
+        "idx,expected",
+        [
+            (
+                PeriodIndex(
+                    [
+                        "2011-01-01",
+                        "2011-01-03",
+                        "2011-01-05",
+                        "2011-01-02",
+                        "2011-01-01",
+                    ],
+                    freq="D",
+                    name="idx1",
+                ),
+                PeriodIndex(
+                    [
+                        "2011-01-01",
+                        "2011-01-01",
+                        "2011-01-02",
+                        "2011-01-03",
+                        "2011-01-05",
+                    ],
+                    freq="D",
+                    name="idx1",
+                ),
+            ),
+            (
+                PeriodIndex(
+                    [
+                        "2011-01-01",
+                        "2011-01-03",
+                        "2011-01-05",
+                        "2011-01-02",
+                        "2011-01-01",
+                    ],
+                    freq="D",
+                    name="idx2",
+                ),
+                PeriodIndex(
+                    [
+                        "2011-01-01",
+                        "2011-01-01",
+                        "2011-01-02",
+                        "2011-01-03",
+                        "2011-01-05",
+                    ],
+                    freq="D",
+                    name="idx2",
+                ),
+            ),
+            (
+                PeriodIndex(
+                    [NaT, "2011-01-03", "2011-01-05", "2011-01-02", NaT],
+                    freq="D",
+                    name="idx3",
+                ),
+                PeriodIndex(
+                    [NaT, NaT, "2011-01-02", "2011-01-03", "2011-01-05"],
+                    freq="D",
+                    name="idx3",
+                ),
+            ),
+            (
+                PeriodIndex(
+                    ["2011", "2013", "2015", "2012", "2011"], name="pidx", freq="Y"
+                ),
+                PeriodIndex(
+                    ["2011", "2011", "2012", "2013", "2015"], name="pidx", freq="Y"
+                ),
+            ),
+            (
+                # For compatibility check
+                Index([2011, 2013, 2015, 2012, 2011], name="idx"),
+                Index([2011, 2011, 2012, 2013, 2015], name="idx"),
+            ),
+        ],
+    )
+    def test_sort_values_without_freq_periodindex(self, idx, expected):
+        # here without_freq means not generateable by period_range
+        self.check_sort_values_without_freq(idx, expected)
+
+    def test_sort_values_without_freq_periodindex_nat(self):
+        # doesn't quite fit into check_sort_values_without_freq
+        idx = PeriodIndex(["2011", "2013", "NaT", "2011"], name="pidx", freq="D")
+        expected = PeriodIndex(["NaT", "2011", "2011", "2013"], name="pidx", freq="D")
+
+        ordered = idx.sort_values(na_position="first")
+        tm.assert_index_equal(ordered, expected)
+        check_freq_nonmonotonic(ordered, idx)
+
+        ordered = idx.sort_values(ascending=False)
+        tm.assert_index_equal(ordered, expected[::-1])
+        check_freq_nonmonotonic(ordered, idx)
+
+
+def test_order_stability_compat():
+    # GH#35922. sort_values is stable both for normal and datetime-like Index
+    pidx = PeriodIndex(["2011", "2013", "2015", "2012", "2011"], name="pidx", freq="Y")
+    iidx = Index([2011, 2013, 2015, 2012, 2011], name="idx")
+    ordered1, indexer1 = pidx.sort_values(return_indexer=True, ascending=False)
+    ordered2, indexer2 = iidx.sort_values(return_indexer=True, ascending=False)
+    tm.assert_numpy_array_equal(indexer1, indexer2)

env-llmeval/lib/python3.10/site-packages/pandas/tests/indexes/datetimelike_/test_value_counts.py

@@ -0,0 +1,103 @@
+import numpy as np
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    PeriodIndex,
+    Series,
+    TimedeltaIndex,
+    date_range,
+    period_range,
+    timedelta_range,
+)
+import pandas._testing as tm
+
+
+class TestValueCounts:
+    # GH#7735
+
+    def test_value_counts_unique_datetimeindex(self, tz_naive_fixture):
+        tz = tz_naive_fixture
+        orig = date_range("2011-01-01 09:00", freq="h", periods=10, tz=tz)
+        self._check_value_counts_with_repeats(orig)
+
+    def test_value_counts_unique_timedeltaindex(self):
+        orig = timedelta_range("1 days 09:00:00", freq="h", periods=10)
+        self._check_value_counts_with_repeats(orig)
+
+    def test_value_counts_unique_periodindex(self):
+        orig = period_range("2011-01-01 09:00", freq="h", periods=10)
+        self._check_value_counts_with_repeats(orig)
+
+    def _check_value_counts_with_repeats(self, orig):
+        # create repeated values, 'n'th element is repeated by n+1 times
+        idx = type(orig)(
+            np.repeat(orig._values, range(1, len(orig) + 1)), dtype=orig.dtype
+        )
+
+        exp_idx = orig[::-1]
+        if not isinstance(exp_idx, PeriodIndex):
+            exp_idx = exp_idx._with_freq(None)
+        expected = Series(range(10, 0, -1), index=exp_idx, dtype="int64", name="count")
+
+        for obj in [idx, Series(idx)]:
+            tm.assert_series_equal(obj.value_counts(), expected)
+
+        tm.assert_index_equal(idx.unique(), orig)
+
+    def test_value_counts_unique_datetimeindex2(self, tz_naive_fixture):
+        tz = tz_naive_fixture
+        idx = DatetimeIndex(
+            [
+                "2013-01-01 09:00",
+                "2013-01-01 09:00",
+                "2013-01-01 09:00",
+                "2013-01-01 08:00",
+                "2013-01-01 08:00",
+                NaT,
+            ],
+            tz=tz,
+        )
+        self._check_value_counts_dropna(idx)
+
+    def test_value_counts_unique_timedeltaindex2(self):
+        idx = TimedeltaIndex(
+            [
+                "1 days 09:00:00",
+                "1 days 09:00:00",
+                "1 days 09:00:00",
+                "1 days 08:00:00",
+                "1 days 08:00:00",
+                NaT,
+            ]
+        )
+        self._check_value_counts_dropna(idx)
+
+    def test_value_counts_unique_periodindex2(self):
+        idx = PeriodIndex(
+            [
+                "2013-01-01 09:00",
+                "2013-01-01 09:00",
+                "2013-01-01 09:00",
+                "2013-01-01 08:00",
+                "2013-01-01 08:00",
+                NaT,
+            ],
+            freq="h",
+        )
+        self._check_value_counts_dropna(idx)
+
+    def _check_value_counts_dropna(self, idx):
+        exp_idx = idx[[2, 3]]
+        expected = Series([3, 2], index=exp_idx, name="count")
+
+        for obj in [idx, Series(idx)]:
+            tm.assert_series_equal(obj.value_counts(), expected)
+
+        exp_idx = idx[[2, 3, -1]]
+        expected = Series([3, 2, 1], index=exp_idx, name="count")
+
+        for obj in [idx, Series(idx)]:
+            tm.assert_series_equal(obj.value_counts(dropna=False), expected)
+
+        tm.assert_index_equal(idx.unique(), exp_idx)

env-llmeval/lib/python3.10/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"))

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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

env-llmeval/lib/python3.10/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"

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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)

env-llmeval/lib/python3.10/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)