Initial Debugging Completed and Execution Successful

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_asfreq.py

@@ -0,0 +1,189 @@
+import re
+
+import pytest
+
+from pandas import (
+    PeriodIndex,
+    Series,
+    period_range,
+)
+import pandas._testing as tm
+
+from pandas.tseries import offsets
+
+
+class TestPeriodIndex:
+    def test_asfreq(self):
+        pi1 = period_range(freq="Y", start="1/1/2001", end="1/1/2001")
+        pi2 = period_range(freq="Q", start="1/1/2001", end="1/1/2001")
+        pi3 = period_range(freq="M", start="1/1/2001", end="1/1/2001")
+        pi4 = period_range(freq="D", start="1/1/2001", end="1/1/2001")
+        pi5 = period_range(freq="h", start="1/1/2001", end="1/1/2001 00:00")
+        pi6 = period_range(freq="Min", start="1/1/2001", end="1/1/2001 00:00")
+        pi7 = period_range(freq="s", start="1/1/2001", end="1/1/2001 00:00:00")
+
+        assert pi1.asfreq("Q", "s") == pi2
+        assert pi1.asfreq("Q", "s") == pi2
+        assert pi1.asfreq("M", "start") == pi3
+        assert pi1.asfreq("D", "StarT") == pi4
+        assert pi1.asfreq("h", "beGIN") == pi5
+        assert pi1.asfreq("Min", "s") == pi6
+        assert pi1.asfreq("s", "s") == pi7
+
+        assert pi2.asfreq("Y", "s") == pi1
+        assert pi2.asfreq("M", "s") == pi3
+        assert pi2.asfreq("D", "s") == pi4
+        assert pi2.asfreq("h", "s") == pi5
+        assert pi2.asfreq("Min", "s") == pi6
+        assert pi2.asfreq("s", "s") == pi7
+
+        assert pi3.asfreq("Y", "s") == pi1
+        assert pi3.asfreq("Q", "s") == pi2
+        assert pi3.asfreq("D", "s") == pi4
+        assert pi3.asfreq("h", "s") == pi5
+        assert pi3.asfreq("Min", "s") == pi6
+        assert pi3.asfreq("s", "s") == pi7
+
+        assert pi4.asfreq("Y", "s") == pi1
+        assert pi4.asfreq("Q", "s") == pi2
+        assert pi4.asfreq("M", "s") == pi3
+        assert pi4.asfreq("h", "s") == pi5
+        assert pi4.asfreq("Min", "s") == pi6
+        assert pi4.asfreq("s", "s") == pi7
+
+        assert pi5.asfreq("Y", "s") == pi1
+        assert pi5.asfreq("Q", "s") == pi2
+        assert pi5.asfreq("M", "s") == pi3
+        assert pi5.asfreq("D", "s") == pi4
+        assert pi5.asfreq("Min", "s") == pi6
+        assert pi5.asfreq("s", "s") == pi7
+
+        assert pi6.asfreq("Y", "s") == pi1
+        assert pi6.asfreq("Q", "s") == pi2
+        assert pi6.asfreq("M", "s") == pi3
+        assert pi6.asfreq("D", "s") == pi4
+        assert pi6.asfreq("h", "s") == pi5
+        assert pi6.asfreq("s", "s") == pi7
+
+        assert pi7.asfreq("Y", "s") == pi1
+        assert pi7.asfreq("Q", "s") == pi2
+        assert pi7.asfreq("M", "s") == pi3
+        assert pi7.asfreq("D", "s") == pi4
+        assert pi7.asfreq("h", "s") == pi5
+        assert pi7.asfreq("Min", "s") == pi6
+
+        msg = "How must be one of S or E"
+        with pytest.raises(ValueError, match=msg):
+            pi7.asfreq("T", "foo")
+        result1 = pi1.asfreq("3M")
+        result2 = pi1.asfreq("M")
+        expected = period_range(freq="M", start="2001-12", end="2001-12")
+        tm.assert_numpy_array_equal(result1.asi8, expected.asi8)
+        assert result1.freqstr == "3M"
+        tm.assert_numpy_array_equal(result2.asi8, expected.asi8)
+        assert result2.freqstr == "M"
+
+    def test_asfreq_nat(self):
+        idx = PeriodIndex(["2011-01", "2011-02", "NaT", "2011-04"], freq="M")
+        result = idx.asfreq(freq="Q")
+        expected = PeriodIndex(["2011Q1", "2011Q1", "NaT", "2011Q2"], freq="Q")
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("freq", ["D", "3D"])
+    def test_asfreq_mult_pi(self, freq):
+        pi = PeriodIndex(["2001-01", "2001-02", "NaT", "2001-03"], freq="2M")
+
+        result = pi.asfreq(freq)
+        exp = PeriodIndex(["2001-02-28", "2001-03-31", "NaT", "2001-04-30"], freq=freq)
+        tm.assert_index_equal(result, exp)
+        assert result.freq == exp.freq
+
+        result = pi.asfreq(freq, how="S")
+        exp = PeriodIndex(["2001-01-01", "2001-02-01", "NaT", "2001-03-01"], freq=freq)
+        tm.assert_index_equal(result, exp)
+        assert result.freq == exp.freq
+
+    def test_asfreq_combined_pi(self):
+        pi = PeriodIndex(["2001-01-01 00:00", "2001-01-02 02:00", "NaT"], freq="h")
+        exp = PeriodIndex(["2001-01-01 00:00", "2001-01-02 02:00", "NaT"], freq="25h")
+        for freq, how in zip(["1D1h", "1h1D"], ["S", "E"]):
+            result = pi.asfreq(freq, how=how)
+            tm.assert_index_equal(result, exp)
+            assert result.freq == exp.freq
+
+        for freq in ["1D1h", "1h1D"]:
+            pi = PeriodIndex(["2001-01-01 00:00", "2001-01-02 02:00", "NaT"], freq=freq)
+            result = pi.asfreq("h")
+            exp = PeriodIndex(["2001-01-02 00:00", "2001-01-03 02:00", "NaT"], freq="h")
+            tm.assert_index_equal(result, exp)
+            assert result.freq == exp.freq
+
+            pi = PeriodIndex(["2001-01-01 00:00", "2001-01-02 02:00", "NaT"], freq=freq)
+            result = pi.asfreq("h", how="S")
+            exp = PeriodIndex(["2001-01-01 00:00", "2001-01-02 02:00", "NaT"], freq="h")
+            tm.assert_index_equal(result, exp)
+            assert result.freq == exp.freq
+
+    def test_astype_asfreq(self):
+        pi1 = PeriodIndex(["2011-01-01", "2011-02-01", "2011-03-01"], freq="D")
+        exp = PeriodIndex(["2011-01", "2011-02", "2011-03"], freq="M")
+        tm.assert_index_equal(pi1.asfreq("M"), exp)
+        tm.assert_index_equal(pi1.astype("period[M]"), exp)
+
+        exp = PeriodIndex(["2011-01", "2011-02", "2011-03"], freq="3M")
+        tm.assert_index_equal(pi1.asfreq("3M"), exp)
+        tm.assert_index_equal(pi1.astype("period[3M]"), exp)
+
+    def test_asfreq_with_different_n(self):
+        ser = Series([1, 2], index=PeriodIndex(["2020-01", "2020-03"], freq="2M"))
+        result = ser.asfreq("M")
+
+        excepted = Series([1, 2], index=PeriodIndex(["2020-02", "2020-04"], freq="M"))
+        tm.assert_series_equal(result, excepted)
+
+    @pytest.mark.parametrize(
+        "freq",
+        [
+            "2BMS",
+            "2YS-MAR",
+            "2bh",
+        ],
+    )
+    def test_pi_asfreq_not_supported_frequency(self, freq):
+        # GH#55785
+        msg = f"{freq[1:]} is not supported as period frequency"
+
+        pi = PeriodIndex(["2020-01-01", "2021-01-01"], freq="M")
+        with pytest.raises(ValueError, match=msg):
+            pi.asfreq(freq=freq)
+
+    @pytest.mark.parametrize(
+        "freq",
+        [
+            "2BME",
+            "2YE-MAR",
+            "2QE",
+        ],
+    )
+    def test_pi_asfreq_invalid_frequency(self, freq):
+        # GH#55785
+        msg = f"Invalid frequency: {freq}"
+
+        pi = PeriodIndex(["2020-01-01", "2021-01-01"], freq="M")
+        with pytest.raises(ValueError, match=msg):
+            pi.asfreq(freq=freq)
+
+    @pytest.mark.parametrize(
+        "freq",
+        [
+            offsets.MonthBegin(2),
+            offsets.BusinessMonthEnd(2),
+        ],
+    )
+    def test_pi_asfreq_invalid_baseoffset(self, freq):
+        # GH#56945
+        msg = re.escape(f"{freq} is not supported as period frequency")
+
+        pi = PeriodIndex(["2020-01-01", "2021-01-01"], freq="M")
+        with pytest.raises(ValueError, match=msg):
+            pi.asfreq(freq=freq)

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_astype.py

@@ -0,0 +1,156 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    CategoricalIndex,
+    DatetimeIndex,
+    Index,
+    NaT,
+    Period,
+    PeriodIndex,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestPeriodIndexAsType:
+    @pytest.mark.parametrize("dtype", [float, "timedelta64", "timedelta64[ns]"])
+    def test_astype_raises(self, dtype):
+        # GH#13149, GH#13209
+        idx = PeriodIndex(["2016-05-16", "NaT", NaT, np.nan], freq="D")
+        msg = "Cannot cast PeriodIndex to dtype"
+        with pytest.raises(TypeError, match=msg):
+            idx.astype(dtype)
+
+    def test_astype_conversion(self, using_infer_string):
+        # GH#13149, GH#13209
+        idx = PeriodIndex(["2016-05-16", "NaT", NaT, np.nan], freq="D", name="idx")
+
+        result = idx.astype(object)
+        expected = Index(
+            [Period("2016-05-16", freq="D")] + [Period(NaT, freq="D")] * 3,
+            dtype="object",
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.astype(np.int64)
+        expected = Index(
+            [16937] + [-9223372036854775808] * 3, dtype=np.int64, name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.astype(str)
+        if using_infer_string:
+            expected = Index(
+                [str(x) if x is not NaT else None for x in idx], name="idx", dtype="str"
+            )
+        else:
+            expected = Index([str(x) for x in idx], name="idx", dtype=object)
+        tm.assert_index_equal(result, expected)
+
+        idx = period_range("1990", "2009", freq="Y", name="idx")
+        result = idx.astype("i8")
+        tm.assert_index_equal(result, Index(idx.asi8, name="idx"))
+        tm.assert_numpy_array_equal(result.values, idx.asi8)
+
+    def test_astype_uint(self):
+        arr = period_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_object(self):
+        idx = PeriodIndex([], freq="M")
+
+        exp = np.array([], dtype=object)
+        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
+        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
+
+        idx = PeriodIndex(["2011-01", NaT], freq="M")
+
+        exp = np.array([Period("2011-01", freq="M"), NaT], dtype=object)
+        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
+        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
+
+        exp = np.array([Period("2011-01-01", freq="D"), NaT], dtype=object)
+        idx = PeriodIndex(["2011-01-01", NaT], freq="D")
+        tm.assert_numpy_array_equal(idx.astype(object).values, exp)
+        tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
+
+    # TODO: de-duplicate this version (from test_ops) with the one above
+    # (from test_period)
+    def test_astype_object2(self):
+        idx = period_range(start="2013-01-01", periods=4, freq="M", name="idx")
+        expected_list = [
+            Period("2013-01-31", freq="M"),
+            Period("2013-02-28", freq="M"),
+            Period("2013-03-31", freq="M"),
+            Period("2013-04-30", freq="M"),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        assert isinstance(result, Index)
+        assert result.dtype == object
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+        assert idx.tolist() == expected_list
+
+        idx = PeriodIndex(
+            ["2013-01-01", "2013-01-02", "NaT", "2013-01-04"], freq="D", name="idx"
+        )
+        expected_list = [
+            Period("2013-01-01", freq="D"),
+            Period("2013-01-02", freq="D"),
+            Period("NaT", freq="D"),
+            Period("2013-01-04", freq="D"),
+        ]
+        expected = Index(expected_list, dtype=object, name="idx")
+        result = idx.astype(object)
+        assert isinstance(result, Index)
+        assert result.dtype == object
+        tm.assert_index_equal(result, expected)
+        for i in [0, 1, 3]:
+            assert result[i] == expected[i]
+        assert result[2] is NaT
+        assert result.name == expected.name
+
+        result_list = idx.tolist()
+        for i in [0, 1, 3]:
+            assert result_list[i] == expected_list[i]
+        assert result_list[2] is NaT
+
+    def test_astype_category(self):
+        obj = period_range("2000", periods=2, name="idx")
+        result = obj.astype("category")
+        expected = CategoricalIndex(
+            [Period("2000-01-01", freq="D"), Period("2000-01-02", freq="D")], name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = obj._data.astype("category")
+        expected = expected.values
+        tm.assert_categorical_equal(result, expected)
+
+    def test_astype_array_fallback(self):
+        obj = period_range("2000", periods=2, 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)
+
+    def test_period_astype_to_timestamp(self, unit):
+        # GH#55958
+        pi = PeriodIndex(["2011-01", "2011-02", "2011-03"], freq="M")
+
+        exp = DatetimeIndex(
+            ["2011-01-01", "2011-02-01", "2011-03-01"], tz="US/Eastern"
+        ).as_unit(unit)
+        res = pi.astype(f"datetime64[{unit}, US/Eastern]")
+        tm.assert_index_equal(res, exp)
+        assert res.freq == exp.freq

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_factorize.py

@@ -0,0 +1,41 @@
+import numpy as np
+
+from pandas import PeriodIndex
+import pandas._testing as tm
+
+
+class TestFactorize:
+    def test_factorize_period(self):
+        idx1 = PeriodIndex(
+            ["2014-01", "2014-01", "2014-02", "2014-02", "2014-03", "2014-03"],
+            freq="M",
+        )
+
+        exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp)
+        exp_idx = PeriodIndex(["2014-01", "2014-02", "2014-03"], freq="M")
+
+        arr, idx = idx1.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+
+        arr, idx = idx1.factorize(sort=True)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+
+    def test_factorize_period_nonmonotonic(self):
+        idx2 = PeriodIndex(
+            ["2014-03", "2014-03", "2014-02", "2014-01", "2014-03", "2014-01"],
+            freq="M",
+        )
+        exp_idx = PeriodIndex(["2014-01", "2014-02", "2014-03"], freq="M")
+
+        exp_arr = np.array([2, 2, 1, 0, 2, 0], dtype=np.intp)
+        arr, idx = idx2.factorize(sort=True)
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)
+
+        exp_arr = np.array([0, 0, 1, 2, 0, 2], dtype=np.intp)
+        exp_idx = PeriodIndex(["2014-03", "2014-02", "2014-01"], freq="M")
+        arr, idx = idx2.factorize()
+        tm.assert_numpy_array_equal(arr, exp_arr)
+        tm.assert_index_equal(idx, exp_idx)

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_fillna.py

@@ -0,0 +1,41 @@
+from pandas import (
+    Index,
+    NaT,
+    Period,
+    PeriodIndex,
+)
+import pandas._testing as tm
+
+
+class TestFillNA:
+    def test_fillna_period(self):
+        # GH#11343
+        idx = PeriodIndex(["2011-01-01 09:00", NaT, "2011-01-01 11:00"], freq="h")
+
+        exp = PeriodIndex(
+            ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"], freq="h"
+        )
+        result = idx.fillna(Period("2011-01-01 10:00", freq="h"))
+        tm.assert_index_equal(result, exp)
+
+        exp = Index(
+            [
+                Period("2011-01-01 09:00", freq="h"),
+                "x",
+                Period("2011-01-01 11:00", freq="h"),
+            ],
+            dtype=object,
+        )
+        result = idx.fillna("x")
+        tm.assert_index_equal(result, exp)
+
+        exp = Index(
+            [
+                Period("2011-01-01 09:00", freq="h"),
+                Period("2011-01-01", freq="D"),
+                Period("2011-01-01 11:00", freq="h"),
+            ],
+            dtype=object,
+        )
+        result = idx.fillna(Period("2011-01-01", freq="D"))
+        tm.assert_index_equal(result, exp)

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_insert.py

@@ -0,0 +1,18 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    NaT,
+    PeriodIndex,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestInsert:
+    @pytest.mark.parametrize("na", [np.nan, NaT, None])
+    def test_insert(self, na):
+        # GH#18295 (test missing)
+        expected = PeriodIndex(["2017Q1", NaT, "2017Q2", "2017Q3", "2017Q4"], freq="Q")
+        result = period_range("2017Q1", periods=4, freq="Q").insert(1, na)
+        tm.assert_index_equal(result, expected)

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_is_full.py

@@ -0,0 +1,23 @@
+import pytest
+
+from pandas import PeriodIndex
+
+
+def test_is_full():
+    index = PeriodIndex([2005, 2007, 2009], freq="Y")
+    assert not index.is_full
+
+    index = PeriodIndex([2005, 2006, 2007], freq="Y")
+    assert index.is_full
+
+    index = PeriodIndex([2005, 2005, 2007], freq="Y")
+    assert not index.is_full
+
+    index = PeriodIndex([2005, 2005, 2006], freq="Y")
+    assert index.is_full
+
+    index = PeriodIndex([2006, 2005, 2005], freq="Y")
+    with pytest.raises(ValueError, match="Index is not monotonic"):
+        index.is_full
+
+    assert index[:0].is_full

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_repeat.py

@@ -0,0 +1,26 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    PeriodIndex,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestRepeat:
+    @pytest.mark.parametrize("use_numpy", [True, False])
+    @pytest.mark.parametrize(
+        "index",
+        [
+            period_range("2000-01-01", periods=3, freq="D"),
+            period_range("2001-01-01", periods=3, freq="2D"),
+            PeriodIndex(["2001-01", "NaT", "2003-01"], freq="M"),
+        ],
+    )
+    def test_repeat_freqstr(self, index, use_numpy):
+        # GH#10183
+        expected = PeriodIndex([per for per in index for _ in range(3)])
+        result = np.repeat(index, 3) if use_numpy else index.repeat(3)
+        tm.assert_index_equal(result, expected)
+        assert result.freqstr == index.freqstr

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_shift.py

@@ -0,0 +1,122 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    PeriodIndex,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestPeriodIndexShift:
+    # ---------------------------------------------------------------
+    # PeriodIndex.shift is used by __add__ and __sub__
+
+    def test_pi_shift_ndarray(self):
+        idx = PeriodIndex(
+            ["2011-01", "2011-02", "NaT", "2011-04"], freq="M", name="idx"
+        )
+        result = idx.shift(np.array([1, 2, 3, 4]))
+        expected = PeriodIndex(
+            ["2011-02", "2011-04", "NaT", "2011-08"], freq="M", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.shift(np.array([1, -2, 3, -4]))
+        expected = PeriodIndex(
+            ["2011-02", "2010-12", "NaT", "2010-12"], freq="M", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_shift(self):
+        pi1 = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        pi2 = period_range(freq="Y", start="1/1/2002", end="12/1/2010")
+
+        tm.assert_index_equal(pi1.shift(0), pi1)
+
+        assert len(pi1) == len(pi2)
+        tm.assert_index_equal(pi1.shift(1), pi2)
+
+        pi1 = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        pi2 = period_range(freq="Y", start="1/1/2000", end="12/1/2008")
+        assert len(pi1) == len(pi2)
+        tm.assert_index_equal(pi1.shift(-1), pi2)
+
+        pi1 = period_range(freq="M", start="1/1/2001", end="12/1/2009")
+        pi2 = period_range(freq="M", start="2/1/2001", end="1/1/2010")
+        assert len(pi1) == len(pi2)
+        tm.assert_index_equal(pi1.shift(1), pi2)
+
+        pi1 = period_range(freq="M", start="1/1/2001", end="12/1/2009")
+        pi2 = period_range(freq="M", start="12/1/2000", end="11/1/2009")
+        assert len(pi1) == len(pi2)
+        tm.assert_index_equal(pi1.shift(-1), pi2)
+
+        pi1 = period_range(freq="D", start="1/1/2001", end="12/1/2009")
+        pi2 = period_range(freq="D", start="1/2/2001", end="12/2/2009")
+        assert len(pi1) == len(pi2)
+        tm.assert_index_equal(pi1.shift(1), pi2)
+
+        pi1 = period_range(freq="D", start="1/1/2001", end="12/1/2009")
+        pi2 = period_range(freq="D", start="12/31/2000", end="11/30/2009")
+        assert len(pi1) == len(pi2)
+        tm.assert_index_equal(pi1.shift(-1), pi2)
+
+    def test_shift_corner_cases(self):
+        # GH#9903
+        idx = PeriodIndex([], name="xxx", freq="h")
+
+        msg = "`freq` argument is not supported for PeriodIndex.shift"
+        with pytest.raises(TypeError, match=msg):
+            # period shift doesn't accept freq
+            idx.shift(1, freq="h")
+
+        tm.assert_index_equal(idx.shift(0), idx)
+        tm.assert_index_equal(idx.shift(3), idx)
+
+        idx = PeriodIndex(
+            ["2011-01-01 10:00", "2011-01-01 11:00", "2011-01-01 12:00"],
+            name="xxx",
+            freq="h",
+        )
+        tm.assert_index_equal(idx.shift(0), idx)
+        exp = PeriodIndex(
+            ["2011-01-01 13:00", "2011-01-01 14:00", "2011-01-01 15:00"],
+            name="xxx",
+            freq="h",
+        )
+        tm.assert_index_equal(idx.shift(3), exp)
+        exp = PeriodIndex(
+            ["2011-01-01 07:00", "2011-01-01 08:00", "2011-01-01 09:00"],
+            name="xxx",
+            freq="h",
+        )
+        tm.assert_index_equal(idx.shift(-3), exp)
+
+    def test_shift_nat(self):
+        idx = PeriodIndex(
+            ["2011-01", "2011-02", "NaT", "2011-04"], freq="M", name="idx"
+        )
+        result = idx.shift(1)
+        expected = PeriodIndex(
+            ["2011-02", "2011-03", "NaT", "2011-05"], freq="M", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.name == expected.name
+
+    def test_shift_gh8083(self):
+        # test shift for PeriodIndex
+        # GH#8083
+        drange = period_range("20130101", periods=5, freq="D")
+        result = drange.shift(1)
+        expected = PeriodIndex(
+            ["2013-01-02", "2013-01-03", "2013-01-04", "2013-01-05", "2013-01-06"],
+            freq="D",
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_shift_periods(self):
+        # GH #22458 : argument 'n' was deprecated in favor of 'periods'
+        idx = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        tm.assert_index_equal(idx.shift(periods=0), idx)
+        tm.assert_index_equal(idx.shift(0), idx)

venv/lib/python3.11/site-packages/pandas/tests/indexes/period/methods/test_to_timestamp.py

@@ -0,0 +1,142 @@
+from datetime import datetime
+
+import numpy as np
+import pytest
+
+from pandas import (
+    DatetimeIndex,
+    NaT,
+    PeriodIndex,
+    Timedelta,
+    Timestamp,
+    date_range,
+    period_range,
+)
+import pandas._testing as tm
+
+
+class TestToTimestamp:
+    def test_to_timestamp_non_contiguous(self):
+        # GH#44100
+        dti = date_range("2021-10-18", periods=9, freq="D")
+        pi = dti.to_period()
+
+        result = pi[::2].to_timestamp()
+        expected = dti[::2]
+        tm.assert_index_equal(result, expected)
+
+        result = pi._data[::2].to_timestamp()
+        expected = dti._data[::2]
+        # TODO: can we get the freq to round-trip?
+        tm.assert_datetime_array_equal(result, expected, check_freq=False)
+
+        result = pi[::-1].to_timestamp()
+        expected = dti[::-1]
+        tm.assert_index_equal(result, expected)
+
+        result = pi._data[::-1].to_timestamp()
+        expected = dti._data[::-1]
+        tm.assert_datetime_array_equal(result, expected, check_freq=False)
+
+        result = pi[::2][::-1].to_timestamp()
+        expected = dti[::2][::-1]
+        tm.assert_index_equal(result, expected)
+
+        result = pi._data[::2][::-1].to_timestamp()
+        expected = dti._data[::2][::-1]
+        tm.assert_datetime_array_equal(result, expected, check_freq=False)
+
+    def test_to_timestamp_freq(self):
+        idx = period_range("2017", periods=12, freq="Y-DEC")
+        result = idx.to_timestamp()
+        expected = date_range("2017", periods=12, freq="YS-JAN")
+        tm.assert_index_equal(result, expected)
+
+    def test_to_timestamp_pi_nat(self):
+        # GH#7228
+        index = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="M", name="idx")
+
+        result = index.to_timestamp("D")
+        expected = DatetimeIndex(
+            [NaT, datetime(2011, 1, 1), datetime(2011, 2, 1)],
+            dtype="M8[ns]",
+            name="idx",
+        )
+        tm.assert_index_equal(result, expected)
+        assert result.name == "idx"
+
+        result2 = result.to_period(freq="M")
+        tm.assert_index_equal(result2, index)
+        assert result2.name == "idx"
+
+        result3 = result.to_period(freq="3M")
+        exp = PeriodIndex(["NaT", "2011-01", "2011-02"], freq="3M", name="idx")
+        tm.assert_index_equal(result3, exp)
+        assert result3.freqstr == "3M"
+
+        msg = "Frequency must be positive, because it represents span: -2Y"
+        with pytest.raises(ValueError, match=msg):
+            result.to_period(freq="-2Y")
+
+    def test_to_timestamp_preserve_name(self):
+        index = period_range(freq="Y", start="1/1/2001", end="12/1/2009", name="foo")
+        assert index.name == "foo"
+
+        conv = index.to_timestamp("D")
+        assert conv.name == "foo"
+
+    def test_to_timestamp_quarterly_bug(self):
+        years = np.arange(1960, 2000).repeat(4)
+        quarters = np.tile(list(range(1, 5)), 40)
+
+        pindex = PeriodIndex.from_fields(year=years, quarter=quarters)
+
+        stamps = pindex.to_timestamp("D", "end")
+        expected = DatetimeIndex([x.to_timestamp("D", "end") for x in pindex])
+        tm.assert_index_equal(stamps, expected)
+        assert stamps.freq == expected.freq
+
+    def test_to_timestamp_pi_mult(self):
+        idx = PeriodIndex(["2011-01", "NaT", "2011-02"], freq="2M", name="idx")
+
+        result = idx.to_timestamp()
+        expected = DatetimeIndex(
+            ["2011-01-01", "NaT", "2011-02-01"], dtype="M8[ns]", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.to_timestamp(how="E")
+        expected = DatetimeIndex(
+            ["2011-02-28", "NaT", "2011-03-31"], dtype="M8[ns]", name="idx"
+        )
+        expected = expected + Timedelta(1, "D") - Timedelta(1, "ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_to_timestamp_pi_combined(self):
+        idx = period_range(start="2011", periods=2, freq="1D1h", name="idx")
+
+        result = idx.to_timestamp()
+        expected = DatetimeIndex(
+            ["2011-01-01 00:00", "2011-01-02 01:00"], dtype="M8[ns]", name="idx"
+        )
+        tm.assert_index_equal(result, expected)
+
+        result = idx.to_timestamp(how="E")
+        expected = DatetimeIndex(
+            ["2011-01-02 00:59:59", "2011-01-03 01:59:59"], name="idx", dtype="M8[ns]"
+        )
+        expected = expected + Timedelta(1, "s") - Timedelta(1, "ns")
+        tm.assert_index_equal(result, expected)
+
+        result = idx.to_timestamp(how="E", freq="h")
+        expected = DatetimeIndex(
+            ["2011-01-02 00:00", "2011-01-03 01:00"], dtype="M8[ns]", name="idx"
+        )
+        expected = expected + Timedelta(1, "h") - Timedelta(1, "ns")
+        tm.assert_index_equal(result, expected)
+
+    def test_to_timestamp_1703(self):
+        index = period_range("1/1/2012", periods=4, freq="D")
+
+        result = index.to_timestamp()
+        assert result[0] == Timestamp("1/1/2012")