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venv/lib/python3.10/site-packages/pandas/tests/indexes/numeric/test_astype.py

@@ -0,0 +1,95 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    Index,
+    to_datetime,
+    to_timedelta,
+)
+import pandas._testing as tm
+
+
+class TestAstype:
+    def test_astype_float64_to_uint64(self):
+        # GH#45309 used to incorrectly return Index with int64 dtype
+        idx = Index([0.0, 5.0, 10.0, 15.0, 20.0], dtype=np.float64)
+        result = idx.astype("u8")
+        expected = Index([0, 5, 10, 15, 20], dtype=np.uint64)
+        tm.assert_index_equal(result, expected, exact=True)
+
+        idx_with_negatives = idx - 10
+        with pytest.raises(ValueError, match="losslessly"):
+            idx_with_negatives.astype(np.uint64)
+
+    def test_astype_float64_to_object(self):
+        float_index = Index([0.0, 2.5, 5.0, 7.5, 10.0], dtype=np.float64)
+        result = float_index.astype(object)
+        assert result.equals(float_index)
+        assert float_index.equals(result)
+        assert isinstance(result, Index) and result.dtype == object
+
+    def test_astype_float64_mixed_to_object(self):
+        # mixed int-float
+        idx = Index([1.5, 2, 3, 4, 5], dtype=np.float64)
+        idx.name = "foo"
+        result = idx.astype(object)
+        assert result.equals(idx)
+        assert idx.equals(result)
+        assert isinstance(result, Index) and result.dtype == object
+
+    @pytest.mark.parametrize("dtype", ["int16", "int32", "int64"])
+    def test_astype_float64_to_int_dtype(self, dtype):
+        # GH#12881
+        # a float astype int
+        idx = Index([0, 1, 2], dtype=np.float64)
+        result = idx.astype(dtype)
+        expected = Index([0, 1, 2], dtype=dtype)
+        tm.assert_index_equal(result, expected, exact=True)
+
+        idx = Index([0, 1.1, 2], dtype=np.float64)
+        result = idx.astype(dtype)
+        expected = Index([0, 1, 2], dtype=dtype)
+        tm.assert_index_equal(result, expected, exact=True)
+
+    @pytest.mark.parametrize("dtype", ["float32", "float64"])
+    def test_astype_float64_to_float_dtype(self, dtype):
+        # GH#12881
+        # a float astype int
+        idx = Index([0, 1, 2], dtype=np.float64)
+        result = idx.astype(dtype)
+        assert isinstance(result, Index) and result.dtype == dtype
+
+    @pytest.mark.parametrize("dtype", ["M8[ns]", "m8[ns]"])
+    def test_astype_float_to_datetimelike(self, dtype):
+        # GH#49660 pre-2.0 Index.astype from floating to M8/m8/Period raised,
+        #  inconsistent with Series.astype
+        idx = Index([0, 1.1, 2], dtype=np.float64)
+
+        result = idx.astype(dtype)
+        if dtype[0] == "M":
+            expected = to_datetime(idx.values)
+        else:
+            expected = to_timedelta(idx.values)
+        tm.assert_index_equal(result, expected)
+
+        # check that we match Series behavior
+        result = idx.to_series().set_axis(range(3)).astype(dtype)
+        expected = expected.to_series().set_axis(range(3))
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("dtype", [int, "int16", "int32", "int64"])
+    @pytest.mark.parametrize("non_finite", [np.inf, np.nan])
+    def test_cannot_cast_inf_to_int(self, non_finite, dtype):
+        # GH#13149
+        idx = Index([1, 2, non_finite], dtype=np.float64)
+
+        msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
+        with pytest.raises(ValueError, match=msg):
+            idx.astype(dtype)
+
+    def test_astype_from_object(self):
+        index = Index([1.0, np.nan, 0.2], dtype="object")
+        result = index.astype(float)
+        expected = Index([1.0, np.nan, 0.2], dtype=np.float64)
+        assert result.dtype == expected.dtype
+        tm.assert_index_equal(result, expected)

venv/lib/python3.10/site-packages/pandas/tests/indexes/numeric/test_indexing.py

@@ -0,0 +1,611 @@
+import numpy as np
+import pytest
+
+from pandas.errors import InvalidIndexError
+
+from pandas import (
+    NA,
+    Index,
+    RangeIndex,
+    Series,
+    Timestamp,
+)
+import pandas._testing as tm
+from pandas.core.arrays import (
+    ArrowExtensionArray,
+    FloatingArray,
+)
+
+
+@pytest.fixture
+def index_large():
+    # large values used in Index[uint64] tests where no compat needed with Int64/Float64
+    large = [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25]
+    return Index(large, dtype=np.uint64)
+
+
+class TestGetLoc:
+    def test_get_loc(self):
+        index = Index([0, 1, 2])
+        assert index.get_loc(1) == 1
+
+    def test_get_loc_raises_bad_label(self):
+        index = Index([0, 1, 2])
+        with pytest.raises(InvalidIndexError, match=r"\[1, 2\]"):
+            index.get_loc([1, 2])
+
+    def test_get_loc_float64(self):
+        idx = Index([0.0, 1.0, 2.0], dtype=np.float64)
+
+        with pytest.raises(KeyError, match="^'foo'$"):
+            idx.get_loc("foo")
+        with pytest.raises(KeyError, match=r"^1\.5$"):
+            idx.get_loc(1.5)
+        with pytest.raises(KeyError, match="^True$"):
+            idx.get_loc(True)
+        with pytest.raises(KeyError, match="^False$"):
+            idx.get_loc(False)
+
+    def test_get_loc_na(self):
+        idx = Index([np.nan, 1, 2], dtype=np.float64)
+        assert idx.get_loc(1) == 1
+        assert idx.get_loc(np.nan) == 0
+
+        idx = Index([np.nan, 1, np.nan], dtype=np.float64)
+        assert idx.get_loc(1) == 1
+
+        # representable by slice [0:2:2]
+        msg = "'Cannot get left slice bound for non-unique label: nan'"
+        with pytest.raises(KeyError, match=msg):
+            idx.slice_locs(np.nan)
+        # not representable by slice
+        idx = Index([np.nan, 1, np.nan, np.nan], dtype=np.float64)
+        assert idx.get_loc(1) == 1
+        msg = "'Cannot get left slice bound for non-unique label: nan"
+        with pytest.raises(KeyError, match=msg):
+            idx.slice_locs(np.nan)
+
+    def test_get_loc_missing_nan(self):
+        # GH#8569
+        idx = Index([1, 2], dtype=np.float64)
+        assert idx.get_loc(1) == 0
+        with pytest.raises(KeyError, match=r"^3$"):
+            idx.get_loc(3)
+        with pytest.raises(KeyError, match="^nan$"):
+            idx.get_loc(np.nan)
+        with pytest.raises(InvalidIndexError, match=r"\[nan\]"):
+            # listlike/non-hashable raises TypeError
+            idx.get_loc([np.nan])
+
+    @pytest.mark.parametrize("vals", [[1], [1.0], [Timestamp("2019-12-31")], ["test"]])
+    def test_get_loc_float_index_nan_with_method(self, vals):
+        # GH#39382
+        idx = Index(vals)
+        with pytest.raises(KeyError, match="nan"):
+            idx.get_loc(np.nan)
+
+    @pytest.mark.parametrize("dtype", ["f8", "i8", "u8"])
+    def test_get_loc_numericindex_none_raises(self, dtype):
+        # case that goes through searchsorted and key is non-comparable to values
+        arr = np.arange(10**7, dtype=dtype)
+        idx = Index(arr)
+        with pytest.raises(KeyError, match="None"):
+            idx.get_loc(None)
+
+    def test_get_loc_overflows(self):
+        # unique but non-monotonic goes through IndexEngine.mapping.get_item
+        idx = Index([0, 2, 1])
+
+        val = np.iinfo(np.int64).max + 1
+
+        with pytest.raises(KeyError, match=str(val)):
+            idx.get_loc(val)
+        with pytest.raises(KeyError, match=str(val)):
+            idx._engine.get_loc(val)
+
+
+class TestGetIndexer:
+    def test_get_indexer(self):
+        index1 = Index([1, 2, 3, 4, 5])
+        index2 = Index([2, 4, 6])
+
+        r1 = index1.get_indexer(index2)
+        e1 = np.array([1, 3, -1], dtype=np.intp)
+        tm.assert_almost_equal(r1, e1)
+
+    @pytest.mark.parametrize("reverse", [True, False])
+    @pytest.mark.parametrize(
+        "expected,method",
+        [
+            (np.array([-1, 0, 0, 1, 1], dtype=np.intp), "pad"),
+            (np.array([-1, 0, 0, 1, 1], dtype=np.intp), "ffill"),
+            (np.array([0, 0, 1, 1, 2], dtype=np.intp), "backfill"),
+            (np.array([0, 0, 1, 1, 2], dtype=np.intp), "bfill"),
+        ],
+    )
+    def test_get_indexer_methods(self, reverse, expected, method):
+        index1 = Index([1, 2, 3, 4, 5])
+        index2 = Index([2, 4, 6])
+
+        if reverse:
+            index1 = index1[::-1]
+            expected = expected[::-1]
+
+        result = index2.get_indexer(index1, method=method)
+        tm.assert_almost_equal(result, expected)
+
+    def test_get_indexer_invalid(self):
+        # GH10411
+        index = Index(np.arange(10))
+
+        with pytest.raises(ValueError, match="tolerance argument"):
+            index.get_indexer([1, 0], tolerance=1)
+
+        with pytest.raises(ValueError, match="limit argument"):
+            index.get_indexer([1, 0], limit=1)
+
+    @pytest.mark.parametrize(
+        "method, tolerance, indexer, expected",
+        [
+            ("pad", None, [0, 5, 9], [0, 5, 9]),
+            ("backfill", None, [0, 5, 9], [0, 5, 9]),
+            ("nearest", None, [0, 5, 9], [0, 5, 9]),
+            ("pad", 0, [0, 5, 9], [0, 5, 9]),
+            ("backfill", 0, [0, 5, 9], [0, 5, 9]),
+            ("nearest", 0, [0, 5, 9], [0, 5, 9]),
+            ("pad", None, [0.2, 1.8, 8.5], [0, 1, 8]),
+            ("backfill", None, [0.2, 1.8, 8.5], [1, 2, 9]),
+            ("nearest", None, [0.2, 1.8, 8.5], [0, 2, 9]),
+            ("pad", 1, [0.2, 1.8, 8.5], [0, 1, 8]),
+            ("backfill", 1, [0.2, 1.8, 8.5], [1, 2, 9]),
+            ("nearest", 1, [0.2, 1.8, 8.5], [0, 2, 9]),
+            ("pad", 0.2, [0.2, 1.8, 8.5], [0, -1, -1]),
+            ("backfill", 0.2, [0.2, 1.8, 8.5], [-1, 2, -1]),
+            ("nearest", 0.2, [0.2, 1.8, 8.5], [0, 2, -1]),
+        ],
+    )
+    def test_get_indexer_nearest(self, method, tolerance, indexer, expected):
+        index = Index(np.arange(10))
+
+        actual = index.get_indexer(indexer, method=method, tolerance=tolerance)
+        tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
+
+    @pytest.mark.parametrize("listtype", [list, tuple, Series, np.array])
+    @pytest.mark.parametrize(
+        "tolerance, expected",
+        list(
+            zip(
+                [[0.3, 0.3, 0.1], [0.2, 0.1, 0.1], [0.1, 0.5, 0.5]],
+                [[0, 2, -1], [0, -1, -1], [-1, 2, 9]],
+            )
+        ),
+    )
+    def test_get_indexer_nearest_listlike_tolerance(
+        self, tolerance, expected, listtype
+    ):
+        index = Index(np.arange(10))
+
+        actual = index.get_indexer(
+            [0.2, 1.8, 8.5], method="nearest", tolerance=listtype(tolerance)
+        )
+        tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
+
+    def test_get_indexer_nearest_error(self):
+        index = Index(np.arange(10))
+        with pytest.raises(ValueError, match="limit argument"):
+            index.get_indexer([1, 0], method="nearest", limit=1)
+
+        with pytest.raises(ValueError, match="tolerance size must match"):
+            index.get_indexer([1, 0], method="nearest", tolerance=[1, 2, 3])
+
+    @pytest.mark.parametrize(
+        "method,expected",
+        [("pad", [8, 7, 0]), ("backfill", [9, 8, 1]), ("nearest", [9, 7, 0])],
+    )
+    def test_get_indexer_nearest_decreasing(self, method, expected):
+        index = Index(np.arange(10))[::-1]
+
+        actual = index.get_indexer([0, 5, 9], method=method)
+        tm.assert_numpy_array_equal(actual, np.array([9, 4, 0], dtype=np.intp))
+
+        actual = index.get_indexer([0.2, 1.8, 8.5], method=method)
+        tm.assert_numpy_array_equal(actual, np.array(expected, dtype=np.intp))
+
+    @pytest.mark.parametrize("idx_dtype", ["int64", "float64", "uint64", "range"])
+    @pytest.mark.parametrize("method", ["get_indexer", "get_indexer_non_unique"])
+    def test_get_indexer_numeric_index_boolean_target(self, method, idx_dtype):
+        # GH 16877
+
+        if idx_dtype == "range":
+            numeric_index = RangeIndex(4)
+        else:
+            numeric_index = Index(np.arange(4, dtype=idx_dtype))
+
+        other = Index([True, False, True])
+
+        result = getattr(numeric_index, method)(other)
+        expected = np.array([-1, -1, -1], dtype=np.intp)
+        if method == "get_indexer":
+            tm.assert_numpy_array_equal(result, expected)
+        else:
+            missing = np.arange(3, dtype=np.intp)
+            tm.assert_numpy_array_equal(result[0], expected)
+            tm.assert_numpy_array_equal(result[1], missing)
+
+    @pytest.mark.parametrize("method", ["pad", "backfill", "nearest"])
+    def test_get_indexer_with_method_numeric_vs_bool(self, method):
+        left = Index([1, 2, 3])
+        right = Index([True, False])
+
+        with pytest.raises(TypeError, match="Cannot compare"):
+            left.get_indexer(right, method=method)
+
+        with pytest.raises(TypeError, match="Cannot compare"):
+            right.get_indexer(left, method=method)
+
+    def test_get_indexer_numeric_vs_bool(self):
+        left = Index([1, 2, 3])
+        right = Index([True, False])
+
+        res = left.get_indexer(right)
+        expected = -1 * np.ones(len(right), dtype=np.intp)
+        tm.assert_numpy_array_equal(res, expected)
+
+        res = right.get_indexer(left)
+        expected = -1 * np.ones(len(left), dtype=np.intp)
+        tm.assert_numpy_array_equal(res, expected)
+
+        res = left.get_indexer_non_unique(right)[0]
+        expected = -1 * np.ones(len(right), dtype=np.intp)
+        tm.assert_numpy_array_equal(res, expected)
+
+        res = right.get_indexer_non_unique(left)[0]
+        expected = -1 * np.ones(len(left), dtype=np.intp)
+        tm.assert_numpy_array_equal(res, expected)
+
+    def test_get_indexer_float64(self):
+        idx = Index([0.0, 1.0, 2.0], dtype=np.float64)
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(idx), np.array([0, 1, 2], dtype=np.intp)
+        )
+
+        target = [-0.1, 0.5, 1.1]
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
+        )
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
+        )
+        tm.assert_numpy_array_equal(
+            idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
+        )
+
+    def test_get_indexer_nan(self):
+        # GH#7820
+        result = Index([1, 2, np.nan], dtype=np.float64).get_indexer([np.nan])
+        expected = np.array([2], dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_get_indexer_int64(self):
+        index = Index(range(0, 20, 2), dtype=np.int64)
+        target = Index(np.arange(10), dtype=np.int64)
+        indexer = index.get_indexer(target)
+        expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, expected)
+
+        target = Index(np.arange(10), dtype=np.int64)
+        indexer = index.get_indexer(target, method="pad")
+        expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, expected)
+
+        target = Index(np.arange(10), dtype=np.int64)
+        indexer = index.get_indexer(target, method="backfill")
+        expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, expected)
+
+    def test_get_indexer_uint64(self, index_large):
+        target = Index(np.arange(10).astype("uint64") * 5 + 2**63)
+        indexer = index_large.get_indexer(target)
+        expected = np.array([0, -1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, expected)
+
+        target = Index(np.arange(10).astype("uint64") * 5 + 2**63)
+        indexer = index_large.get_indexer(target, method="pad")
+        expected = np.array([0, 0, 1, 2, 3, 4, 4, 4, 4, 4], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, expected)
+
+        target = Index(np.arange(10).astype("uint64") * 5 + 2**63)
+        indexer = index_large.get_indexer(target, method="backfill")
+        expected = np.array([0, 1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
+        tm.assert_numpy_array_equal(indexer, expected)
+
+    @pytest.mark.parametrize("val, val2", [(4, 5), (4, 4), (4, NA), (NA, NA)])
+    def test_get_loc_masked(self, val, val2, any_numeric_ea_and_arrow_dtype):
+        # GH#39133
+        idx = Index([1, 2, 3, val, val2], dtype=any_numeric_ea_and_arrow_dtype)
+        result = idx.get_loc(2)
+        assert result == 1
+
+        with pytest.raises(KeyError, match="9"):
+            idx.get_loc(9)
+
+    def test_get_loc_masked_na(self, any_numeric_ea_and_arrow_dtype):
+        # GH#39133
+        idx = Index([1, 2, NA], dtype=any_numeric_ea_and_arrow_dtype)
+        result = idx.get_loc(NA)
+        assert result == 2
+
+        idx = Index([1, 2, NA, NA], dtype=any_numeric_ea_and_arrow_dtype)
+        result = idx.get_loc(NA)
+        tm.assert_numpy_array_equal(result, np.array([False, False, True, True]))
+
+        idx = Index([1, 2, 3], dtype=any_numeric_ea_and_arrow_dtype)
+        with pytest.raises(KeyError, match="NA"):
+            idx.get_loc(NA)
+
+    def test_get_loc_masked_na_and_nan(self):
+        # GH#39133
+        idx = Index(
+            FloatingArray(
+                np.array([1, 2, 1, np.nan]), mask=np.array([False, False, True, False])
+            )
+        )
+        result = idx.get_loc(NA)
+        assert result == 2
+        result = idx.get_loc(np.nan)
+        assert result == 3
+
+        idx = Index(
+            FloatingArray(np.array([1, 2, 1.0]), mask=np.array([False, False, True]))
+        )
+        result = idx.get_loc(NA)
+        assert result == 2
+        with pytest.raises(KeyError, match="nan"):
+            idx.get_loc(np.nan)
+
+        idx = Index(
+            FloatingArray(
+                np.array([1, 2, np.nan]), mask=np.array([False, False, False])
+            )
+        )
+        result = idx.get_loc(np.nan)
+        assert result == 2
+        with pytest.raises(KeyError, match="NA"):
+            idx.get_loc(NA)
+
+    @pytest.mark.parametrize("val", [4, 2])
+    def test_get_indexer_masked_na(self, any_numeric_ea_and_arrow_dtype, val):
+        # GH#39133
+        idx = Index([1, 2, NA, 3, val], dtype=any_numeric_ea_and_arrow_dtype)
+        result = idx.get_indexer_for([1, NA, 5])
+        expected = np.array([0, 2, -1])
+        tm.assert_numpy_array_equal(result, expected, check_dtype=False)
+
+    @pytest.mark.parametrize("dtype", ["boolean", "bool[pyarrow]"])
+    def test_get_indexer_masked_na_boolean(self, dtype):
+        # GH#39133
+        if dtype == "bool[pyarrow]":
+            pytest.importorskip("pyarrow")
+        idx = Index([True, False, NA], dtype=dtype)
+        result = idx.get_loc(False)
+        assert result == 1
+        result = idx.get_loc(NA)
+        assert result == 2
+
+    def test_get_indexer_arrow_dictionary_target(self):
+        pa = pytest.importorskip("pyarrow")
+        target = Index(
+            ArrowExtensionArray(
+                pa.array([1, 2], type=pa.dictionary(pa.int8(), pa.int8()))
+            )
+        )
+        idx = Index([1])
+
+        result = idx.get_indexer(target)
+        expected = np.array([0, -1], dtype=np.int64)
+        tm.assert_numpy_array_equal(result, expected)
+
+        result_1, result_2 = idx.get_indexer_non_unique(target)
+        expected_1, expected_2 = np.array([0, -1], dtype=np.int64), np.array(
+            [1], dtype=np.int64
+        )
+        tm.assert_numpy_array_equal(result_1, expected_1)
+        tm.assert_numpy_array_equal(result_2, expected_2)
+
+
+class TestWhere:
+    @pytest.mark.parametrize(
+        "index",
+        [
+            Index(np.arange(5, dtype="float64")),
+            Index(range(0, 20, 2), dtype=np.int64),
+            Index(np.arange(5, dtype="uint64")),
+        ],
+    )
+    def test_where(self, listlike_box, index):
+        cond = [True] * len(index)
+        expected = index
+        result = index.where(listlike_box(cond))
+
+        cond = [False] + [True] * (len(index) - 1)
+        expected = Index([index._na_value] + index[1:].tolist(), dtype=np.float64)
+        result = index.where(listlike_box(cond))
+        tm.assert_index_equal(result, expected)
+
+    def test_where_uint64(self):
+        idx = Index([0, 6, 2], dtype=np.uint64)
+        mask = np.array([False, True, False])
+        other = np.array([1], dtype=np.int64)
+
+        expected = Index([1, 6, 1], dtype=np.uint64)
+
+        result = idx.where(mask, other)
+        tm.assert_index_equal(result, expected)
+
+        result = idx.putmask(~mask, other)
+        tm.assert_index_equal(result, expected)
+
+    def test_where_infers_type_instead_of_trying_to_convert_string_to_float(self):
+        # GH 32413
+        index = Index([1, np.nan])
+        cond = index.notna()
+        other = Index(["a", "b"], dtype="string")
+
+        expected = Index([1.0, "b"])
+        result = index.where(cond, other)
+
+        tm.assert_index_equal(result, expected)
+
+
+class TestTake:
+    @pytest.mark.parametrize("idx_dtype", [np.float64, np.int64, np.uint64])
+    def test_take_preserve_name(self, idx_dtype):
+        index = Index([1, 2, 3, 4], dtype=idx_dtype, name="foo")
+        taken = index.take([3, 0, 1])
+        assert index.name == taken.name
+
+    def test_take_fill_value_float64(self):
+        # GH 12631
+        idx = Index([1.0, 2.0, 3.0], name="xxx", dtype=np.float64)
+        result = idx.take(np.array([1, 0, -1]))
+        expected = Index([2.0, 1.0, 3.0], dtype=np.float64, name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        # fill_value
+        result = idx.take(np.array([1, 0, -1]), fill_value=True)
+        expected = Index([2.0, 1.0, np.nan], dtype=np.float64, name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        # allow_fill=False
+        result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
+        expected = Index([2.0, 1.0, 3.0], dtype=np.float64, name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        msg = (
+            "When allow_fill=True and fill_value is not None, "
+            "all indices must be >= -1"
+        )
+        with pytest.raises(ValueError, match=msg):
+            idx.take(np.array([1, 0, -2]), fill_value=True)
+        with pytest.raises(ValueError, match=msg):
+            idx.take(np.array([1, 0, -5]), fill_value=True)
+
+        msg = "index -5 is out of bounds for (axis 0 with )?size 3"
+        with pytest.raises(IndexError, match=msg):
+            idx.take(np.array([1, -5]))
+
+    @pytest.mark.parametrize("dtype", [np.int64, np.uint64])
+    def test_take_fill_value_ints(self, dtype):
+        # see gh-12631
+        idx = Index([1, 2, 3], dtype=dtype, name="xxx")
+        result = idx.take(np.array([1, 0, -1]))
+        expected = Index([2, 1, 3], dtype=dtype, name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        name = type(idx).__name__
+        msg = f"Unable to fill values because {name} cannot contain NA"
+
+        # fill_value=True
+        with pytest.raises(ValueError, match=msg):
+            idx.take(np.array([1, 0, -1]), fill_value=True)
+
+        # allow_fill=False
+        result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
+        expected = Index([2, 1, 3], dtype=dtype, name="xxx")
+        tm.assert_index_equal(result, expected)
+
+        with pytest.raises(ValueError, match=msg):
+            idx.take(np.array([1, 0, -2]), fill_value=True)
+        with pytest.raises(ValueError, match=msg):
+            idx.take(np.array([1, 0, -5]), fill_value=True)
+
+        msg = "index -5 is out of bounds for (axis 0 with )?size 3"
+        with pytest.raises(IndexError, match=msg):
+            idx.take(np.array([1, -5]))
+
+
+class TestContains:
+    @pytest.mark.parametrize("dtype", [np.float64, np.int64, np.uint64])
+    def test_contains_none(self, dtype):
+        # GH#35788 should return False, not raise TypeError
+        index = Index([0, 1, 2, 3, 4], dtype=dtype)
+        assert None not in index
+
+    def test_contains_float64_nans(self):
+        index = Index([1.0, 2.0, np.nan], dtype=np.float64)
+        assert np.nan in index
+
+    def test_contains_float64_not_nans(self):
+        index = Index([1.0, 2.0, np.nan], dtype=np.float64)
+        assert 1.0 in index
+
+
+class TestSliceLocs:
+    @pytest.mark.parametrize("dtype", [int, float])
+    def test_slice_locs(self, dtype):
+        index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
+        n = len(index)
+
+        assert index.slice_locs(start=2) == (2, n)
+        assert index.slice_locs(start=3) == (3, n)
+        assert index.slice_locs(3, 8) == (3, 6)
+        assert index.slice_locs(5, 10) == (3, n)
+        assert index.slice_locs(end=8) == (0, 6)
+        assert index.slice_locs(end=9) == (0, 7)
+
+        # reversed
+        index2 = index[::-1]
+        assert index2.slice_locs(8, 2) == (2, 6)
+        assert index2.slice_locs(7, 3) == (2, 5)
+
+    @pytest.mark.parametrize("dtype", [int, float])
+    def test_slice_locs_float_locs(self, dtype):
+        index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
+        n = len(index)
+        assert index.slice_locs(5.0, 10.0) == (3, n)
+        assert index.slice_locs(4.5, 10.5) == (3, 8)
+
+        index2 = index[::-1]
+        assert index2.slice_locs(8.5, 1.5) == (2, 6)
+        assert index2.slice_locs(10.5, -1) == (0, n)
+
+    @pytest.mark.parametrize("dtype", [int, float])
+    def test_slice_locs_dup_numeric(self, dtype):
+        index = Index(np.array([10, 12, 12, 14], dtype=dtype))
+        assert index.slice_locs(12, 12) == (1, 3)
+        assert index.slice_locs(11, 13) == (1, 3)
+
+        index2 = index[::-1]
+        assert index2.slice_locs(12, 12) == (1, 3)
+        assert index2.slice_locs(13, 11) == (1, 3)
+
+    def test_slice_locs_na(self):
+        index = Index([np.nan, 1, 2])
+        assert index.slice_locs(1) == (1, 3)
+        assert index.slice_locs(np.nan) == (0, 3)
+
+        index = Index([0, np.nan, np.nan, 1, 2])
+        assert index.slice_locs(np.nan) == (1, 5)
+
+    def test_slice_locs_na_raises(self):
+        index = Index([np.nan, 1, 2])
+        with pytest.raises(KeyError, match=""):
+            index.slice_locs(start=1.5)
+
+        with pytest.raises(KeyError, match=""):
+            index.slice_locs(end=1.5)
+
+
+class TestGetSliceBounds:
+    @pytest.mark.parametrize("side, expected", [("left", 4), ("right", 5)])
+    def test_get_slice_bounds_within(self, side, expected):
+        index = Index(range(6))
+        result = index.get_slice_bound(4, side=side)
+        assert result == expected
+
+    @pytest.mark.parametrize("side", ["left", "right"])
+    @pytest.mark.parametrize("bound, expected", [(-1, 0), (10, 6)])
+    def test_get_slice_bounds_outside(self, side, expected, bound):
+        index = Index(range(6))
+        result = index.get_slice_bound(bound, side=side)
+        assert result == expected

venv/lib/python3.10/site-packages/pandas/tests/indexes/numeric/test_join.py

@@ -0,0 +1,380 @@
+import numpy as np
+import pytest
+
+import pandas._testing as tm
+from pandas.core.indexes.api import Index
+
+
+class TestJoinInt64Index:
+    def test_join_non_unique(self):
+        left = Index([4, 4, 3, 3])
+
+        joined, lidx, ridx = left.join(left, return_indexers=True)
+
+        exp_joined = Index([4, 4, 4, 4, 3, 3, 3, 3])
+        tm.assert_index_equal(joined, exp_joined)
+
+        exp_lidx = np.array([0, 0, 1, 1, 2, 2, 3, 3], dtype=np.intp)
+        tm.assert_numpy_array_equal(lidx, exp_lidx)
+
+        exp_ridx = np.array([0, 1, 0, 1, 2, 3, 2, 3], dtype=np.intp)
+        tm.assert_numpy_array_equal(ridx, exp_ridx)
+
+    def test_join_inner(self):
+        index = Index(range(0, 20, 2), dtype=np.int64)
+        other = Index([7, 12, 25, 1, 2, 5], dtype=np.int64)
+        other_mono = Index([1, 2, 5, 7, 12, 25], dtype=np.int64)
+
+        # not monotonic
+        res, lidx, ridx = index.join(other, how="inner", return_indexers=True)
+
+        # no guarantee of sortedness, so sort for comparison purposes
+        ind = res.argsort()
+        res = res.take(ind)
+        lidx = lidx.take(ind)
+        ridx = ridx.take(ind)
+
+        eres = Index([2, 12], dtype=np.int64)
+        elidx = np.array([1, 6], dtype=np.intp)
+        eridx = np.array([4, 1], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # monotonic
+        res, lidx, ridx = index.join(other_mono, how="inner", return_indexers=True)
+
+        res2 = index.intersection(other_mono)
+        tm.assert_index_equal(res, res2)
+
+        elidx = np.array([1, 6], dtype=np.intp)
+        eridx = np.array([1, 4], dtype=np.intp)
+        assert isinstance(res, Index) and res.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+    def test_join_left(self):
+        index = Index(range(0, 20, 2), dtype=np.int64)
+        other = Index([7, 12, 25, 1, 2, 5], dtype=np.int64)
+        other_mono = Index([1, 2, 5, 7, 12, 25], dtype=np.int64)
+
+        # not monotonic
+        res, lidx, ridx = index.join(other, how="left", return_indexers=True)
+        eres = index
+        eridx = np.array([-1, 4, -1, -1, -1, -1, 1, -1, -1, -1], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        assert lidx is None
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # monotonic
+        res, lidx, ridx = index.join(other_mono, how="left", return_indexers=True)
+        eridx = np.array([-1, 1, -1, -1, -1, -1, 4, -1, -1, -1], dtype=np.intp)
+        assert isinstance(res, Index) and res.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        assert lidx is None
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # non-unique
+        idx = Index([1, 1, 2, 5])
+        idx2 = Index([1, 2, 5, 7, 9])
+        res, lidx, ridx = idx2.join(idx, how="left", return_indexers=True)
+        eres = Index([1, 1, 2, 5, 7, 9])  # 1 is in idx2, so it should be x2
+        eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
+        elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+    def test_join_right(self):
+        index = Index(range(0, 20, 2), dtype=np.int64)
+        other = Index([7, 12, 25, 1, 2, 5], dtype=np.int64)
+        other_mono = Index([1, 2, 5, 7, 12, 25], dtype=np.int64)
+
+        # not monotonic
+        res, lidx, ridx = index.join(other, how="right", return_indexers=True)
+        eres = other
+        elidx = np.array([-1, 6, -1, -1, 1, -1], dtype=np.intp)
+
+        assert isinstance(other, Index) and other.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        assert ridx is None
+
+        # monotonic
+        res, lidx, ridx = index.join(other_mono, how="right", return_indexers=True)
+        eres = other_mono
+        elidx = np.array([-1, 1, -1, -1, 6, -1], dtype=np.intp)
+        assert isinstance(other, Index) and other.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        assert ridx is None
+
+        # non-unique
+        idx = Index([1, 1, 2, 5])
+        idx2 = Index([1, 2, 5, 7, 9])
+        res, lidx, ridx = idx.join(idx2, how="right", return_indexers=True)
+        eres = Index([1, 1, 2, 5, 7, 9])  # 1 is in idx2, so it should be x2
+        elidx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
+        eridx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+    def test_join_non_int_index(self):
+        index = Index(range(0, 20, 2), dtype=np.int64)
+        other = Index([3, 6, 7, 8, 10], dtype=object)
+
+        outer = index.join(other, how="outer")
+        outer2 = other.join(index, how="outer")
+        expected = Index([0, 2, 3, 4, 6, 7, 8, 10, 12, 14, 16, 18])
+        tm.assert_index_equal(outer, outer2)
+        tm.assert_index_equal(outer, expected)
+
+        inner = index.join(other, how="inner")
+        inner2 = other.join(index, how="inner")
+        expected = Index([6, 8, 10])
+        tm.assert_index_equal(inner, inner2)
+        tm.assert_index_equal(inner, expected)
+
+        left = index.join(other, how="left")
+        tm.assert_index_equal(left, index.astype(object))
+
+        left2 = other.join(index, how="left")
+        tm.assert_index_equal(left2, other)
+
+        right = index.join(other, how="right")
+        tm.assert_index_equal(right, other)
+
+        right2 = other.join(index, how="right")
+        tm.assert_index_equal(right2, index.astype(object))
+
+    def test_join_outer(self):
+        index = Index(range(0, 20, 2), dtype=np.int64)
+        other = Index([7, 12, 25, 1, 2, 5], dtype=np.int64)
+        other_mono = Index([1, 2, 5, 7, 12, 25], dtype=np.int64)
+
+        # not monotonic
+        # guarantee of sortedness
+        res, lidx, ridx = index.join(other, how="outer", return_indexers=True)
+        noidx_res = index.join(other, how="outer")
+        tm.assert_index_equal(res, noidx_res)
+
+        eres = Index([0, 1, 2, 4, 5, 6, 7, 8, 10, 12, 14, 16, 18, 25], dtype=np.int64)
+        elidx = np.array([0, -1, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, 9, -1], dtype=np.intp)
+        eridx = np.array(
+            [-1, 3, 4, -1, 5, -1, 0, -1, -1, 1, -1, -1, -1, 2], dtype=np.intp
+        )
+
+        assert isinstance(res, Index) and res.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # monotonic
+        res, lidx, ridx = index.join(other_mono, how="outer", return_indexers=True)
+        noidx_res = index.join(other_mono, how="outer")
+        tm.assert_index_equal(res, noidx_res)
+
+        elidx = np.array([0, -1, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, 9, -1], dtype=np.intp)
+        eridx = np.array(
+            [-1, 0, 1, -1, 2, -1, 3, -1, -1, 4, -1, -1, -1, 5], dtype=np.intp
+        )
+        assert isinstance(res, Index) and res.dtype == np.int64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+
+class TestJoinUInt64Index:
+    @pytest.fixture
+    def index_large(self):
+        # large values used in TestUInt64Index where no compat needed with int64/float64
+        large = [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25]
+        return Index(large, dtype=np.uint64)
+
+    def test_join_inner(self, index_large):
+        other = Index(2**63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
+        other_mono = Index(2**63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64"))
+
+        # not monotonic
+        res, lidx, ridx = index_large.join(other, how="inner", return_indexers=True)
+
+        # no guarantee of sortedness, so sort for comparison purposes
+        ind = res.argsort()
+        res = res.take(ind)
+        lidx = lidx.take(ind)
+        ridx = ridx.take(ind)
+
+        eres = Index(2**63 + np.array([10, 25], dtype="uint64"))
+        elidx = np.array([1, 4], dtype=np.intp)
+        eridx = np.array([5, 2], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # monotonic
+        res, lidx, ridx = index_large.join(
+            other_mono, how="inner", return_indexers=True
+        )
+
+        res2 = index_large.intersection(other_mono)
+        tm.assert_index_equal(res, res2)
+
+        elidx = np.array([1, 4], dtype=np.intp)
+        eridx = np.array([3, 5], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+    def test_join_left(self, index_large):
+        other = Index(2**63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
+        other_mono = Index(2**63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64"))
+
+        # not monotonic
+        res, lidx, ridx = index_large.join(other, how="left", return_indexers=True)
+        eres = index_large
+        eridx = np.array([-1, 5, -1, -1, 2], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        assert lidx is None
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # monotonic
+        res, lidx, ridx = index_large.join(other_mono, how="left", return_indexers=True)
+        eridx = np.array([-1, 3, -1, -1, 5], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        assert lidx is None
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # non-unique
+        idx = Index(2**63 + np.array([1, 1, 2, 5], dtype="uint64"))
+        idx2 = Index(2**63 + np.array([1, 2, 5, 7, 9], dtype="uint64"))
+        res, lidx, ridx = idx2.join(idx, how="left", return_indexers=True)
+
+        # 1 is in idx2, so it should be x2
+        eres = Index(2**63 + np.array([1, 1, 2, 5, 7, 9], dtype="uint64"))
+        eridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
+        elidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
+
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+    def test_join_right(self, index_large):
+        other = Index(2**63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
+        other_mono = Index(2**63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64"))
+
+        # not monotonic
+        res, lidx, ridx = index_large.join(other, how="right", return_indexers=True)
+        eres = other
+        elidx = np.array([-1, -1, 4, -1, -1, 1], dtype=np.intp)
+
+        tm.assert_numpy_array_equal(lidx, elidx)
+        assert isinstance(other, Index) and other.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        assert ridx is None
+
+        # monotonic
+        res, lidx, ridx = index_large.join(
+            other_mono, how="right", return_indexers=True
+        )
+        eres = other_mono
+        elidx = np.array([-1, -1, -1, 1, -1, 4], dtype=np.intp)
+
+        assert isinstance(other, Index) and other.dtype == np.uint64
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_index_equal(res, eres)
+        assert ridx is None
+
+        # non-unique
+        idx = Index(2**63 + np.array([1, 1, 2, 5], dtype="uint64"))
+        idx2 = Index(2**63 + np.array([1, 2, 5, 7, 9], dtype="uint64"))
+        res, lidx, ridx = idx.join(idx2, how="right", return_indexers=True)
+
+        # 1 is in idx2, so it should be x2
+        eres = Index(2**63 + np.array([1, 1, 2, 5, 7, 9], dtype="uint64"))
+        elidx = np.array([0, 1, 2, 3, -1, -1], dtype=np.intp)
+        eridx = np.array([0, 0, 1, 2, 3, 4], dtype=np.intp)
+
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+    def test_join_non_int_index(self, index_large):
+        other = Index(
+            2**63 + np.array([1, 5, 7, 10, 20], dtype="uint64"), dtype=object
+        )
+
+        outer = index_large.join(other, how="outer")
+        outer2 = other.join(index_large, how="outer")
+        expected = Index(
+            2**63 + np.array([0, 1, 5, 7, 10, 15, 20, 25], dtype="uint64")
+        )
+        tm.assert_index_equal(outer, outer2)
+        tm.assert_index_equal(outer, expected)
+
+        inner = index_large.join(other, how="inner")
+        inner2 = other.join(index_large, how="inner")
+        expected = Index(2**63 + np.array([10, 20], dtype="uint64"))
+        tm.assert_index_equal(inner, inner2)
+        tm.assert_index_equal(inner, expected)
+
+        left = index_large.join(other, how="left")
+        tm.assert_index_equal(left, index_large.astype(object))
+
+        left2 = other.join(index_large, how="left")
+        tm.assert_index_equal(left2, other)
+
+        right = index_large.join(other, how="right")
+        tm.assert_index_equal(right, other)
+
+        right2 = other.join(index_large, how="right")
+        tm.assert_index_equal(right2, index_large.astype(object))
+
+    def test_join_outer(self, index_large):
+        other = Index(2**63 + np.array([7, 12, 25, 1, 2, 10], dtype="uint64"))
+        other_mono = Index(2**63 + np.array([1, 2, 7, 10, 12, 25], dtype="uint64"))
+
+        # not monotonic
+        # guarantee of sortedness
+        res, lidx, ridx = index_large.join(other, how="outer", return_indexers=True)
+        noidx_res = index_large.join(other, how="outer")
+        tm.assert_index_equal(res, noidx_res)
+
+        eres = Index(
+            2**63 + np.array([0, 1, 2, 7, 10, 12, 15, 20, 25], dtype="uint64")
+        )
+        elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
+        eridx = np.array([-1, 3, 4, 0, 5, 1, -1, -1, 2], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)
+
+        # monotonic
+        res, lidx, ridx = index_large.join(
+            other_mono, how="outer", return_indexers=True
+        )
+        noidx_res = index_large.join(other_mono, how="outer")
+        tm.assert_index_equal(res, noidx_res)
+
+        elidx = np.array([0, -1, -1, -1, 1, -1, 2, 3, 4], dtype=np.intp)
+        eridx = np.array([-1, 0, 1, 2, 3, 4, -1, -1, 5], dtype=np.intp)
+
+        assert isinstance(res, Index) and res.dtype == np.uint64
+        tm.assert_index_equal(res, eres)
+        tm.assert_numpy_array_equal(lidx, elidx)
+        tm.assert_numpy_array_equal(ridx, eridx)

venv/lib/python3.10/site-packages/pandas/tests/indexes/numeric/test_setops.py

@@ -0,0 +1,168 @@
+from datetime import (
+    datetime,
+    timedelta,
+)
+
+import numpy as np
+import pytest
+
+import pandas._testing as tm
+from pandas.core.indexes.api import (
+    Index,
+    RangeIndex,
+)
+
+
+@pytest.fixture
+def index_large():
+    # large values used in TestUInt64Index where no compat needed with int64/float64
+    large = [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25]
+    return Index(large, dtype=np.uint64)
+
+
+class TestSetOps:
+    @pytest.mark.parametrize("dtype", ["f8", "u8", "i8"])
+    def test_union_non_numeric(self, dtype):
+        # corner case, non-numeric
+        index = Index(np.arange(5, dtype=dtype), dtype=dtype)
+        assert index.dtype == dtype
+
+        other = Index([datetime.now() + timedelta(i) for i in range(4)], dtype=object)
+        result = index.union(other)
+        expected = Index(np.concatenate((index, other)))
+        tm.assert_index_equal(result, expected)
+
+        result = other.union(index)
+        expected = Index(np.concatenate((other, index)))
+        tm.assert_index_equal(result, expected)
+
+    def test_intersection(self):
+        index = Index(range(5), dtype=np.int64)
+
+        other = Index([1, 2, 3, 4, 5])
+        result = index.intersection(other)
+        expected = Index(np.sort(np.intersect1d(index.values, other.values)))
+        tm.assert_index_equal(result, expected)
+
+        result = other.intersection(index)
+        expected = Index(
+            np.sort(np.asarray(np.intersect1d(index.values, other.values)))
+        )
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize("dtype", ["int64", "uint64"])
+    def test_int_float_union_dtype(self, dtype):
+        # https://github.com/pandas-dev/pandas/issues/26778
+        # [u]int | float -> float
+        index = Index([0, 2, 3], dtype=dtype)
+        other = Index([0.5, 1.5], dtype=np.float64)
+        expected = Index([0.0, 0.5, 1.5, 2.0, 3.0], dtype=np.float64)
+        result = index.union(other)
+        tm.assert_index_equal(result, expected)
+
+        result = other.union(index)
+        tm.assert_index_equal(result, expected)
+
+    def test_range_float_union_dtype(self):
+        # https://github.com/pandas-dev/pandas/issues/26778
+        index = RangeIndex(start=0, stop=3)
+        other = Index([0.5, 1.5], dtype=np.float64)
+        result = index.union(other)
+        expected = Index([0.0, 0.5, 1, 1.5, 2.0], dtype=np.float64)
+        tm.assert_index_equal(result, expected)
+
+        result = other.union(index)
+        tm.assert_index_equal(result, expected)
+
+    def test_range_uint64_union_dtype(self):
+        # https://github.com/pandas-dev/pandas/issues/26778
+        index = RangeIndex(start=0, stop=3)
+        other = Index([0, 10], dtype=np.uint64)
+        result = index.union(other)
+        expected = Index([0, 1, 2, 10], dtype=object)
+        tm.assert_index_equal(result, expected)
+
+        result = other.union(index)
+        tm.assert_index_equal(result, expected)
+
+    def test_float64_index_difference(self):
+        # https://github.com/pandas-dev/pandas/issues/35217
+        float_index = Index([1.0, 2, 3])
+        string_index = Index(["1", "2", "3"])
+
+        result = float_index.difference(string_index)
+        tm.assert_index_equal(result, float_index)
+
+        result = string_index.difference(float_index)
+        tm.assert_index_equal(result, string_index)
+
+    def test_intersection_uint64_outside_int64_range(self, index_large):
+        other = Index([2**63, 2**63 + 5, 2**63 + 10, 2**63 + 15, 2**63 + 20])
+        result = index_large.intersection(other)
+        expected = Index(np.sort(np.intersect1d(index_large.values, other.values)))
+        tm.assert_index_equal(result, expected)
+
+        result = other.intersection(index_large)
+        expected = Index(
+            np.sort(np.asarray(np.intersect1d(index_large.values, other.values)))
+        )
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "index2,keeps_name",
+        [
+            (Index([4, 7, 6, 5, 3], name="index"), True),
+            (Index([4, 7, 6, 5, 3], name="other"), False),
+        ],
+    )
+    def test_intersection_monotonic(self, index2, keeps_name, sort):
+        index1 = Index([5, 3, 2, 4, 1], name="index")
+        expected = Index([5, 3, 4])
+
+        if keeps_name:
+            expected.name = "index"
+
+        result = index1.intersection(index2, sort=sort)
+        if sort is None:
+            expected = expected.sort_values()
+        tm.assert_index_equal(result, expected)
+
+    def test_symmetric_difference(self, sort):
+        # smoke
+        index1 = Index([5, 2, 3, 4], name="index1")
+        index2 = Index([2, 3, 4, 1])
+        result = index1.symmetric_difference(index2, sort=sort)
+        expected = Index([5, 1])
+        if sort is not None:
+            tm.assert_index_equal(result, expected)
+        else:
+            tm.assert_index_equal(result, expected.sort_values())
+        assert result.name is None
+        if sort is None:
+            expected = expected.sort_values()
+        tm.assert_index_equal(result, expected)
+
+
+class TestSetOpsSort:
+    @pytest.mark.parametrize("slice_", [slice(None), slice(0)])
+    def test_union_sort_other_special(self, slice_):
+        # https://github.com/pandas-dev/pandas/issues/24959
+
+        idx = Index([1, 0, 2])
+        # default, sort=None
+        other = idx[slice_]
+        tm.assert_index_equal(idx.union(other), idx)
+        tm.assert_index_equal(other.union(idx), idx)
+
+        # sort=False
+        tm.assert_index_equal(idx.union(other, sort=False), idx)
+
+    @pytest.mark.parametrize("slice_", [slice(None), slice(0)])
+    def test_union_sort_special_true(self, slice_):
+        idx = Index([1, 0, 2])
+        # default, sort=None
+        other = idx[slice_]
+
+        result = idx.union(other, sort=True)
+        expected = Index([0, 1, 2])
+        tm.assert_index_equal(result, expected)

venv/lib/python3.10/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/python3.10/site-packages/pandas/tests/indexes/period/methods/test_astype.py

@@ -0,0 +1,151 @@
+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):
+        # 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)
+        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/python3.10/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/python3.10/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/python3.10/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/python3.10/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/python3.10/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/python3.10/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/python3.10/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")

venv/lib/python3.10/site-packages/pandas/tests/indexes/period/test_constructors.py

@@ -0,0 +1,691 @@
+import numpy as np
+import pytest
+
+from pandas._libs.tslibs.period import IncompatibleFrequency
+
+from pandas.core.dtypes.dtypes import PeriodDtype
+
+from pandas import (
+    Index,
+    NaT,
+    Period,
+    PeriodIndex,
+    Series,
+    date_range,
+    offsets,
+    period_range,
+)
+import pandas._testing as tm
+from pandas.core.arrays import PeriodArray
+
+
+class TestPeriodIndexDisallowedFreqs:
+    @pytest.mark.parametrize(
+        "freq,freq_depr",
+        [
+            ("2M", "2ME"),
+            ("2Q-MAR", "2QE-MAR"),
+            ("2Y-FEB", "2YE-FEB"),
+            ("2M", "2me"),
+            ("2Q-MAR", "2qe-MAR"),
+            ("2Y-FEB", "2yE-feb"),
+        ],
+    )
+    def test_period_index_offsets_frequency_error_message(self, freq, freq_depr):
+        # GH#52064
+        msg = f"for Period, please use '{freq[1:]}' instead of '{freq_depr[1:]}'"
+
+        with pytest.raises(ValueError, match=msg):
+            PeriodIndex(["2020-01-01", "2020-01-02"], freq=freq_depr)
+
+        with pytest.raises(ValueError, match=msg):
+            period_range(start="2020-01-01", end="2020-01-02", freq=freq_depr)
+
+    @pytest.mark.parametrize("freq_depr", ["2SME", "2sme", "2CBME", "2BYE", "2Bye"])
+    def test_period_index_frequency_invalid_freq(self, freq_depr):
+        # GH#9586
+        msg = f"Invalid frequency: {freq_depr[1:]}"
+
+        with pytest.raises(ValueError, match=msg):
+            period_range("2020-01", "2020-05", freq=freq_depr)
+        with pytest.raises(ValueError, match=msg):
+            PeriodIndex(["2020-01", "2020-05"], freq=freq_depr)
+
+    @pytest.mark.parametrize("freq", ["2BQE-SEP", "2BYE-MAR", "2BME"])
+    def test_period_index_from_datetime_index_invalid_freq(self, freq):
+        # GH#56899
+        msg = f"Invalid frequency: {freq[1:]}"
+
+        rng = date_range("01-Jan-2012", periods=8, freq=freq)
+        with pytest.raises(ValueError, match=msg):
+            rng.to_period()
+
+
+class TestPeriodIndex:
+    def test_from_ordinals(self):
+        Period(ordinal=-1000, freq="Y")
+        Period(ordinal=0, freq="Y")
+
+        msg = "The 'ordinal' keyword in PeriodIndex is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            idx1 = PeriodIndex(ordinal=[-1, 0, 1], freq="Y")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            idx2 = PeriodIndex(ordinal=np.array([-1, 0, 1]), freq="Y")
+        tm.assert_index_equal(idx1, idx2)
+
+        alt1 = PeriodIndex.from_ordinals([-1, 0, 1], freq="Y")
+        tm.assert_index_equal(alt1, idx1)
+
+        alt2 = PeriodIndex.from_ordinals(np.array([-1, 0, 1]), freq="Y")
+        tm.assert_index_equal(alt2, idx2)
+
+    def test_keyword_mismatch(self):
+        # GH#55961 we should get exactly one of data/ordinals/**fields
+        per = Period("2016-01-01", "D")
+        depr_msg1 = "The 'ordinal' keyword in PeriodIndex is deprecated"
+        depr_msg2 = "Constructing PeriodIndex from fields is deprecated"
+
+        err_msg1 = "Cannot pass both data and ordinal"
+        with pytest.raises(ValueError, match=err_msg1):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg1):
+                PeriodIndex(data=[per], ordinal=[per.ordinal], freq=per.freq)
+
+        err_msg2 = "Cannot pass both data and fields"
+        with pytest.raises(ValueError, match=err_msg2):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg2):
+                PeriodIndex(data=[per], year=[per.year], freq=per.freq)
+
+        err_msg3 = "Cannot pass both ordinal and fields"
+        with pytest.raises(ValueError, match=err_msg3):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg2):
+                PeriodIndex(ordinal=[per.ordinal], year=[per.year], freq=per.freq)
+
+    def test_construction_base_constructor(self):
+        # GH 13664
+        arr = [Period("2011-01", freq="M"), NaT, Period("2011-03", freq="M")]
+        tm.assert_index_equal(Index(arr), PeriodIndex(arr))
+        tm.assert_index_equal(Index(np.array(arr)), PeriodIndex(np.array(arr)))
+
+        arr = [np.nan, NaT, Period("2011-03", freq="M")]
+        tm.assert_index_equal(Index(arr), PeriodIndex(arr))
+        tm.assert_index_equal(Index(np.array(arr)), PeriodIndex(np.array(arr)))
+
+        arr = [Period("2011-01", freq="M"), NaT, Period("2011-03", freq="D")]
+        tm.assert_index_equal(Index(arr), Index(arr, dtype=object))
+
+        tm.assert_index_equal(Index(np.array(arr)), Index(np.array(arr), dtype=object))
+
+    def test_base_constructor_with_period_dtype(self):
+        dtype = PeriodDtype("D")
+        values = ["2011-01-01", "2012-03-04", "2014-05-01"]
+        result = Index(values, dtype=dtype)
+
+        expected = PeriodIndex(values, dtype=dtype)
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "values_constructor", [list, np.array, PeriodIndex, PeriodArray._from_sequence]
+    )
+    def test_index_object_dtype(self, values_constructor):
+        # Index(periods, dtype=object) is an Index (not an PeriodIndex)
+        periods = [
+            Period("2011-01", freq="M"),
+            NaT,
+            Period("2011-03", freq="M"),
+        ]
+        values = values_constructor(periods)
+        result = Index(values, dtype=object)
+
+        assert type(result) is Index
+        tm.assert_numpy_array_equal(result.values, np.array(values))
+
+    def test_constructor_use_start_freq(self):
+        # GH #1118
+        msg1 = "Period with BDay freq is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg1):
+            p = Period("4/2/2012", freq="B")
+        msg2 = r"PeriodDtype\[B\] is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg2):
+            expected = period_range(start="4/2/2012", periods=10, freq="B")
+
+        with tm.assert_produces_warning(FutureWarning, match=msg2):
+            index = period_range(start=p, periods=10)
+        tm.assert_index_equal(index, expected)
+
+    def test_constructor_field_arrays(self):
+        # GH #1264
+
+        years = np.arange(1990, 2010).repeat(4)[2:-2]
+        quarters = np.tile(np.arange(1, 5), 20)[2:-2]
+
+        depr_msg = "Constructing PeriodIndex from fields is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+            index = PeriodIndex(year=years, quarter=quarters, freq="Q-DEC")
+        expected = period_range("1990Q3", "2009Q2", freq="Q-DEC")
+        tm.assert_index_equal(index, expected)
+
+        with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+            index2 = PeriodIndex(year=years, quarter=quarters, freq="2Q-DEC")
+        tm.assert_numpy_array_equal(index.asi8, index2.asi8)
+
+        with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+            index = PeriodIndex(year=years, quarter=quarters)
+        tm.assert_index_equal(index, expected)
+
+        years = [2007, 2007, 2007]
+        months = [1, 2]
+
+        msg = "Mismatched Period array lengths"
+        with pytest.raises(ValueError, match=msg):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+                PeriodIndex(year=years, month=months, freq="M")
+        with pytest.raises(ValueError, match=msg):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+                PeriodIndex(year=years, month=months, freq="2M")
+
+        years = [2007, 2007, 2007]
+        months = [1, 2, 3]
+        with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+            idx = PeriodIndex(year=years, month=months, freq="M")
+        exp = period_range("2007-01", periods=3, freq="M")
+        tm.assert_index_equal(idx, exp)
+
+    def test_constructor_nano(self):
+        idx = period_range(
+            start=Period(ordinal=1, freq="ns"),
+            end=Period(ordinal=4, freq="ns"),
+            freq="ns",
+        )
+        exp = PeriodIndex(
+            [
+                Period(ordinal=1, freq="ns"),
+                Period(ordinal=2, freq="ns"),
+                Period(ordinal=3, freq="ns"),
+                Period(ordinal=4, freq="ns"),
+            ],
+            freq="ns",
+        )
+        tm.assert_index_equal(idx, exp)
+
+    def test_constructor_arrays_negative_year(self):
+        years = np.arange(1960, 2000, dtype=np.int64).repeat(4)
+        quarters = np.tile(np.array([1, 2, 3, 4], dtype=np.int64), 40)
+
+        msg = "Constructing PeriodIndex from fields is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            pindex = PeriodIndex(year=years, quarter=quarters)
+
+        tm.assert_index_equal(pindex.year, Index(years))
+        tm.assert_index_equal(pindex.quarter, Index(quarters))
+
+        alt = PeriodIndex.from_fields(year=years, quarter=quarters)
+        tm.assert_index_equal(alt, pindex)
+
+    def test_constructor_invalid_quarters(self):
+        depr_msg = "Constructing PeriodIndex from fields is deprecated"
+        msg = "Quarter must be 1 <= q <= 4"
+        with pytest.raises(ValueError, match=msg):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+                PeriodIndex(
+                    year=range(2000, 2004), quarter=list(range(4)), freq="Q-DEC"
+                )
+
+    def test_period_range_fractional_period(self):
+        msg = "Non-integer 'periods' in pd.date_range, pd.timedelta_range"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = period_range("2007-01", periods=10.5, freq="M")
+        exp = period_range("2007-01", periods=10, freq="M")
+        tm.assert_index_equal(result, exp)
+
+    def test_constructor_with_without_freq(self):
+        # GH53687
+        start = Period("2002-01-01 00:00", freq="30min")
+        exp = period_range(start=start, periods=5, freq=start.freq)
+        result = period_range(start=start, periods=5)
+        tm.assert_index_equal(exp, result)
+
+    def test_constructor_fromarraylike(self):
+        idx = period_range("2007-01", periods=20, freq="M")
+
+        # values is an array of Period, thus can retrieve freq
+        tm.assert_index_equal(PeriodIndex(idx.values), idx)
+        tm.assert_index_equal(PeriodIndex(list(idx.values)), idx)
+
+        msg = "freq not specified and cannot be inferred"
+        with pytest.raises(ValueError, match=msg):
+            PeriodIndex(idx.asi8)
+        with pytest.raises(ValueError, match=msg):
+            PeriodIndex(list(idx.asi8))
+
+        msg = "'Period' object is not iterable"
+        with pytest.raises(TypeError, match=msg):
+            PeriodIndex(data=Period("2007", freq="Y"))
+
+        result = PeriodIndex(iter(idx))
+        tm.assert_index_equal(result, idx)
+
+        result = PeriodIndex(idx)
+        tm.assert_index_equal(result, idx)
+
+        result = PeriodIndex(idx, freq="M")
+        tm.assert_index_equal(result, idx)
+
+        result = PeriodIndex(idx, freq=offsets.MonthEnd())
+        tm.assert_index_equal(result, idx)
+        assert result.freq == "ME"
+
+        result = PeriodIndex(idx, freq="2M")
+        tm.assert_index_equal(result, idx.asfreq("2M"))
+        assert result.freq == "2ME"
+
+        result = PeriodIndex(idx, freq=offsets.MonthEnd(2))
+        tm.assert_index_equal(result, idx.asfreq("2M"))
+        assert result.freq == "2ME"
+
+        result = PeriodIndex(idx, freq="D")
+        exp = idx.asfreq("D", "e")
+        tm.assert_index_equal(result, exp)
+
+    def test_constructor_datetime64arr(self):
+        vals = np.arange(100000, 100000 + 10000, 100, dtype=np.int64)
+        vals = vals.view(np.dtype("M8[us]"))
+
+        pi = PeriodIndex(vals, freq="D")
+
+        expected = PeriodIndex(vals.astype("M8[ns]"), freq="D")
+        tm.assert_index_equal(pi, expected)
+
+    @pytest.mark.parametrize("box", [None, "series", "index"])
+    def test_constructor_datetime64arr_ok(self, box):
+        # https://github.com/pandas-dev/pandas/issues/23438
+        data = date_range("2017", periods=4, freq="ME")
+        if box is None:
+            data = data._values
+        elif box == "series":
+            data = Series(data)
+
+        result = PeriodIndex(data, freq="D")
+        expected = PeriodIndex(
+            ["2017-01-31", "2017-02-28", "2017-03-31", "2017-04-30"], freq="D"
+        )
+        tm.assert_index_equal(result, expected)
+
+    def test_constructor_dtype(self):
+        # passing a dtype with a tz should localize
+        idx = PeriodIndex(["2013-01", "2013-03"], dtype="period[M]")
+        exp = PeriodIndex(["2013-01", "2013-03"], freq="M")
+        tm.assert_index_equal(idx, exp)
+        assert idx.dtype == "period[M]"
+
+        idx = PeriodIndex(["2013-01-05", "2013-03-05"], dtype="period[3D]")
+        exp = PeriodIndex(["2013-01-05", "2013-03-05"], freq="3D")
+        tm.assert_index_equal(idx, exp)
+        assert idx.dtype == "period[3D]"
+
+        # if we already have a freq and its not the same, then asfreq
+        # (not changed)
+        idx = PeriodIndex(["2013-01-01", "2013-01-02"], freq="D")
+
+        res = PeriodIndex(idx, dtype="period[M]")
+        exp = PeriodIndex(["2013-01", "2013-01"], freq="M")
+        tm.assert_index_equal(res, exp)
+        assert res.dtype == "period[M]"
+
+        res = PeriodIndex(idx, freq="M")
+        tm.assert_index_equal(res, exp)
+        assert res.dtype == "period[M]"
+
+        msg = "specified freq and dtype are different"
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            PeriodIndex(["2011-01"], freq="M", dtype="period[D]")
+
+    def test_constructor_empty(self):
+        idx = PeriodIndex([], freq="M")
+        assert isinstance(idx, PeriodIndex)
+        assert len(idx) == 0
+        assert idx.freq == "ME"
+
+        with pytest.raises(ValueError, match="freq not specified"):
+            PeriodIndex([])
+
+    def test_constructor_pi_nat(self):
+        idx = PeriodIndex(
+            [Period("2011-01", freq="M"), NaT, Period("2011-01", freq="M")]
+        )
+        exp = PeriodIndex(["2011-01", "NaT", "2011-01"], freq="M")
+        tm.assert_index_equal(idx, exp)
+
+        idx = PeriodIndex(
+            np.array([Period("2011-01", freq="M"), NaT, Period("2011-01", freq="M")])
+        )
+        tm.assert_index_equal(idx, exp)
+
+        idx = PeriodIndex(
+            [NaT, NaT, Period("2011-01", freq="M"), Period("2011-01", freq="M")]
+        )
+        exp = PeriodIndex(["NaT", "NaT", "2011-01", "2011-01"], freq="M")
+        tm.assert_index_equal(idx, exp)
+
+        idx = PeriodIndex(
+            np.array(
+                [NaT, NaT, Period("2011-01", freq="M"), Period("2011-01", freq="M")]
+            )
+        )
+        tm.assert_index_equal(idx, exp)
+
+        idx = PeriodIndex([NaT, NaT, "2011-01", "2011-01"], freq="M")
+        tm.assert_index_equal(idx, exp)
+
+        with pytest.raises(ValueError, match="freq not specified"):
+            PeriodIndex([NaT, NaT])
+
+        with pytest.raises(ValueError, match="freq not specified"):
+            PeriodIndex(np.array([NaT, NaT]))
+
+        with pytest.raises(ValueError, match="freq not specified"):
+            PeriodIndex(["NaT", "NaT"])
+
+        with pytest.raises(ValueError, match="freq not specified"):
+            PeriodIndex(np.array(["NaT", "NaT"]))
+
+    def test_constructor_incompat_freq(self):
+        msg = "Input has different freq=D from PeriodIndex\\(freq=M\\)"
+
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            PeriodIndex([Period("2011-01", freq="M"), NaT, Period("2011-01", freq="D")])
+
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            PeriodIndex(
+                np.array(
+                    [Period("2011-01", freq="M"), NaT, Period("2011-01", freq="D")]
+                )
+            )
+
+        # first element is NaT
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            PeriodIndex([NaT, Period("2011-01", freq="M"), Period("2011-01", freq="D")])
+
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            PeriodIndex(
+                np.array(
+                    [NaT, Period("2011-01", freq="M"), Period("2011-01", freq="D")]
+                )
+            )
+
+    def test_constructor_mixed(self):
+        idx = PeriodIndex(["2011-01", NaT, Period("2011-01", freq="M")])
+        exp = PeriodIndex(["2011-01", "NaT", "2011-01"], freq="M")
+        tm.assert_index_equal(idx, exp)
+
+        idx = PeriodIndex(["NaT", NaT, Period("2011-01", freq="M")])
+        exp = PeriodIndex(["NaT", "NaT", "2011-01"], freq="M")
+        tm.assert_index_equal(idx, exp)
+
+        idx = PeriodIndex([Period("2011-01-01", freq="D"), NaT, "2012-01-01"])
+        exp = PeriodIndex(["2011-01-01", "NaT", "2012-01-01"], freq="D")
+        tm.assert_index_equal(idx, exp)
+
+    @pytest.mark.parametrize("floats", [[1.1, 2.1], np.array([1.1, 2.1])])
+    def test_constructor_floats(self, floats):
+        msg = "PeriodIndex does not allow floating point in construction"
+        with pytest.raises(TypeError, match=msg):
+            PeriodIndex(floats)
+
+    def test_constructor_year_and_quarter(self):
+        year = Series([2001, 2002, 2003])
+        quarter = year - 2000
+        msg = "Constructing PeriodIndex from fields is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            idx = PeriodIndex(year=year, quarter=quarter)
+        strs = [f"{t[0]:d}Q{t[1]:d}" for t in zip(quarter, year)]
+        lops = list(map(Period, strs))
+        p = PeriodIndex(lops)
+        tm.assert_index_equal(p, idx)
+
+    def test_constructor_freq_mult(self):
+        # GH #7811
+        pidx = period_range(start="2014-01", freq="2M", periods=4)
+        expected = PeriodIndex(["2014-01", "2014-03", "2014-05", "2014-07"], freq="2M")
+        tm.assert_index_equal(pidx, expected)
+
+        pidx = period_range(start="2014-01-02", end="2014-01-15", freq="3D")
+        expected = PeriodIndex(
+            ["2014-01-02", "2014-01-05", "2014-01-08", "2014-01-11", "2014-01-14"],
+            freq="3D",
+        )
+        tm.assert_index_equal(pidx, expected)
+
+        pidx = period_range(end="2014-01-01 17:00", freq="4h", periods=3)
+        expected = PeriodIndex(
+            ["2014-01-01 09:00", "2014-01-01 13:00", "2014-01-01 17:00"], freq="4h"
+        )
+        tm.assert_index_equal(pidx, expected)
+
+        msg = "Frequency must be positive, because it represents span: -1M"
+        with pytest.raises(ValueError, match=msg):
+            PeriodIndex(["2011-01"], freq="-1M")
+
+        msg = "Frequency must be positive, because it represents span: 0M"
+        with pytest.raises(ValueError, match=msg):
+            PeriodIndex(["2011-01"], freq="0M")
+
+        msg = "Frequency must be positive, because it represents span: 0M"
+        with pytest.raises(ValueError, match=msg):
+            period_range("2011-01", periods=3, freq="0M")
+
+    @pytest.mark.parametrize(
+        "freq_offset, freq_period",
+        [
+            ("YE", "Y"),
+            ("ME", "M"),
+            ("D", "D"),
+            ("min", "min"),
+            ("s", "s"),
+        ],
+    )
+    @pytest.mark.parametrize("mult", [1, 2, 3, 4, 5])
+    def test_constructor_freq_mult_dti_compat(self, mult, freq_offset, freq_period):
+        freqstr_offset = str(mult) + freq_offset
+        freqstr_period = str(mult) + freq_period
+        pidx = period_range(start="2014-04-01", freq=freqstr_period, periods=10)
+        expected = date_range(
+            start="2014-04-01", freq=freqstr_offset, periods=10
+        ).to_period(freqstr_period)
+        tm.assert_index_equal(pidx, expected)
+
+    @pytest.mark.parametrize("mult", [1, 2, 3, 4, 5])
+    def test_constructor_freq_mult_dti_compat_month(self, mult):
+        pidx = period_range(start="2014-04-01", freq=f"{mult}M", periods=10)
+        expected = date_range(
+            start="2014-04-01", freq=f"{mult}ME", periods=10
+        ).to_period(f"{mult}M")
+        tm.assert_index_equal(pidx, expected)
+
+    def test_constructor_freq_combined(self):
+        for freq in ["1D1h", "1h1D"]:
+            pidx = PeriodIndex(["2016-01-01", "2016-01-02"], freq=freq)
+            expected = PeriodIndex(["2016-01-01 00:00", "2016-01-02 00:00"], freq="25h")
+        for freq in ["1D1h", "1h1D"]:
+            pidx = period_range(start="2016-01-01", periods=2, freq=freq)
+            expected = PeriodIndex(["2016-01-01 00:00", "2016-01-02 01:00"], freq="25h")
+            tm.assert_index_equal(pidx, expected)
+
+    def test_period_range_length(self):
+        pi = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
+        assert len(pi) == 9
+
+        pi = period_range(freq="Q", start="1/1/2001", end="12/1/2009")
+        assert len(pi) == 4 * 9
+
+        pi = period_range(freq="M", start="1/1/2001", end="12/1/2009")
+        assert len(pi) == 12 * 9
+
+        pi = period_range(freq="D", start="1/1/2001", end="12/31/2009")
+        assert len(pi) == 365 * 9 + 2
+
+        msg = "Period with BDay freq is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            pi = period_range(freq="B", start="1/1/2001", end="12/31/2009")
+        assert len(pi) == 261 * 9
+
+        pi = period_range(freq="h", start="1/1/2001", end="12/31/2001 23:00")
+        assert len(pi) == 365 * 24
+
+        pi = period_range(freq="Min", start="1/1/2001", end="1/1/2001 23:59")
+        assert len(pi) == 24 * 60
+
+        pi = period_range(freq="s", start="1/1/2001", end="1/1/2001 23:59:59")
+        assert len(pi) == 24 * 60 * 60
+
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            start = Period("02-Apr-2005", "B")
+            i1 = period_range(start=start, periods=20)
+        assert len(i1) == 20
+        assert i1.freq == start.freq
+        assert i1[0] == start
+
+        end_intv = Period("2006-12-31", "W")
+        i1 = period_range(end=end_intv, periods=10)
+        assert len(i1) == 10
+        assert i1.freq == end_intv.freq
+        assert i1[-1] == end_intv
+
+        msg = "'w' is deprecated and will be removed in a future version."
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            end_intv = Period("2006-12-31", "1w")
+        i2 = period_range(end=end_intv, periods=10)
+        assert len(i1) == len(i2)
+        assert (i1 == i2).all()
+        assert i1.freq == i2.freq
+
+    def test_infer_freq_from_first_element(self):
+        msg = "Period with BDay freq is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            start = Period("02-Apr-2005", "B")
+            end_intv = Period("2005-05-01", "B")
+            period_range(start=start, end=end_intv)
+
+            # infer freq from first element
+            i2 = PeriodIndex([end_intv, Period("2005-05-05", "B")])
+        assert len(i2) == 2
+        assert i2[0] == end_intv
+
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            i2 = PeriodIndex(np.array([end_intv, Period("2005-05-05", "B")]))
+        assert len(i2) == 2
+        assert i2[0] == end_intv
+
+    def test_mixed_freq_raises(self):
+        # Mixed freq should fail
+        msg = "Period with BDay freq is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            end_intv = Period("2005-05-01", "B")
+
+        msg = "'w' is deprecated and will be removed in a future version."
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            vals = [end_intv, Period("2006-12-31", "w")]
+        msg = r"Input has different freq=W-SUN from PeriodIndex\(freq=B\)"
+        depr_msg = r"PeriodDtype\[B\] is deprecated"
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+                PeriodIndex(vals)
+        vals = np.array(vals)
+        with pytest.raises(IncompatibleFrequency, match=msg):
+            with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+                PeriodIndex(vals)
+
+    @pytest.mark.parametrize(
+        "freq", ["M", "Q", "Y", "D", "B", "min", "s", "ms", "us", "ns", "h"]
+    )
+    @pytest.mark.filterwarnings(
+        r"ignore:Period with BDay freq is deprecated:FutureWarning"
+    )
+    @pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
+    def test_recreate_from_data(self, freq):
+        org = period_range(start="2001/04/01", freq=freq, periods=1)
+        idx = PeriodIndex(org.values, freq=freq)
+        tm.assert_index_equal(idx, org)
+
+    def test_map_with_string_constructor(self):
+        raw = [2005, 2007, 2009]
+        index = PeriodIndex(raw, freq="Y")
+
+        expected = Index([str(num) for num in raw])
+        res = index.map(str)
+
+        # should return an Index
+        assert isinstance(res, Index)
+
+        # preserve element types
+        assert all(isinstance(resi, str) for resi in res)
+
+        # lastly, values should compare equal
+        tm.assert_index_equal(res, expected)
+
+
+class TestSimpleNew:
+    def test_constructor_simple_new(self):
+        idx = period_range("2007-01", name="p", periods=2, freq="M")
+
+        with pytest.raises(AssertionError, match="<class .*PeriodIndex'>"):
+            idx._simple_new(idx, name="p")
+
+        result = idx._simple_new(idx._data, name="p")
+        tm.assert_index_equal(result, idx)
+
+        msg = "Should be numpy array of type i8"
+        with pytest.raises(AssertionError, match=msg):
+            # Need ndarray, not int64 Index
+            type(idx._data)._simple_new(Index(idx.asi8), dtype=idx.dtype)
+
+        arr = type(idx._data)._simple_new(idx.asi8, dtype=idx.dtype)
+        result = idx._simple_new(arr, name="p")
+        tm.assert_index_equal(result, idx)
+
+    def test_constructor_simple_new_empty(self):
+        # GH13079
+        idx = PeriodIndex([], freq="M", name="p")
+        with pytest.raises(AssertionError, match="<class .*PeriodIndex'>"):
+            idx._simple_new(idx, name="p")
+
+        result = idx._simple_new(idx._data, name="p")
+        tm.assert_index_equal(result, idx)
+
+    @pytest.mark.parametrize("floats", [[1.1, 2.1], np.array([1.1, 2.1])])
+    def test_period_index_simple_new_disallows_floats(self, floats):
+        with pytest.raises(AssertionError, match="<class "):
+            PeriodIndex._simple_new(floats)
+
+
+class TestShallowCopy:
+    def test_shallow_copy_empty(self):
+        # GH#13067
+        idx = PeriodIndex([], freq="M")
+        result = idx._view()
+        expected = idx
+
+        tm.assert_index_equal(result, expected)
+
+    def test_shallow_copy_disallow_i8(self):
+        # GH#24391
+        pi = period_range("2018-01-01", periods=3, freq="2D")
+        with pytest.raises(AssertionError, match="ndarray"):
+            pi._shallow_copy(pi.asi8)
+
+    def test_shallow_copy_requires_disallow_period_index(self):
+        pi = period_range("2018-01-01", periods=3, freq="2D")
+        with pytest.raises(AssertionError, match="PeriodIndex"):
+            pi._shallow_copy(pi)
+
+
+class TestSeriesPeriod:
+    def test_constructor_cant_cast_period(self):
+        msg = "Cannot cast PeriodIndex to dtype float64"
+        with pytest.raises(TypeError, match=msg):
+            Series(period_range("2000-01-01", periods=10, freq="D"), dtype=float)
+
+    def test_constructor_cast_object(self):
+        pi = period_range("1/1/2000", periods=10)
+        ser = Series(pi, dtype=PeriodDtype("D"))
+        exp = Series(pi)
+        tm.assert_series_equal(ser, exp)

venv/lib/python3.10/site-packages/pandas/tests/indexes/period/test_formats.py

@@ -0,0 +1,350 @@
+from contextlib import nullcontext
+from datetime import (
+    datetime,
+    time,
+)
+import locale
+
+import numpy as np
+import pytest
+
+import pandas as pd
+from pandas import (
+    PeriodIndex,
+    Series,
+)
+import pandas._testing as tm
+
+
+def get_local_am_pm():
+    """Return the AM and PM strings returned by strftime in current locale."""
+    am_local = time(1).strftime("%p")
+    pm_local = time(13).strftime("%p")
+    return am_local, pm_local
+
+
+def test_get_values_for_csv():
+    index = PeriodIndex(["2017-01-01", "2017-01-02", "2017-01-03"], freq="D")
+
+    # First, with no arguments.
+    expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object)
+
+    result = index._get_values_for_csv()
+    tm.assert_numpy_array_equal(result, expected)
+
+    # No NaN values, so na_rep has no effect
+    result = index._get_values_for_csv(na_rep="pandas")
+    tm.assert_numpy_array_equal(result, expected)
+
+    # Make sure date formatting works
+    expected = np.array(["01-2017-01", "01-2017-02", "01-2017-03"], dtype=object)
+
+    result = index._get_values_for_csv(date_format="%m-%Y-%d")
+    tm.assert_numpy_array_equal(result, expected)
+
+    # NULL object handling should work
+    index = PeriodIndex(["2017-01-01", pd.NaT, "2017-01-03"], freq="D")
+    expected = np.array(["2017-01-01", "NaT", "2017-01-03"], dtype=object)
+
+    result = index._get_values_for_csv(na_rep="NaT")
+    tm.assert_numpy_array_equal(result, expected)
+
+    expected = np.array(["2017-01-01", "pandas", "2017-01-03"], dtype=object)
+
+    result = index._get_values_for_csv(na_rep="pandas")
+    tm.assert_numpy_array_equal(result, expected)
+
+
+class TestPeriodIndexRendering:
+    def test_format_empty(self):
+        # GH#35712
+        empty_idx = PeriodIndex([], freq="Y")
+        msg = r"PeriodIndex\.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert empty_idx.format() == []
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert empty_idx.format(name=True) == [""]
+
+    @pytest.mark.parametrize("method", ["__repr__", "__str__"])
+    def test_representation(self, method):
+        # GH#7601
+        idx1 = PeriodIndex([], freq="D")
+        idx2 = PeriodIndex(["2011-01-01"], freq="D")
+        idx3 = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D")
+        idx4 = PeriodIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
+        idx5 = PeriodIndex(["2011", "2012", "2013"], freq="Y")
+        idx6 = PeriodIndex(["2011-01-01 09:00", "2012-02-01 10:00", "NaT"], freq="h")
+        idx7 = pd.period_range("2013Q1", periods=1, freq="Q")
+        idx8 = pd.period_range("2013Q1", periods=2, freq="Q")
+        idx9 = pd.period_range("2013Q1", periods=3, freq="Q")
+        idx10 = PeriodIndex(["2011-01-01", "2011-02-01"], freq="3D")
+
+        exp1 = "PeriodIndex([], dtype='period[D]')"
+
+        exp2 = "PeriodIndex(['2011-01-01'], dtype='period[D]')"
+
+        exp3 = "PeriodIndex(['2011-01-01', '2011-01-02'], dtype='period[D]')"
+
+        exp4 = (
+            "PeriodIndex(['2011-01-01', '2011-01-02', '2011-01-03'], "
+            "dtype='period[D]')"
+        )
+
+        exp5 = "PeriodIndex(['2011', '2012', '2013'], dtype='period[Y-DEC]')"
+
+        exp6 = (
+            "PeriodIndex(['2011-01-01 09:00', '2012-02-01 10:00', 'NaT'], "
+            "dtype='period[h]')"
+        )
+
+        exp7 = "PeriodIndex(['2013Q1'], dtype='period[Q-DEC]')"
+
+        exp8 = "PeriodIndex(['2013Q1', '2013Q2'], dtype='period[Q-DEC]')"
+
+        exp9 = "PeriodIndex(['2013Q1', '2013Q2', '2013Q3'], dtype='period[Q-DEC]')"
+
+        exp10 = "PeriodIndex(['2011-01-01', '2011-02-01'], dtype='period[3D]')"
+
+        for idx, expected in zip(
+            [idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9, idx10],
+            [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9, exp10],
+        ):
+            result = getattr(idx, method)()
+            assert result == expected
+
+    # TODO: These are Series.__repr__ tests
+    def test_representation_to_series(self):
+        # GH#10971
+        idx1 = PeriodIndex([], freq="D")
+        idx2 = PeriodIndex(["2011-01-01"], freq="D")
+        idx3 = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D")
+        idx4 = PeriodIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
+        idx5 = PeriodIndex(["2011", "2012", "2013"], freq="Y")
+        idx6 = PeriodIndex(["2011-01-01 09:00", "2012-02-01 10:00", "NaT"], freq="h")
+
+        idx7 = pd.period_range("2013Q1", periods=1, freq="Q")
+        idx8 = pd.period_range("2013Q1", periods=2, freq="Q")
+        idx9 = pd.period_range("2013Q1", periods=3, freq="Q")
+
+        exp1 = """Series([], dtype: period[D])"""
+
+        exp2 = """0    2011-01-01
+dtype: period[D]"""
+
+        exp3 = """0    2011-01-01
+1    2011-01-02
+dtype: period[D]"""
+
+        exp4 = """0    2011-01-01
+1    2011-01-02
+2    2011-01-03
+dtype: period[D]"""
+
+        exp5 = """0    2011
+1    2012
+2    2013
+dtype: period[Y-DEC]"""
+
+        exp6 = """0    2011-01-01 09:00
+1    2012-02-01 10:00
+2                 NaT
+dtype: period[h]"""
+
+        exp7 = """0    2013Q1
+dtype: period[Q-DEC]"""
+
+        exp8 = """0    2013Q1
+1    2013Q2
+dtype: period[Q-DEC]"""
+
+        exp9 = """0    2013Q1
+1    2013Q2
+2    2013Q3
+dtype: period[Q-DEC]"""
+
+        for idx, expected in zip(
+            [idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9],
+            [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9],
+        ):
+            result = repr(Series(idx))
+            assert result == expected
+
+    def test_summary(self):
+        # GH#9116
+        idx1 = PeriodIndex([], freq="D")
+        idx2 = PeriodIndex(["2011-01-01"], freq="D")
+        idx3 = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D")
+        idx4 = PeriodIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")
+        idx5 = PeriodIndex(["2011", "2012", "2013"], freq="Y")
+        idx6 = PeriodIndex(["2011-01-01 09:00", "2012-02-01 10:00", "NaT"], freq="h")
+
+        idx7 = pd.period_range("2013Q1", periods=1, freq="Q")
+        idx8 = pd.period_range("2013Q1", periods=2, freq="Q")
+        idx9 = pd.period_range("2013Q1", periods=3, freq="Q")
+
+        exp1 = """PeriodIndex: 0 entries
+Freq: D"""
+
+        exp2 = """PeriodIndex: 1 entries, 2011-01-01 to 2011-01-01
+Freq: D"""
+
+        exp3 = """PeriodIndex: 2 entries, 2011-01-01 to 2011-01-02
+Freq: D"""
+
+        exp4 = """PeriodIndex: 3 entries, 2011-01-01 to 2011-01-03
+Freq: D"""
+
+        exp5 = """PeriodIndex: 3 entries, 2011 to 2013
+Freq: Y-DEC"""
+
+        exp6 = """PeriodIndex: 3 entries, 2011-01-01 09:00 to NaT
+Freq: h"""
+
+        exp7 = """PeriodIndex: 1 entries, 2013Q1 to 2013Q1
+Freq: Q-DEC"""
+
+        exp8 = """PeriodIndex: 2 entries, 2013Q1 to 2013Q2
+Freq: Q-DEC"""
+
+        exp9 = """PeriodIndex: 3 entries, 2013Q1 to 2013Q3
+Freq: Q-DEC"""
+
+        for idx, expected in zip(
+            [idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9],
+            [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9],
+        ):
+            result = idx._summary()
+            assert result == expected
+
+
+class TestPeriodIndexFormat:
+    def test_period_format_and_strftime_default(self):
+        per = PeriodIndex([datetime(2003, 1, 1, 12), None], freq="h")
+
+        # Default formatting
+        msg = "PeriodIndex.format is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = per.format()
+        assert formatted[0] == "2003-01-01 12:00"  # default: minutes not shown
+        assert formatted[1] == "NaT"
+        # format is equivalent to strftime(None)...
+        assert formatted[0] == per.strftime(None)[0]
+        assert per.strftime(None)[1] is np.nan  # ...except for NaTs
+
+        # Same test with nanoseconds freq
+        per = pd.period_range("2003-01-01 12:01:01.123456789", periods=2, freq="ns")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = per.format()
+        assert (formatted == per.strftime(None)).all()
+        assert formatted[0] == "2003-01-01 12:01:01.123456789"
+        assert formatted[1] == "2003-01-01 12:01:01.123456790"
+
+    def test_period_custom(self):
+        # GH#46252 custom formatting directives %l (ms) and %u (us)
+        msg = "PeriodIndex.format is deprecated"
+
+        # 3 digits
+        per = pd.period_range("2003-01-01 12:01:01.123", periods=2, freq="ms")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = per.format(date_format="%y %I:%M:%S (ms=%l us=%u ns=%n)")
+        assert formatted[0] == "03 12:01:01 (ms=123 us=123000 ns=123000000)"
+        assert formatted[1] == "03 12:01:01 (ms=124 us=124000 ns=124000000)"
+
+        # 6 digits
+        per = pd.period_range("2003-01-01 12:01:01.123456", periods=2, freq="us")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = per.format(date_format="%y %I:%M:%S (ms=%l us=%u ns=%n)")
+        assert formatted[0] == "03 12:01:01 (ms=123 us=123456 ns=123456000)"
+        assert formatted[1] == "03 12:01:01 (ms=123 us=123457 ns=123457000)"
+
+        # 9 digits
+        per = pd.period_range("2003-01-01 12:01:01.123456789", periods=2, freq="ns")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            formatted = per.format(date_format="%y %I:%M:%S (ms=%l us=%u ns=%n)")
+        assert formatted[0] == "03 12:01:01 (ms=123 us=123456 ns=123456789)"
+        assert formatted[1] == "03 12:01:01 (ms=123 us=123456 ns=123456790)"
+
+    def test_period_tz(self):
+        # Formatting periods created from a datetime with timezone.
+        msg = r"PeriodIndex\.format is deprecated"
+        # This timestamp is in 2013 in Europe/Paris but is 2012 in UTC
+        dt = pd.to_datetime(["2013-01-01 00:00:00+01:00"], utc=True)
+
+        # Converting to a period looses the timezone information
+        # Since tz is currently set as utc, we'll see 2012
+        with tm.assert_produces_warning(UserWarning, match="will drop timezone"):
+            per = dt.to_period(freq="h")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert per.format()[0] == "2012-12-31 23:00"
+
+        # If tz is currently set as paris before conversion, we'll see 2013
+        dt = dt.tz_convert("Europe/Paris")
+        with tm.assert_produces_warning(UserWarning, match="will drop timezone"):
+            per = dt.to_period(freq="h")
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert per.format()[0] == "2013-01-01 00:00"
+
+    @pytest.mark.parametrize(
+        "locale_str",
+        [
+            pytest.param(None, id=str(locale.getlocale())),
+            "it_IT.utf8",
+            "it_IT",  # Note: encoding will be 'ISO8859-1'
+            "zh_CN.utf8",
+            "zh_CN",  # Note: encoding will be 'gb2312'
+        ],
+    )
+    def test_period_non_ascii_fmt(self, locale_str):
+        # GH#46468 non-ascii char in input format string leads to wrong output
+
+        # Skip if locale cannot be set
+        if locale_str is not None and not tm.can_set_locale(locale_str, locale.LC_ALL):
+            pytest.skip(f"Skipping as locale '{locale_str}' cannot be set on host.")
+
+        # Change locale temporarily for this test.
+        with tm.set_locale(locale_str, locale.LC_ALL) if locale_str else nullcontext():
+            # Scalar
+            per = pd.Period("2018-03-11 13:00", freq="h")
+            assert per.strftime("%y é") == "18 é"
+
+            # Index
+            per = pd.period_range("2003-01-01 01:00:00", periods=2, freq="12h")
+            msg = "PeriodIndex.format is deprecated"
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                formatted = per.format(date_format="%y é")
+            assert formatted[0] == "03 é"
+            assert formatted[1] == "03 é"
+
+    @pytest.mark.parametrize(
+        "locale_str",
+        [
+            pytest.param(None, id=str(locale.getlocale())),
+            "it_IT.utf8",
+            "it_IT",  # Note: encoding will be 'ISO8859-1'
+            "zh_CN.utf8",
+            "zh_CN",  # Note: encoding will be 'gb2312'
+        ],
+    )
+    def test_period_custom_locale_directive(self, locale_str):
+        # GH#46319 locale-specific directive leads to non-utf8 c strftime char* result
+
+        # Skip if locale cannot be set
+        if locale_str is not None and not tm.can_set_locale(locale_str, locale.LC_ALL):
+            pytest.skip(f"Skipping as locale '{locale_str}' cannot be set on host.")
+
+        # Change locale temporarily for this test.
+        with tm.set_locale(locale_str, locale.LC_ALL) if locale_str else nullcontext():
+            # Get locale-specific reference
+            am_local, pm_local = get_local_am_pm()
+
+            # Scalar
+            per = pd.Period("2018-03-11 13:00", freq="h")
+            assert per.strftime("%p") == pm_local
+
+            # Index
+            per = pd.period_range("2003-01-01 01:00:00", periods=2, freq="12h")
+            msg = "PeriodIndex.format is deprecated"
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                formatted = per.format(date_format="%y %I:%M:%S%p")
+            assert formatted[0] == f"03 01:00:00{am_local}"
+            assert formatted[1] == f"03 01:00:00{pm_local}"