DEPR: remove Int64Index, UInt64Index, Float64Index from tests.indexes…

….numeric (pandas-dev#49682)

* DEPR: remove Int64Index, UInt64Index, Float64Index from tests.indexes.numeric

* add back pylint

* RangeIndex in test_indexing.py

Co-authored-by: Terji Petersen <terjipetersen@Terjis-Air.fritz.box>

pandas/tests/indexes/common.py

@@ -818,6 +818,19 @@ def test_can_hold_identifiers(self, simple_index):
         key = idx[0]
         assert idx._can_hold_identifiers_and_holds_name(key) is False
 
+    def test_view(self, dtype):
+        index_cls = self._index_cls
+
+        idx = index_cls([], dtype=dtype, name="Foo")
+        idx_view = idx.view()
+        assert idx_view.name == "Foo"
+
+        idx_view = idx.view(dtype)
+        tm.assert_index_equal(idx, index_cls(idx_view, name="Foo"), exact=True)
+
+        idx_view = idx.view(index_cls)
+        tm.assert_index_equal(idx, index_cls(idx_view, name="Foo"), exact=True)
+
     def test_format(self, simple_index):
         # GH35439
         idx = simple_index

pandas/tests/indexes/numeric/test_astype.py

@@ -7,72 +7,67 @@
 
 from pandas import Index
 import pandas._testing as tm
-from pandas.core.indexes.api import (
-    Float64Index,
-    Int64Index,
-    UInt64Index,
-)
 
 
 class TestAstype:
     def test_astype_float64_to_uint64(self):
         # GH#45309 used to incorrectly return Int64Index
-        idx = Float64Index([0.0, 5.0, 10.0, 15.0, 20.0])
+        idx = Index([0.0, 5.0, 10.0, 15.0, 20.0], dtype=np.float64)
         result = idx.astype("u8")
-        expected = UInt64Index([0, 5, 10, 15, 20])
-        tm.assert_index_equal(result, expected)
+        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 = Float64Index([0.0, 2.5, 5.0, 7.5, 10.0])
+        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 not isinstance(result, Float64Index)
+        assert isinstance(result, Index) and result.dtype == object
 
     def test_astype_float64_mixed_to_object(self):
         # mixed int-float
-        idx = Float64Index([1.5, 2, 3, 4, 5])
+        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 not isinstance(result, Float64Index)
+        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 = Float64Index([0, 1, 2])
+        idx = Index([0, 1, 2], dtype=np.float64)
         result = idx.astype(dtype)
-        expected = Int64Index([0, 1, 2])
-        tm.assert_index_equal(result, expected)
+        expected = Index([0, 1, 2], dtype=np.int64)
+        tm.assert_index_equal(result, expected, exact=True)
 
-        idx = Float64Index([0, 1.1, 2])
+        idx = Index([0, 1.1, 2], dtype=np.float64)
         result = idx.astype(dtype)
-        expected = Int64Index([0, 1, 2])
-        tm.assert_index_equal(result, expected)
+        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 = Float64Index([0, 1, 2])
+        idx = Index([0, 1, 2], dtype=np.float64)
         result = idx.astype(dtype)
         expected = idx
-        tm.assert_index_equal(result, expected)
+        tm.assert_index_equal(result, expected, exact=True)
 
-        idx = Float64Index([0, 1.1, 2])
+        idx = Index([0, 1.1, 2], dtype=np.float64)
         result = idx.astype(dtype)
         expected = Index(idx.values.astype(dtype))
-        tm.assert_index_equal(result, expected)
+        tm.assert_index_equal(result, expected, exact=True)
 
     @pytest.mark.parametrize("dtype", ["M8[ns]", "m8[ns]"])
     def test_cannot_cast_to_datetimelike(self, dtype):
-        idx = Float64Index([0, 1.1, 2])
+        idx = Index([0, 1.1, 2], dtype=np.float64)
 
         msg = (
             f"Cannot convert Float64Index to dtype {pandas_dtype(dtype)}; "
@@ -85,7 +80,7 @@ def test_cannot_cast_to_datetimelike(self, dtype):
     @pytest.mark.parametrize("non_finite", [np.inf, np.nan])
     def test_cannot_cast_inf_to_int(self, non_finite, dtype):
         # GH#13149
-        idx = Float64Index([1, 2, non_finite])
+        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):
@@ -94,6 +89,6 @@ def test_cannot_cast_inf_to_int(self, non_finite, dtype):
     def test_astype_from_object(self):
         index = Index([1.0, np.nan, 0.2], dtype="object")
         result = index.astype(float)
-        expected = Float64Index([1.0, np.nan, 0.2])
+        expected = Index([1.0, np.nan, 0.2], dtype=np.float64)
         assert result.dtype == expected.dtype
         tm.assert_index_equal(result, expected)

pandas/tests/indexes/numeric/test_indexing.py

@@ -10,18 +10,13 @@
     Timestamp,
 )
 import pandas._testing as tm
-from pandas.core.indexes.api import (
-    Float64Index,
-    Int64Index,
-    UInt64Index,
-)
 
 
 @pytest.fixture
 def index_large():
-    # large values used in UInt64Index tests where no compat needed with Int64/Float64
+    # 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 UInt64Index(large)
+    return Index(large, dtype=np.uint64)
 
 
 class TestGetLoc:
@@ -86,7 +81,7 @@ def test_get_loc_raises_missized_tolerance(self):
 
     @pytest.mark.filterwarnings("ignore:Passing method:FutureWarning")
     def test_get_loc_float64(self):
-        idx = Float64Index([0.0, 1.0, 2.0])
+        idx = Index([0.0, 1.0, 2.0], dtype=np.float64)
         for method in [None, "pad", "backfill", "nearest"]:
             assert idx.get_loc(1, method) == 1
             if method is not None:
@@ -119,27 +114,27 @@ def test_get_loc_float64(self):
             idx.get_loc(1.4, method="nearest", tolerance=np.array([1, 2]))
 
     def test_get_loc_na(self):
-        idx = Float64Index([np.nan, 1, 2])
+        idx = Index([np.nan, 1, 2], dtype=np.float64)
         assert idx.get_loc(1) == 1
         assert idx.get_loc(np.nan) == 0
 
-        idx = Float64Index([np.nan, 1, np.nan])
+        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 = Float64Index([np.nan, 1, np.nan, np.nan])
+        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 = Float64Index([1, 2])
+        idx = Index([1, 2], dtype=np.float64)
         assert idx.get_loc(1) == 0
         with pytest.raises(KeyError, match=r"^3$"):
             idx.get_loc(3)
@@ -285,14 +280,16 @@ def test_get_indexer_nearest_decreasing(self, method, expected):
         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_class", [Int64Index, RangeIndex, Float64Index, UInt64Index]
-    )
+    @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_class):
+    def test_get_indexer_numeric_index_boolean_target(self, method, idx_dtype):
         # GH 16877
 
-        numeric_index = idx_class(RangeIndex(4))
+        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)
@@ -336,7 +333,7 @@ def test_get_indexer_numeric_vs_bool(self):
         tm.assert_numpy_array_equal(res, expected)
 
     def test_get_indexer_float64(self):
-        idx = Float64Index([0.0, 1.0, 2.0])
+        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)
         )
@@ -354,39 +351,39 @@ def test_get_indexer_float64(self):
 
     def test_get_indexer_nan(self):
         # GH#7820
-        result = Float64Index([1, 2, np.nan]).get_indexer([np.nan])
+        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 = Int64Index(range(0, 20, 2))
-        target = Int64Index(np.arange(10))
+        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 = Int64Index(np.arange(10))
+        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 = Int64Index(np.arange(10))
+        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 = UInt64Index(np.arange(10).astype("uint64") * 5 + 2**63)
+        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 = UInt64Index(np.arange(10).astype("uint64") * 5 + 2**63)
+        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 = UInt64Index(np.arange(10).astype("uint64") * 5 + 2**63)
+        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)
@@ -396,9 +393,9 @@ class TestWhere:
     @pytest.mark.parametrize(
         "index",
         [
-            Float64Index(np.arange(5, dtype="float64")),
-            Int64Index(range(0, 20, 2)),
-            UInt64Index(np.arange(5, dtype="uint64")),
+            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):
@@ -407,16 +404,16 @@ def test_where(self, listlike_box, index):
         result = index.where(listlike_box(cond))
 
         cond = [False] + [True] * (len(index) - 1)
-        expected = Float64Index([index._na_value] + index[1:].tolist())
+        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 = UInt64Index([0, 6, 2])
+        idx = Index([0, 6, 2], dtype=np.uint64)
         mask = np.array([False, True, False])
         other = np.array([1], dtype=np.int64)
 
-        expected = UInt64Index([1, 6, 1])
+        expected = Index([1, 6, 1], dtype=np.uint64)
 
         result = idx.where(mask, other)
         tm.assert_index_equal(result, expected)
@@ -437,27 +434,27 @@ def test_where_infers_type_instead_of_trying_to_convert_string_to_float(self):
 
 
 class TestTake:
-    @pytest.mark.parametrize("klass", [Float64Index, Int64Index, UInt64Index])
-    def test_take_preserve_name(self, klass):
-        index = klass([1, 2, 3, 4], name="foo")
+    @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 = Float64Index([1.0, 2.0, 3.0], name="xxx")
+        idx = Index([1.0, 2.0, 3.0], name="xxx", dtype=np.float64)
         result = idx.take(np.array([1, 0, -1]))
-        expected = Float64Index([2.0, 1.0, 3.0], name="xxx")
+        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 = Float64Index([2.0, 1.0, np.nan], name="xxx")
+        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 = Float64Index([2.0, 1.0, 3.0], name="xxx")
+        expected = Index([2.0, 1.0, 3.0], dtype=np.float64, name="xxx")
         tm.assert_index_equal(result, expected)
 
         msg = (
@@ -473,15 +470,15 @@ def test_take_fill_value_float64(self):
         with pytest.raises(IndexError, match=msg):
             idx.take(np.array([1, -5]))
 
-    @pytest.mark.parametrize("klass", [Int64Index, UInt64Index])
-    def test_take_fill_value_ints(self, klass):
+    @pytest.mark.parametrize("dtype", [np.int64, np.uint64])
+    def test_take_fill_value_ints(self, dtype):
         # see gh-12631
-        idx = klass([1, 2, 3], name="xxx")
+        idx = Index([1, 2, 3], dtype=dtype, name="xxx")
         result = idx.take(np.array([1, 0, -1]))
-        expected = klass([2, 1, 3], name="xxx")
+        expected = Index([2, 1, 3], dtype=dtype, name="xxx")
         tm.assert_index_equal(result, expected)
 
-        name = klass.__name__
+        name = type(idx).__name__
         msg = f"Unable to fill values because {name} cannot contain NA"
 
         # fill_value=True
@@ -490,7 +487,7 @@ def test_take_fill_value_ints(self, klass):
 
         # allow_fill=False
         result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
-        expected = klass([2, 1, 3], name="xxx")
+        expected = Index([2, 1, 3], dtype=dtype, name="xxx")
         tm.assert_index_equal(result, expected)
 
         with pytest.raises(ValueError, match=msg):
@@ -504,18 +501,18 @@ def test_take_fill_value_ints(self, klass):
 
 
 class TestContains:
-    @pytest.mark.parametrize("klass", [Float64Index, Int64Index, UInt64Index])
-    def test_contains_none(self, klass):
+    @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 = klass([0, 1, 2, 3, 4])
+        index = Index([0, 1, 2, 3, 4], dtype=dtype)
         assert None not in index
 
     def test_contains_float64_nans(self):
-        index = Float64Index([1.0, 2.0, np.nan])
+        index = Index([1.0, 2.0, np.nan], dtype=np.float64)
         assert np.nan in index
 
     def test_contains_float64_not_nans(self):
-        index = Float64Index([1.0, 2.0, np.nan])
+        index = Index([1.0, 2.0, np.nan], dtype=np.float64)
         assert 1.0 in index