first commit

.venv/Lib/site-packages/pandas/tests/indexes/numeric/test_numeric.py

@@ -0,0 +1,689 @@
+import numpy as np
+import pytest
+
+from pandas._libs.tslibs import Timestamp
+
+import pandas as pd
+from pandas import (
+    Index,
+    Series,
+)
+import pandas._testing as tm
+from pandas.core.indexes.api import (
+    Float64Index,
+    Int64Index,
+    NumericIndex,
+    UInt64Index,
+)
+from pandas.tests.indexes.common import NumericBase
+
+
+class TestFloatNumericIndex(NumericBase):
+    _index_cls = NumericIndex
+
+    @pytest.fixture(params=[np.float64, np.float32])
+    def dtype(self, request):
+        return request.param
+
+    @pytest.fixture(params=["category", "datetime64", "object"])
+    def invalid_dtype(self, request):
+        return request.param
+
+    @pytest.fixture
+    def simple_index(self, dtype):
+        values = np.arange(5, dtype=dtype)
+        return self._index_cls(values)
+
+    @pytest.fixture(
+        params=[
+            [1.5, 2, 3, 4, 5],
+            [0.0, 2.5, 5.0, 7.5, 10.0],
+            [5, 4, 3, 2, 1.5],
+            [10.0, 7.5, 5.0, 2.5, 0.0],
+        ],
+        ids=["mixed", "float", "mixed_dec", "float_dec"],
+    )
+    def index(self, request, dtype):
+        return self._index_cls(request.param, dtype=dtype)
+
+    @pytest.fixture
+    def mixed_index(self, dtype):
+        return self._index_cls([1.5, 2, 3, 4, 5], dtype=dtype)
+
+    @pytest.fixture
+    def float_index(self, dtype):
+        return self._index_cls([0.0, 2.5, 5.0, 7.5, 10.0], dtype=dtype)
+
+    def test_repr_roundtrip(self, index):
+        tm.assert_index_equal(eval(repr(index)), index, exact=True)
+
+    def check_is_index(self, idx):
+        assert isinstance(idx, Index)
+        assert not isinstance(idx, self._index_cls)
+
+    def check_coerce(self, a, b, is_float_index=True):
+        assert a.equals(b)
+        tm.assert_index_equal(a, b, exact=False)
+        if is_float_index:
+            assert isinstance(b, self._index_cls)
+        else:
+            self.check_is_index(b)
+
+    def test_constructor(self, dtype):
+        index_cls = self._index_cls
+
+        # explicit construction
+        index = index_cls([1, 2, 3, 4, 5], dtype=dtype)
+
+        assert isinstance(index, index_cls)
+        assert index.dtype == dtype
+
+        expected = np.array([1, 2, 3, 4, 5], dtype=dtype)
+        tm.assert_numpy_array_equal(index.values, expected)
+
+        index = index_cls(np.array([1, 2, 3, 4, 5]), dtype=dtype)
+        assert isinstance(index, index_cls)
+        assert index.dtype == dtype
+
+        index = index_cls([1.0, 2, 3, 4, 5], dtype=dtype)
+        assert isinstance(index, index_cls)
+        assert index.dtype == dtype
+
+        index = index_cls(np.array([1.0, 2, 3, 4, 5]), dtype=dtype)
+        assert isinstance(index, index_cls)
+        assert index.dtype == dtype
+
+        index = index_cls([1.0, 2, 3, 4, 5], dtype=dtype)
+        assert isinstance(index, index_cls)
+        assert index.dtype == dtype
+
+        index = index_cls(np.array([1.0, 2, 3, 4, 5]), dtype=dtype)
+        assert isinstance(index, index_cls)
+        assert index.dtype == dtype
+
+        # nan handling
+        result = index_cls([np.nan, np.nan], dtype=dtype)
+        assert pd.isna(result.values).all()
+
+        result = index_cls(np.array([np.nan]), dtype=dtype)
+        assert pd.isna(result.values).all()
+
+    def test_constructor_invalid(self):
+        index_cls = self._index_cls
+        cls_name = index_cls.__name__
+
+        # invalid
+        msg = (
+            rf"{cls_name}\(\.\.\.\) must be called with a collection of "
+            r"some kind, 0\.0 was passed"
+        )
+        with pytest.raises(TypeError, match=msg):
+            index_cls(0.0)
+
+        # 2021-02-1 we get ValueError in numpy 1.20, but not on all builds
+        msg = "|".join(
+            [
+                "String dtype not supported, you may need to explicitly cast ",
+                "could not convert string to float: 'a'",
+            ]
+        )
+        with pytest.raises((TypeError, ValueError), match=msg):
+            index_cls(["a", "b", 0.0])
+
+        msg = f"data is not compatible with {index_cls.__name__}"
+        with pytest.raises(ValueError, match=msg):
+            index_cls([Timestamp("20130101")])
+
+    def test_constructor_coerce(self, mixed_index, float_index):
+
+        self.check_coerce(mixed_index, Index([1.5, 2, 3, 4, 5]))
+        self.check_coerce(float_index, Index(np.arange(5) * 2.5))
+
+        with tm.assert_produces_warning(FutureWarning, match="will not infer"):
+            result = Index(np.array(np.arange(5) * 2.5, dtype=object))
+        self.check_coerce(float_index, result.astype("float64"))
+
+    def test_constructor_explicit(self, mixed_index, float_index):
+
+        # these don't auto convert
+        self.check_coerce(
+            float_index, Index((np.arange(5) * 2.5), dtype=object), is_float_index=False
+        )
+        self.check_coerce(
+            mixed_index, Index([1.5, 2, 3, 4, 5], dtype=object), is_float_index=False
+        )
+
+    def test_type_coercion_fail(self, any_int_numpy_dtype):
+        # see gh-15832
+        msg = "Trying to coerce float values to integers"
+        with pytest.raises(ValueError, match=msg):
+            Index([1, 2, 3.5], dtype=any_int_numpy_dtype)
+
+    def test_type_coercion_valid(self, float_numpy_dtype):
+        # There is no Float32Index, so we always
+        # generate Float64Index.
+        idx = Index([1, 2, 3.5], dtype=float_numpy_dtype)
+        tm.assert_index_equal(idx, Index([1, 2, 3.5]), exact=True)
+
+    def test_equals_numeric(self):
+        index_cls = self._index_cls
+
+        idx = index_cls([1.0, 2.0])
+        assert idx.equals(idx)
+        assert idx.identical(idx)
+
+        idx2 = index_cls([1.0, 2.0])
+        assert idx.equals(idx2)
+
+        idx = index_cls([1.0, np.nan])
+        assert idx.equals(idx)
+        assert idx.identical(idx)
+
+        idx2 = index_cls([1.0, np.nan])
+        assert idx.equals(idx2)
+
+    @pytest.mark.parametrize(
+        "other",
+        (
+            Int64Index([1, 2]),
+            Index([1.0, 2.0], dtype=object),
+            Index([1, 2], dtype=object),
+        ),
+    )
+    def test_equals_numeric_other_index_type(self, other):
+        idx = self._index_cls([1.0, 2.0])
+        assert idx.equals(other)
+        assert other.equals(idx)
+
+    @pytest.mark.parametrize(
+        "vals",
+        [
+            pd.date_range("2016-01-01", periods=3),
+            pd.timedelta_range("1 Day", periods=3),
+        ],
+    )
+    def test_lookups_datetimelike_values(self, vals, dtype):
+
+        # If we have datetime64 or timedelta64 values, make sure they are
+        #  wrappped correctly  GH#31163
+        ser = Series(vals, index=range(3, 6))
+        ser.index = ser.index.astype(dtype)
+
+        expected = vals[1]
+
+        with tm.assert_produces_warning(FutureWarning):
+            result = ser.index.get_value(ser, 4.0)
+        assert isinstance(result, type(expected)) and result == expected
+        with tm.assert_produces_warning(FutureWarning):
+            result = ser.index.get_value(ser, 4)
+        assert isinstance(result, type(expected)) and result == expected
+
+        result = ser[4.0]
+        assert isinstance(result, type(expected)) and result == expected
+        result = ser[4]
+        assert isinstance(result, type(expected)) and result == expected
+
+        result = ser.loc[4.0]
+        assert isinstance(result, type(expected)) and result == expected
+        result = ser.loc[4]
+        assert isinstance(result, type(expected)) and result == expected
+
+        result = ser.at[4.0]
+        assert isinstance(result, type(expected)) and result == expected
+        # GH#31329 .at[4] should cast to 4.0, matching .loc behavior
+        result = ser.at[4]
+        assert isinstance(result, type(expected)) and result == expected
+
+        result = ser.iloc[1]
+        assert isinstance(result, type(expected)) and result == expected
+
+        result = ser.iat[1]
+        assert isinstance(result, type(expected)) and result == expected
+
+    def test_doesnt_contain_all_the_things(self):
+        idx = self._index_cls([np.nan])
+        assert not idx.isin([0]).item()
+        assert not idx.isin([1]).item()
+        assert idx.isin([np.nan]).item()
+
+    def test_nan_multiple_containment(self):
+        index_cls = self._index_cls
+
+        idx = index_cls([1.0, np.nan])
+        tm.assert_numpy_array_equal(idx.isin([1.0]), np.array([True, False]))
+        tm.assert_numpy_array_equal(idx.isin([2.0, np.pi]), np.array([False, False]))
+        tm.assert_numpy_array_equal(idx.isin([np.nan]), np.array([False, True]))
+        tm.assert_numpy_array_equal(idx.isin([1.0, np.nan]), np.array([True, True]))
+        idx = index_cls([1.0, 2.0])
+        tm.assert_numpy_array_equal(idx.isin([np.nan]), np.array([False, False]))
+
+    def test_fillna_float64(self):
+        index_cls = self._index_cls
+        # GH 11343
+        idx = Index([1.0, np.nan, 3.0], dtype=float, name="x")
+        # can't downcast
+        exp = Index([1.0, 0.1, 3.0], name="x")
+        tm.assert_index_equal(idx.fillna(0.1), exp, exact=True)
+
+        # downcast
+        exact = True if index_cls is Int64Index else "equiv"
+        exp = index_cls([1.0, 2.0, 3.0], name="x")
+        tm.assert_index_equal(idx.fillna(2), exp, exact=exact)
+
+        # object
+        exp = Index([1.0, "obj", 3.0], name="x")
+        tm.assert_index_equal(idx.fillna("obj"), exp, exact=True)
+
+
+class TestFloat64Index(TestFloatNumericIndex):
+    _index_cls = Float64Index
+
+    @pytest.fixture
+    def dtype(self, request):
+        return np.float64
+
+    @pytest.fixture(
+        params=["int64", "uint64", "object", "category", "datetime64"],
+    )
+    def invalid_dtype(self, request):
+        return request.param
+
+    def test_constructor_from_base_index(self, dtype):
+        index_cls = self._index_cls
+
+        result = Index(np.array([np.nan], dtype=dtype))
+        assert isinstance(result, index_cls)
+        assert result.dtype == dtype
+        assert pd.isna(result.values).all()
+
+    def test_constructor_32bit(self, dtype):
+        index_cls = self._index_cls
+
+        index = index_cls(np.array([1.0, 2, 3, 4, 5]), dtype=np.float32)
+        assert isinstance(index, index_cls)
+        assert index.dtype == np.float64
+
+        index = index_cls(np.array([1, 2, 3, 4, 5]), dtype=np.float32)
+        assert isinstance(index, index_cls)
+        assert index.dtype == np.float64
+
+
+class NumericInt(NumericBase):
+    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_is_monotonic(self):
+        index_cls = self._index_cls
+
+        index = index_cls([1, 2, 3, 4])
+        assert index.is_monotonic is True
+        assert index.is_monotonic_increasing is True
+        assert index._is_strictly_monotonic_increasing is True
+        assert index.is_monotonic_decreasing is False
+        assert index._is_strictly_monotonic_decreasing is False
+
+        index = index_cls([4, 3, 2, 1])
+        assert index.is_monotonic is False
+        assert index._is_strictly_monotonic_increasing is False
+        assert index._is_strictly_monotonic_decreasing is True
+
+        index = index_cls([1])
+        assert index.is_monotonic is True
+        assert index.is_monotonic_increasing is True
+        assert index.is_monotonic_decreasing is True
+        assert index._is_strictly_monotonic_increasing is True
+        assert index._is_strictly_monotonic_decreasing is True
+
+    def test_is_strictly_monotonic(self):
+        index_cls = self._index_cls
+
+        index = index_cls([1, 1, 2, 3])
+        assert index.is_monotonic_increasing is True
+        assert index._is_strictly_monotonic_increasing is False
+
+        index = index_cls([3, 2, 1, 1])
+        assert index.is_monotonic_decreasing is True
+        assert index._is_strictly_monotonic_decreasing is False
+
+        index = index_cls([1, 1])
+        assert index.is_monotonic_increasing
+        assert index.is_monotonic_decreasing
+        assert not index._is_strictly_monotonic_increasing
+        assert not index._is_strictly_monotonic_decreasing
+
+    def test_logical_compat(self, simple_index):
+        idx = simple_index
+        assert idx.all() == idx.values.all()
+        assert idx.any() == idx.values.any()
+
+    def test_identical(self, simple_index, dtype):
+        index = simple_index
+
+        idx = Index(index.copy())
+        assert idx.identical(index)
+
+        same_values_different_type = Index(idx, dtype=object)
+        assert not idx.identical(same_values_different_type)
+
+        idx = index.astype(dtype=object)
+        idx = idx.rename("foo")
+        same_values = Index(idx, dtype=object)
+        assert same_values.identical(idx)
+
+        assert not idx.identical(index)
+        assert Index(same_values, name="foo", dtype=object).identical(idx)
+
+        assert not index.astype(dtype=object).identical(index.astype(dtype=dtype))
+
+    def test_cant_or_shouldnt_cast(self):
+        msg = (
+            "String dtype not supported, "
+            "you may need to explicitly cast to a numeric type"
+        )
+        # can't
+        data = ["foo", "bar", "baz"]
+        with pytest.raises(TypeError, match=msg):
+            self._index_cls(data)
+
+        # shouldn't
+        data = ["0", "1", "2"]
+        with pytest.raises(TypeError, match=msg):
+            self._index_cls(data)
+
+    def test_view_index(self, simple_index):
+        index = simple_index
+        index.view(Index)
+
+    def test_prevent_casting(self, simple_index):
+        index = simple_index
+        result = index.astype("O")
+        assert result.dtype == np.object_
+
+
+class TestIntNumericIndex(NumericInt):
+    _index_cls = NumericIndex
+
+    @pytest.fixture(params=[np.int64, np.int32, np.int16, np.int8])
+    def dtype(self, request):
+        return request.param
+
+    @pytest.fixture(params=["category", "datetime64", "object"])
+    def invalid_dtype(self, request):
+        return request.param
+
+    @pytest.fixture
+    def simple_index(self, dtype):
+        return self._index_cls(range(0, 20, 2), dtype=dtype)
+
+    @pytest.fixture(
+        params=[range(0, 20, 2), range(19, -1, -1)], ids=["index_inc", "index_dec"]
+    )
+    def index(self, request, dtype):
+        return self._index_cls(request.param, dtype=dtype)
+
+    def test_constructor(self, dtype):
+        index_cls = self._index_cls
+
+        # scalar raise Exception
+        msg = (
+            rf"{index_cls.__name__}\(\.\.\.\) must be called with a collection of some "
+            "kind, 5 was passed"
+        )
+        with pytest.raises(TypeError, match=msg):
+            index_cls(5)
+
+        # copy
+        # pass list, coerce fine
+        index = index_cls([-5, 0, 1, 2], dtype=dtype)
+        arr = index.values
+        new_index = index_cls(arr, copy=True)
+        tm.assert_index_equal(new_index, index, exact=True)
+        val = arr[0] + 3000
+
+        # this should not change index
+        arr[0] = val
+        assert new_index[0] != val
+
+        if dtype == np.int64:
+            exact = "equiv" if index_cls != Int64Index else True
+
+            # pass list, coerce fine
+            index = index_cls([-5, 0, 1, 2], dtype=dtype)
+            expected = Index([-5, 0, 1, 2], dtype=dtype)
+            tm.assert_index_equal(index, expected, exact=exact)
+
+            # from iterable
+            index = index_cls(iter([-5, 0, 1, 2]), dtype=dtype)
+            expected = index_cls([-5, 0, 1, 2], dtype=dtype)
+            tm.assert_index_equal(index, expected, exact=exact)
+
+            # interpret list-like
+            expected = index_cls([5, 0], dtype=dtype)
+            for cls in [Index, index_cls]:
+                for idx in [
+                    cls([5, 0], dtype=dtype),
+                    cls(np.array([5, 0]), dtype=dtype),
+                    cls(Series([5, 0]), dtype=dtype),
+                ]:
+                    tm.assert_index_equal(idx, expected, exact=exact)
+
+    def test_constructor_corner(self, dtype):
+        index_cls = self._index_cls
+
+        arr = np.array([1, 2, 3, 4], dtype=object)
+
+        index = index_cls(arr, dtype=dtype)
+        assert index.values.dtype == index.dtype
+        if dtype == np.int64:
+
+            msg = "will not infer"
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                without_dtype = Index(arr)
+
+            exact = True if index_cls is Int64Index else "equiv"
+            tm.assert_index_equal(index, without_dtype, exact=exact)
+
+        # preventing casting
+        arr = np.array([1, "2", 3, "4"], dtype=object)
+        with pytest.raises(TypeError, match="casting"):
+            index_cls(arr, dtype=dtype)
+
+    def test_constructor_coercion_signed_to_unsigned(
+        self,
+        any_unsigned_int_numpy_dtype,
+    ):
+
+        # see gh-15832
+        msg = "Trying to coerce negative values to unsigned integers"
+
+        with pytest.raises(OverflowError, match=msg):
+            Index([-1], dtype=any_unsigned_int_numpy_dtype)
+
+    def test_coerce_list(self):
+        # coerce things
+        arr = Index([1, 2, 3, 4])
+        assert isinstance(arr, self._index_cls)
+
+        # but not if explicit dtype passed
+        arr = Index([1, 2, 3, 4], dtype=object)
+        assert type(arr) is Index
+
+
+class TestInt64Index(TestIntNumericIndex):
+    _index_cls = Int64Index
+
+    @pytest.fixture
+    def dtype(self):
+        return np.int64
+
+    @pytest.fixture(
+        params=["float64", "uint64", "object", "category", "datetime64"],
+    )
+    def invalid_dtype(self, request):
+        return request.param
+
+    def test_constructor_32bit(self, dtype):
+        index_cls = self._index_cls
+
+        index = index_cls(np.array([1, 2, 3, 4, 5]), dtype=np.int32)
+        assert isinstance(index, index_cls)
+        assert index.dtype == np.int64
+
+        index = index_cls(np.array([1, 2, 3, 4, 5]), dtype=np.int32)
+        assert isinstance(index, index_cls)
+        assert index.dtype == np.int64
+
+
+class TestUIntNumericIndex(NumericInt):
+
+    _index_cls = NumericIndex
+
+    @pytest.fixture(params=[np.uint64])
+    def dtype(self, request):
+        return request.param
+
+    @pytest.fixture(params=["category", "datetime64", "object"])
+    def invalid_dtype(self, request):
+        return request.param
+
+    @pytest.fixture
+    def simple_index(self, dtype):
+        # compat with shared Int64/Float64 tests
+        return self._index_cls(np.arange(5, dtype=dtype))
+
+    @pytest.fixture(
+        params=[
+            [2**63, 2**63 + 10, 2**63 + 15, 2**63 + 20, 2**63 + 25],
+            [2**63 + 25, 2**63 + 20, 2**63 + 15, 2**63 + 10, 2**63],
+        ],
+        ids=["index_inc", "index_dec"],
+    )
+    def index(self, request):
+        return self._index_cls(request.param, dtype=np.uint64)
+
+
+class TestUInt64Index(TestUIntNumericIndex):
+
+    _index_cls = UInt64Index
+
+    @pytest.fixture
+    def dtype(self):
+        return np.uint64
+
+    @pytest.fixture(
+        params=["int64", "float64", "object", "category", "datetime64"],
+    )
+    def invalid_dtype(self, request):
+        return request.param
+
+    def test_constructor(self, dtype):
+        index_cls = self._index_cls
+        exact = True if index_cls is UInt64Index else "equiv"
+
+        idx = index_cls([1, 2, 3])
+        res = Index([1, 2, 3], dtype=dtype)
+        tm.assert_index_equal(res, idx, exact=exact)
+
+        idx = index_cls([1, 2**63])
+        res = Index([1, 2**63], dtype=dtype)
+        tm.assert_index_equal(res, idx, exact=exact)
+
+        idx = index_cls([1, 2**63])
+        res = Index([1, 2**63])
+        tm.assert_index_equal(res, idx, exact=exact)
+
+        idx = Index([-1, 2**63], dtype=object)
+        res = Index(np.array([-1, 2**63], dtype=object))
+        tm.assert_index_equal(res, idx, exact=exact)
+
+        # https://github.com/pandas-dev/pandas/issues/29526
+        idx = index_cls([1, 2**63 + 1], dtype=dtype)
+        res = Index([1, 2**63 + 1], dtype=dtype)
+        tm.assert_index_equal(res, idx, exact=exact)
+
+    def test_constructor_does_not_cast_to_float(self):
+        # https://github.com/numpy/numpy/issues/19146
+        values = [0, np.iinfo(np.uint64).max]
+
+        result = UInt64Index(values)
+        assert list(result) == values
+
+    def test_constructor_32bit(self, dtype):
+        index_cls = self._index_cls
+
+        index = index_cls(np.array([1, 2, 3, 4, 5]), dtype=np.uint32)
+        assert isinstance(index, index_cls)
+        assert index.dtype == np.uint64
+
+        index = index_cls(np.array([1, 2, 3, 4, 5]), dtype=np.uint32)
+        assert isinstance(index, index_cls)
+        assert index.dtype == np.uint64
+
+
+@pytest.mark.parametrize(
+    "box",
+    [list, lambda x: np.array(x, dtype=object), lambda x: Index(x, dtype=object)],
+)
+def test_uint_index_does_not_convert_to_float64(box):
+    # https://github.com/pandas-dev/pandas/issues/28279
+    # https://github.com/pandas-dev/pandas/issues/28023
+    series = Series(
+        [0, 1, 2, 3, 4, 5],
+        index=[
+            7606741985629028552,
+            17876870360202815256,
+            17876870360202815256,
+            13106359306506049338,
+            8991270399732411471,
+            8991270399732411472,
+        ],
+    )
+
+    result = series.loc[box([7606741985629028552, 17876870360202815256])]
+
+    expected = UInt64Index(
+        [7606741985629028552, 17876870360202815256, 17876870360202815256],
+        dtype="uint64",
+    )
+    tm.assert_index_equal(result.index, expected)
+
+    tm.assert_equal(result, series[:3])
+
+
+def test_float64_index_equals():
+    # https://github.com/pandas-dev/pandas/issues/35217
+    float_index = Index([1.0, 2, 3])
+    string_index = Index(["1", "2", "3"])
+
+    result = float_index.equals(string_index)
+    assert result is False
+
+    result = string_index.equals(float_index)
+    assert result is False
+
+
+def test_map_dtype_inference_unsigned_to_signed():
+    # GH#44609 cases where we don't retain dtype
+    idx = UInt64Index([1, 2, 3])
+    result = idx.map(lambda x: -x)
+    expected = Int64Index([-1, -2, -3])
+    tm.assert_index_equal(result, expected)
+
+
+def test_map_dtype_inference_overflows():
+    # GH#44609 case where we have to upcast
+    idx = NumericIndex(np.array([1, 2, 3], dtype=np.int8))
+    result = idx.map(lambda x: x * 1000)
+    # TODO: we could plausibly try to infer down to int16 here
+    expected = NumericIndex([1000, 2000, 3000], dtype=np.int64)
+    tm.assert_index_equal(result, expected)