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