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)