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| import numpy as np
| import pytest
|
| import pandas._testing as tm
| from pandas.core.construction import sanitize_array
|
|
| @pytest.mark.parametrize(
| "values, dtype, expected",
| [
| ([1, 2, 3], None, np.array([1, 2, 3], dtype=np.int64)),
| (np.array([1, 2, 3]), None, np.array([1, 2, 3])),
| (["1", "2", None], None, np.array(["1", "2", None])),
| (["1", "2", None], np.dtype("str"), np.array(["1", "2", None])),
| ([1, 2, None], np.dtype("str"), np.array(["1", "2", None])),
| ],
| )
| def test_construct_1d_ndarray_preserving_na(values, dtype, expected):
| result = sanitize_array(values, index=None, dtype=dtype)
| tm.assert_numpy_array_equal(result, expected)
|
|
| @pytest.mark.parametrize("dtype", ["m8[ns]", "M8[ns]"])
| def test_construct_1d_ndarray_preserving_na_datetimelike(dtype):
| arr = np.arange(5, dtype=np.int64).view(dtype)
| expected = np.array(list(arr), dtype=object)
| assert all(isinstance(x, type(arr[0])) for x in expected)
|
| result = sanitize_array(arr, index=None, dtype=np.dtype(object))
| tm.assert_numpy_array_equal(result, expected)
|
|
