Esempio n. 1
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def test_setting_fill_value_updates():
    arr = SparseArray([0.0, np.nan], fill_value=0)
    arr.fill_value = np.nan
    # use private constructor to get the index right
    # otherwise both nans would be un-stored.
    expected = SparseArray._simple_new(
        sparse_array=np.array([np.nan]),
        sparse_index=IntIndex(2, [1]),
        dtype=SparseDtype(float, np.nan),
    )
    tm.assert_sp_array_equal(arr, expected)
Esempio n. 2
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    def test_astype(self):
        # float -> float
        arr = SparseArray([None, None, 0, 2])
        result = arr.astype("Sparse[float32]")
        expected = SparseArray([None, None, 0, 2], dtype=np.dtype("float32"))
        tm.assert_sp_array_equal(result, expected)

        dtype = SparseDtype("float64", fill_value=0)
        result = arr.astype(dtype)
        expected = SparseArray._simple_new(
            np.array([0.0, 2.0], dtype=dtype.subtype), IntIndex(4, [2, 3]),
            dtype)
        tm.assert_sp_array_equal(result, expected)

        dtype = SparseDtype("int64", 0)
        result = arr.astype(dtype)
        expected = SparseArray._simple_new(np.array([0, 2], dtype=np.int64),
                                           IntIndex(4, [2, 3]), dtype)
        tm.assert_sp_array_equal(result, expected)

        arr = SparseArray([0, np.nan, 0, 1], fill_value=0)
        with pytest.raises(ValueError, match="NA"):
            arr.astype("Sparse[i8]")