Example #1
0
    def test_convert_downcast_int64(self):
        from pandas.io.libparsers import na_values

        arr = np.array([1, 2, 7, 8, 10], dtype=np.int64)
        expected = np.array([1, 2, 7, 8, 10], dtype=np.int8)

        # default argument
        result = lib.downcast_int64(arr, na_values)
        tm.assert_numpy_array_equal(result, expected)

        result = lib.downcast_int64(arr, na_values, use_unsigned=False)
        tm.assert_numpy_array_equal(result, expected)

        expected = np.array([1, 2, 7, 8, 10], dtype=np.uint8)
        result = lib.downcast_int64(arr, na_values, use_unsigned=True)
        tm.assert_numpy_array_equal(result, expected)

        # still cast to int8 despite use_unsigned=True
        # because of the negative number as an element
        arr = np.array([1, 2, -7, 8, 10], dtype=np.int64)
        expected = np.array([1, 2, -7, 8, 10], dtype=np.int8)
        result = lib.downcast_int64(arr, na_values, use_unsigned=True)
        tm.assert_numpy_array_equal(result, expected)

        arr = np.array([1, 2, 7, 8, 300], dtype=np.int64)
        expected = np.array([1, 2, 7, 8, 300], dtype=np.int16)
        result = lib.downcast_int64(arr, na_values)
        tm.assert_numpy_array_equal(result, expected)

        int8_na = na_values[np.int8]
        int64_na = na_values[np.int64]
        arr = np.array([int64_na, 2, 3, 10, 15], dtype=np.int64)
        expected = np.array([int8_na, 2, 3, 10, 15], dtype=np.int8)
        result = lib.downcast_int64(arr, na_values)
        tm.assert_numpy_array_equal(result, expected)
Example #2
0
    def test_convert_downcast_int64(self):
        from pandas._libs.parsers import na_values

        arr = np.array([1, 2, 7, 8, 10], dtype=np.int64)
        expected = np.array([1, 2, 7, 8, 10], dtype=np.int8)

        # default argument
        result = lib.downcast_int64(arr, na_values)
        tm.assert_numpy_array_equal(result, expected)

        result = lib.downcast_int64(arr, na_values, use_unsigned=False)
        tm.assert_numpy_array_equal(result, expected)

        expected = np.array([1, 2, 7, 8, 10], dtype=np.uint8)
        result = lib.downcast_int64(arr, na_values, use_unsigned=True)
        tm.assert_numpy_array_equal(result, expected)

        # still cast to int8 despite use_unsigned=True
        # because of the negative number as an element
        arr = np.array([1, 2, -7, 8, 10], dtype=np.int64)
        expected = np.array([1, 2, -7, 8, 10], dtype=np.int8)
        result = lib.downcast_int64(arr, na_values, use_unsigned=True)
        tm.assert_numpy_array_equal(result, expected)

        arr = np.array([1, 2, 7, 8, 300], dtype=np.int64)
        expected = np.array([1, 2, 7, 8, 300], dtype=np.int16)
        result = lib.downcast_int64(arr, na_values)
        tm.assert_numpy_array_equal(result, expected)

        int8_na = na_values[np.int8]
        int64_na = na_values[np.int64]
        arr = np.array([int64_na, 2, 3, 10, 15], dtype=np.int64)
        expected = np.array([int8_na, 2, 3, 10, 15], dtype=np.int8)
        result = lib.downcast_int64(arr, na_values)
        tm.assert_numpy_array_equal(result, expected)