3cb6ee8f93b805d0cf8f7896b455e57632de9840,pandas/tests/series/test_dtypes.py,TestSeriesDtypes,test_astype_categorical_to_other,#TestSeriesDtypes#,55

Before Change

    def test_astype_categorical_to_other(self):

        value = np.random.RandomState(0).randint(0, 10000, 100)
        df = DataFrame({"value": value})
        labels = [f"{i} - {i + 499}" for i in range(0, 10000, 500)]
        cat_labels = Categorical(labels, labels)

        df = df.sort_values(by=["value"], ascending=True)
        df["value_group"] = pd.cut(
            df.value, range(0, 10500, 500), right=False, labels=cat_labels
        )

        s = df["value_group"]
        expected = s
        tm.assert_series_equal(s.astype("category"), expected)
        tm.assert_series_equal(s.astype(CategoricalDtype()), expected)
        msg = r"could not convert string to float|invalid literal for float\(\)"

After Change

    def test_astype_categorical_to_other(self):
        cat = Categorical([f"{i} - {i + 499}" for i in range(0, 10000, 500)])
        ser = Series(np.random.RandomState(0).randint(0, 10000, 100)).sort_values()
        ser = pd.cut(ser, range(0, 10500, 500), right=False, labels=cat)

        expected = ser
        tm.assert_series_equal(ser.astype("category"), expected)
        tm.assert_series_equal(ser.astype(CategoricalDtype()), expected)
        msg = r"could not convert string to float|invalid literal for float\(\)"
        with pytest.raises(ValueError, match=msg):
            ser.astype("float64")

        cat = Series(Categorical(["a", "b", "b", "a", "a", "c", "c", "c"]))
        exp = Series(["a", "b", "b", "a", "a", "c", "c", "c"])
        tm.assert_series_equal(cat.astype("str"), exp)
        s2 = Series(Categorical(["1", "2", "3", "4"]))
        exp2 = Series([1, 2, 3, 4]).astype(int)
        tm.assert_series_equal(s2.astype("int"), exp2)

        // object don"t sort correctly, so just compare that we have the same
        // values
        def cmp(a, b):
            tm.assert_almost_equal(np.sort(np.unique(a)), np.sort(np.unique(b)))

        expected = Series(np.array(ser.values), name="value_group")
        cmp(ser.astype("object"), expected)
        cmp(ser.astype(np.object_), expected)

        // array conversion
        tm.assert_almost_equal(np.array(ser), np.array(ser.values))

        tm.assert_series_equal(ser.astype("category"), ser)
        tm.assert_series_equal(ser.astype(CategoricalDtype()), ser)

        roundtrip_expected = ser.cat.set_categories(
            ser.cat.categories.sort_values()
        ).cat.remove_unused_categories()
        result = ser.astype("object").astype("category")
        tm.assert_series_equal(result, roundtrip_expected)
        result = ser.astype("object").astype(CategoricalDtype())
        tm.assert_series_equal(result, roundtrip_expected)

    def test_astype_categorical_invalid_conversions(self):
        // invalid conversion (these are NOT a dtype)

Instances