BUG: Can't change datetime precision in columns/rows about pandas HOT 5 OPEN

In [2]: import pandas as pd

In [3]:
   ...: df = pd.DataFrame({'time': pd.to_datetime(['2021-01-01 12:00:00', '2021-01-01 12:00:01', '2021-01-01 12:00:02'])
   ...: ,
   ...:                            'value': [1, 2, 3]})

In [4]: df.iloc[:, 0] = df.iloc[:, 0].astype('M8[us]')

In [5]: df.dtypes
Out[5]:
time     datetime64[ns]
value             int64
dtype: object

In [6]: pd.__version__
Out[6]: '2.0.2'

@pytest.mark.parametrize(
        "dtype", ["int64", "float64"], ids=["single-block", "mixed-block"]
    )
    def test_subset_set_column_with_loc(backend, dtype):
        # Case: setting a single column with loc on a viewing subset
        # -> subset.loc[:, col] = value
        _, DataFrame, _ = backend
        df = DataFrame(
            {"a": [1, 2, 3], "b": [4, 5, 6], "c": np.array([7, 8, 9], dtype=dtype)}
        )
        df_orig = df.copy()
        subset = df[1:3]

        subset.loc[:, "a"] = np.array([10, 11], dtype="int64")

        subset._mgr._verify_integrity()
        expected = DataFrame(
            {"a": [10, 11], "b": [5, 6], "c": np.array([8, 9], dtype=dtype)},
            index=range(1, 3),
        )
>       tm.assert_frame_equal(subset, expected)
E       AssertionError: Attributes of DataFrame.iloc[:, 0] (column name="a") are different
E
E       Attribute "dtype" are different
E       [left]:  int64
E       [right]: Int64

df = pd.DataFrame({'a': [1,2,3]}, dtype='int64')
df.loc[:, 'a'] = df.loc[:, 'a'].astype('int32')
print(df.dtypes) # a is still int64