danepitkin commented on code in PR #35656:
URL: https://github.com/apache/arrow/pull/35656#discussion_r1242896003
##########
python/pyarrow/tests/test_array.py:
##########
@@ -212,8 +212,9 @@ def test_to_numpy_writable():
@pytest.mark.parametrize('unit', ['s', 'ms', 'us', 'ns'])
-def test_to_numpy_datetime64(unit):
- arr = pa.array([1, 2, 3], pa.timestamp(unit))
[email protected]('tz', [None, "UTC"])
+def test_to_numpy_datetime64(unit, tz):
+ arr = pa.array([1, 2, 3], pa.timestamp(unit, tz=tz))
expected = np.array([1, 2, 3], dtype="datetime64[{}]".format(unit))
np_arr = arr.to_numpy()
np.testing.assert_array_equal(np_arr, expected)
Review Comment:
Looks like this is tested in test_pandas.py in
`test_timestamps_with_timezone`. It will call the following function on a
pandas series and I confirmed it is converted into a pyarrow TimestampArray (vs
a ChunkedArray)
```
def _check_series_roundtrip(s, type_=None, expected_pa_type=None):
arr = pa.array(s, from_pandas=True, type=type_)
if type_ is not None and expected_pa_type is None:
expected_pa_type = type_
if expected_pa_type is not None:
assert arr.type == expected_pa_type
result = pd.Series(arr.to_pandas(), name=s.name)
tm.assert_series_equal(s, result)
```
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