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Fix DatetimeIndex.insert(pd.NaT) for tz-aware index #18883

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Merged
merged 8 commits into from
Dec 29, 2017
Merged
1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.23.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -303,6 +303,7 @@ Indexing
- :func:`Index.to_series` now accepts ``index`` and ``name`` kwargs (:issue:`18699`)
- :func:`DatetimeIndex.to_series` now accepts ``index`` and ``name`` kwargs (:issue:`18699`)
- Bug in indexing non-scalar value from ``Series`` having non-unique ``Index`` will return value flattened (:issue:`17610`)
- Bug in :func:`DatetimeIndex.insert` where inserting ``NaT`` into a timezone-aware index incorrectly raised (:issue:`16357`)


I/O
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2 changes: 1 addition & 1 deletion pandas/core/indexes/datetimes.py
Original file line number Diff line number Diff line change
Expand Up @@ -1775,7 +1775,7 @@ def insert(self, loc, item):

if isinstance(item, (datetime, np.datetime64)):
self._assert_can_do_op(item)
if not self._has_same_tz(item):
if not self._has_same_tz(item) and not isna(item):
raise ValueError(
'Passed item and index have different timezone')
# check freq can be preserved on edge cases
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16 changes: 9 additions & 7 deletions pandas/tests/indexes/datetimes/test_indexing.py
Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,15 @@ def test_where_tz(self):
expected = i2
tm.assert_index_equal(result, expected)

@pytest.mark.parametrize('tz', [None, 'UTC', 'US/Eastern'])
def test_insert_nat(self, tz):
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@jschendel jschendel Dec 21, 2017

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You could maybe parametrize over different NA values here, since this should work for inserting np.nan and None as well (shouldn't require any additional code changes). For example, on a tz-naive DTI:

In [2]: pd.date_range('20170101', periods=2).insert(0, np.nan)
Out[2]: DatetimeIndex(['NaT', '2017-01-01', '2017-01-02'], dtype='datetime64[ns]', freq=None)

In [3]: pd.date_range('20170101', periods=2).insert(0, None)
Out[3]: DatetimeIndex(['NaT', '2017-01-01', '2017-01-02'], dtype='datetime64[ns]', freq=None)

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If you do that, I suppose you could delete these lines in test_insert below, as to not duplicate things:

# GH 18295 (test missing)
expected = DatetimeIndex(
['20170101', pd.NaT, '20170102', '20170103', '20170104'])
for na in (np.nan, pd.NaT, None):
result = date_range('20170101', periods=4).insert(1, na)
tm.assert_index_equal(result, expected)

# GH#16537, GH#18295 (test missing)
idx = pd.DatetimeIndex(['2017-01-01'], tz=tz)
expected = pd.DatetimeIndex(['NaT', '2017-01-01'], tz=tz)
for null in [None, np.nan, pd.NaT]:
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can you pull this null into the paramaterization?

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Sure, pushing momentarily.

res = idx.insert(0, null)
tm.assert_index_equal(res, expected)

def test_insert(self):
idx = DatetimeIndex(
['2000-01-04', '2000-01-01', '2000-01-02'], name='idx')
Expand Down Expand Up @@ -145,13 +154,6 @@ def test_insert(self):
assert result.tz == expected.tz
assert result.freq is None

# GH 18295 (test missing)
expected = DatetimeIndex(
['20170101', pd.NaT, '20170102', '20170103', '20170104'])
for na in (np.nan, pd.NaT, None):
result = date_range('20170101', periods=4).insert(1, na)
tm.assert_index_equal(result, expected)

def test_delete(self):
idx = date_range(start='2000-01-01', periods=5, freq='M', name='idx')

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