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BUG: date_range issue with sub-second granularity #24129

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -1305,6 +1305,7 @@ Datetimelike
- Bug in :class:`DatetimeIndex` where calling ``np.array(dtindex, dtype=object)`` would incorrectly return an array of ``long`` objects (:issue:`23524`)
- Bug in :class:`Index` where passing a timezone-aware :class:`DatetimeIndex` and `dtype=object` would incorrectly raise a ``ValueError`` (:issue:`23524`)
- Bug in :class:`Index` where calling ``np.array(dtindex, dtype=object)`` on a timezone-naive :class:`DatetimeIndex` would return an array of ``datetime`` objects instead of :class:`Timestamp` objects, potentially losing nanosecond portions of the timestamps (:issue:`23524`)
- Bug in :func:`date_range` where using dates with millisecond resolution or higher could return incorrect values or the wrong number of values in the index (:issue:`24110`)

Timedelta
^^^^^^^^^
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7 changes: 6 additions & 1 deletion pandas/core/arrays/datetimes.py
Original file line number Diff line number Diff line change
Expand Up @@ -307,7 +307,12 @@ def _generate_range(cls, start, end, periods, freq, tz=None,
end = end.tz_localize(tz).asm8
else:
# Create a linearly spaced date_range in local time
arr = np.linspace(start.value, end.value, periods)
# Nanosecond-granularity timestamps aren't always correctly
# representable with doubles, so we limit the range that we
# pass to np.linspace as much as possible
arr = np.linspace(
0, end.value - start.value,
periods, dtype='int64') + start.value
index = cls._simple_new(
arr.astype('M8[ns]', copy=False), freq=None, tz=tz
)
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11 changes: 11 additions & 0 deletions pandas/tests/indexes/datetimes/test_date_range.py
Original file line number Diff line number Diff line change
Expand Up @@ -769,3 +769,14 @@ def test_all_custom_freq(self, freq):
msg = 'invalid custom frequency string: {freq}'
with pytest.raises(ValueError, match=msg.format(freq=bad_freq)):
bdate_range(START, END, freq=bad_freq)

@pytest.mark.parametrize('start_end', [
('2018-01-01T00:00:01.000Z', '2018-01-03T00:00:01.000Z'),
('2018-01-01T00:00:00.010Z', '2018-01-03T00:00:00.010Z'),
('2001-01-01T00:00:00.010Z', '2001-01-03T00:00:00.010Z')])
def test_range_with_millisecond_resolution(self, start_end):
# https://github.com/pandas-dev/pandas/issues/24110
start, end = start_end
result = pd.date_range(start=start, end=end, periods=2, closed='left')
expected = DatetimeIndex([start])
tm.assert_index_equal(result, expected)