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BUG - anchoring dates for resample with Day(n>1) #24159

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Merged
merged 8 commits into from
Dec 13, 2018
Merged

BUG - anchoring dates for resample with Day(n>1) #24159

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3a552a3
BUG - fix resample for Day offsets n>1 and update associated test
sds9995 Dec 8, 2018
ecdd31c
DOC - add whatsnew entry
sds9995 Dec 8, 2018
be07f5b
TST - add tests for equivalent offsets
sds9995 Dec 8, 2018
9b63c38
CLN - pep8 adherence
sds9995 Dec 8, 2018
2b7f935
Merge branch 'master' into bug/get_range_edges
sds9995 Dec 8, 2018
4967c95
CLN - pep8 adherence
sds9995 Dec 8, 2018
1d4ac73
CLN - parametrize tests and add issue reference
sds9995 Dec 9, 2018
37252a0
TST - add more test cases
sds9995 Dec 11, 2018
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.rst
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Expand Up @@ -1516,6 +1516,7 @@ Groupby/Resample/Rolling

- Bug in :func:`pandas.core.groupby.GroupBy.first` and :func:`pandas.core.groupby.GroupBy.last` with ``as_index=False`` leading to the loss of timezone information (:issue:`15884`)
- Bug in :meth:`DatetimeIndex.resample` when downsampling across a DST boundary (:issue:`8531`)
- Bug in date anchoring for :meth:`DatetimeIndex.resample` with offset :class:`Day` when n > 1 (:issue:`24127`)
- Bug where ``ValueError`` is wrongly raised when calling :func:`~pandas.core.groupby.SeriesGroupBy.count` method of a
``SeriesGroupBy`` when the grouping variable only contains NaNs and numpy version < 1.13 (:issue:`21956`).
- Multiple bugs in :func:`pandas.core.Rolling.min` with ``closed='left'`` and a
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4 changes: 2 additions & 2 deletions pandas/core/resample.py
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Expand Up @@ -1587,8 +1587,8 @@ def _get_range_edges(first, last, offset, closed='left', base=0):
is_day = isinstance(offset, Day)
day_nanos = delta_to_nanoseconds(timedelta(1))

# #1165
if (is_day and day_nanos % offset.nanos == 0) or not is_day:
# #1165 and #24127
if (is_day and not offset.nanos % day_nanos) or not is_day:
return _adjust_dates_anchored(first, last, offset,
closed=closed, base=base)

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4 changes: 2 additions & 2 deletions pandas/tests/groupby/test_timegrouper.py
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Expand Up @@ -43,8 +43,8 @@ def test_groupby_with_timegrouper(self):

expected = DataFrame(
{'Quantity': 0},
index=date_range('20130901 13:00:00',
'20131205 13:00:00', freq='5D',
index=date_range('20130901',
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Why did this test have to change?

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The current behavior for Day(n>1) is inconsistent with all other offsets and their multiples, in that it is not getting anchored on the offset when being resampled. This was due to the reversal of the modulo op (which was valid for n=1, but not otherwise).

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What was the result/expected before and the result/expected after this change?

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>>> s = pd.Series(range(50), index=pd.date_range('11/11/2000 06:00:00', periods=50, freq='H'))
>>> s.resample('2D').mean()

Before:

# Result - note that the freq is not set either 
>>> s.resample('2D').mean()
2000-11-11 06:00:00    48
2000-11-13 06:00:00     2
dtype: int64

# Expected - freq should be set to 2D and index should be anchored to 0hour of the day
2000-11-11    42
2000-11-13     8
Freq: 2D, dtype: int64

After: both match expected from above

The correct analogous behavior with hourly resample can be seen with the current master code

>>> s = pd.Series(range(200), index=pd.date_range('11/11/2000 06:23', periods=200, freq='Min'))
>>> s.resample('2H').mean()
2000-11-11 06:00:00     48
2000-11-11 08:00:00    148
Freq: 2H, dtype: int64

Notice that the daterange didn't start on the offset, but the result was anchored to the hour start

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Makes sense. Thanks

'20131205', freq='5D',
name='Date', closed='left'))
expected.iloc[[0, 6, 18], 0] = np.array([24, 6, 9], dtype='int64')

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26 changes: 26 additions & 0 deletions pandas/tests/resample/test_datetime_index.py
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Expand Up @@ -1463,3 +1463,29 @@ def f(data, add_arg):
result = df.groupby("A").resample("D").agg(f, multiplier)
expected = df.groupby("A").resample('D').mean().multiply(multiplier)
assert_frame_equal(result, expected)

@pytest.mark.parametrize('k', [1, 2, 3])
@pytest.mark.parametrize('n1, freq1, n2, freq2', [
(30, 'S', 0.5, 'Min'),
(60, 'S', 1, 'Min'),
(3600, 'S', 1, 'H'),
(60, 'Min', 1, 'H'),
(21600, 'S', 0.25, 'D'),
(86400, 'S', 1, 'D'),
(43200, 'S', 0.5, 'D'),
(1440, 'Min', 1, 'D'),
(12, 'H', 0.5, 'D'),
(24, 'H', 1, 'D'),
])
def test_resample_equivalent_offsets(self, n1, freq1, n2, freq2, k):
# GH 24127
n1_ = n1 * k
n2_ = n2 * k
s = pd.Series(0, index=pd.date_range('19910905 13:00',
'19911005 07:00',
freq=freq1))
s = s + range(len(s))

result1 = s.resample(str(n1_) + freq1).mean()
result2 = s.resample(str(n2_) + freq2).mean()
assert_series_equal(result1, result2)