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Merge pull request #7043 from sinhrks/pslice
ENH/BUG: partial string indexing with PeriodIndex
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‎doc/source/release.rst

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@@ -498,6 +498,7 @@ Bug Fixes
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- Bug in ``Dataframe.set_index``, ``reindex`` and ``pivot`` don't preserve ``DatetimeIndex`` and ``PeriodIndex`` attributes (:issue:`3950`, :issue:`5878`, :issue:`6631`)
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- Bug in ``MultiIndex.get_level_values`` doesn't preserve ``DatetimeIndex`` and ``PeriodIndex`` attributes (:issue:`7092`)
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- Bug in ``Groupby`` doesn't preserve ``tz`` (:issue:`3950`)
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- Bug in ``PeriodIndex`` partial string slicing (:issue:`6716`)
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pandas 0.13.1
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-------------

‎doc/source/timeseries.rst

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@@ -299,8 +299,10 @@ intelligent functionality like selection, slicing, etc.
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ts[:5].index
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ts[::2].index
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Partial String Indexing
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~~~~~~~~~~~~~~~~~~~~~~~
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.. _timeseries.partialindexing:
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DatetimeIndex Partial String Indexing
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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You can pass in dates and strings that parse to dates as indexing parameters:
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@@ -1092,7 +1094,38 @@ objects:
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.. ipython:: python
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Series(randn(len(prng)), prng)
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ps = Series(randn(len(prng)), prng)
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ps
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PeriodIndex Partial String Indexing
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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You can pass in dates and strings to `Series` and `DataFrame` with `PeriodIndex`, as the same manner as `DatetimeIndex`. For details, refer to :ref:`DatetimeIndex Partial String Indexing <timeseries.partialindexing>`.
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.. ipython:: python
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ps['2011-01']
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ps[datetime(2011, 12, 25):]
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ps['10/31/2011':'12/31/2011']
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Passing string represents lower frequency than `PeriodIndex` returns partial sliced data.
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.. ipython:: python
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ps['2011']
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dfp = DataFrame(randn(600,1), columns=['A'],
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index=period_range('2013-01-01 9:00', periods=600, freq='T'))
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dfp
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dfp['2013-01-01 10H']
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As the same as `DatetimeIndex`, the endpoints will be included in the result. Below example slices data starting from 10:00 to 11:59.
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.. ipython:: python
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dfp['2013-01-01 10H':'2013-01-01 11H']
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Frequency Conversion and Resampling with PeriodIndex
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

‎doc/source/v0.14.0.txt

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@@ -591,6 +591,15 @@ Enhancements
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- str.wrap implemented (:issue:`6999`)
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- `PeriodIndex` fully supports partial string indexing like `DatetimeIndex` (:issue:`7043`)
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.. ipython:: python
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prng = period_range('2013-01-01 09:00', periods=100, freq='H')
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ps = Series(np.random.randn(len(prng)), index=prng)
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ps
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ps['2013-01-02']
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.. _whatsnew_0140.performance:
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Performance

‎pandas/tseries/period.py

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Original file line numberDiff line numberDiff line change
@@ -908,13 +908,13 @@ def get_value(self, series, key):
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pos = np.searchsorted(self.values, [ord1, ord2])
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key = slice(pos[0], pos[1] + 1)
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return series[key]
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else:
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elif grp == freqn:
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key = Period(asdt, freq=self.freq).ordinal
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return _maybe_box(self, self._engine.get_value(s, key), series, key)
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else:
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raise KeyError(key)
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except TypeError:
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pass
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except KeyError:
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pass
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key = Period(key, self.freq).ordinal
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return _maybe_box(self, self._engine.get_value(s, key), series, key)
@@ -978,8 +978,10 @@ def _get_string_slice(self, key):
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raise ValueError('Partial indexing only valid for '
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'ordered time series')
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asdt, parsed, reso = parse_time_string(key, self.freq)
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key = asdt
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key, parsed, reso = parse_time_string(key, self.freq)
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grp = _freq_mod._infer_period_group(reso)
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freqn = _freq_mod._period_group(self.freq)
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if reso == 'year':
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t1 = Period(year=parsed.year, freq='A')
@@ -988,6 +990,19 @@ def _get_string_slice(self, key):
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elif reso == 'quarter':
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q = (parsed.month - 1) // 3 + 1
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t1 = Period(year=parsed.year, quarter=q, freq='Q-DEC')
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elif reso == 'day' and grp < freqn:
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t1 = Period(year=parsed.year, month=parsed.month, day=parsed.day,
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freq='D')
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elif reso == 'hour' and grp < freqn:
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t1 = Period(year=parsed.year, month=parsed.month, day=parsed.day,
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hour=parsed.hour, freq='H')
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elif reso == 'minute' and grp < freqn:
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t1 = Period(year=parsed.year, month=parsed.month, day=parsed.day,
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hour=parsed.hour, minute=parsed.minute, freq='T')
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elif reso == 'second' and grp < freqn:
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t1 = Period(year=parsed.year, month=parsed.month, day=parsed.day,
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hour=parsed.hour, minute=parsed.minute, second=parsed.second,
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freq='S')
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else:
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raise KeyError(key)
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‎pandas/tseries/tests/test_period.py

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Original file line numberDiff line numberDiff line change
@@ -1851,6 +1851,97 @@ def test_pindex_slice_index(self):
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exp = s[12:24]
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assert_series_equal(res, exp)
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def test_getitem_day(self):
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# GH 6716
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# Confirm DatetimeIndex and PeriodIndex works identically
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didx = DatetimeIndex(start='2013/01/01', freq='D', periods=400)
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pidx = PeriodIndex(start='2013/01/01', freq='D', periods=400)
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for idx in [didx, pidx]:
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# getitem against index should raise ValueError
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values = ['2014', '2013/02', '2013/01/02',
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'2013/02/01 9H', '2013/02/01 09:00']
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for v in values:
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with tm.assertRaises(ValueError):
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idx[v]
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s = Series(np.random.rand(len(idx)), index=idx)
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assert_series_equal(s['2013/01'], s[0:31])
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assert_series_equal(s['2013/02'], s[31:59])
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assert_series_equal(s['2014'], s[365:])
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invalid = ['2013/02/01 9H', '2013/02/01 09:00']
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for v in invalid:
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with tm.assertRaises(KeyError):
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s[v]
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def test_range_slice_day(self):
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# GH 6716
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didx = DatetimeIndex(start='2013/01/01', freq='D', periods=400)
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pidx = PeriodIndex(start='2013/01/01', freq='D', periods=400)
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for idx in [didx, pidx]:
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# slices against index should raise IndexError
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values = ['2014', '2013/02', '2013/01/02',
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'2013/02/01 9H', '2013/02/01 09:00']
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for v in values:
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with tm.assertRaises(IndexError):
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idx[v:]
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s = Series(np.random.rand(len(idx)), index=idx)
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assert_series_equal(s['2013/01/02':], s[1:])
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assert_series_equal(s['2013/01/02':'2013/01/05'], s[1:5])
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assert_series_equal(s['2013/02':], s[31:])
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assert_series_equal(s['2014':], s[365:])
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invalid = ['2013/02/01 9H', '2013/02/01 09:00']
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for v in invalid:
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with tm.assertRaises(IndexError):
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idx[v:]
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def test_getitem_seconds(self):
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# GH 6716
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didx = DatetimeIndex(start='2013/01/01 09:00:00', freq='S', periods=4000)
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pidx = PeriodIndex(start='2013/01/01 09:00:00', freq='S', periods=4000)
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for idx in [didx, pidx]:
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# getitem against index should raise ValueError
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values = ['2014', '2013/02', '2013/01/02',
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'2013/02/01 9H', '2013/02/01 09:00']
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for v in values:
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with tm.assertRaises(ValueError):
1914+
idx[v]
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s = Series(np.random.rand(len(idx)), index=idx)
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assert_series_equal(s['2013/01/01 10:00'], s[3600:3660])
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assert_series_equal(s['2013/01/01 9H'], s[:3600])
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for d in ['2013/01/01', '2013/01', '2013']:
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assert_series_equal(s[d], s)
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def test_range_slice_seconds(self):
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# GH 6716
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didx = DatetimeIndex(start='2013/01/01 09:00:00', freq='S', periods=4000)
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pidx = PeriodIndex(start='2013/01/01 09:00:00', freq='S', periods=4000)
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for idx in [didx, pidx]:
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# slices against index should raise IndexError
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values = ['2014', '2013/02', '2013/01/02',
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'2013/02/01 9H', '2013/02/01 09:00']
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for v in values:
1933+
with tm.assertRaises(IndexError):
1934+
idx[v:]
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s = Series(np.random.rand(len(idx)), index=idx)
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assert_series_equal(s['2013/01/01 09:05':'2013/01/01 09:10'], s[300:660])
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assert_series_equal(s['2013/01/01 10:00':'2013/01/01 10:05'], s[3600:3960])
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assert_series_equal(s['2013/01/01 10H':], s[3600:])
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assert_series_equal(s[:'2013/01/01 09:30'], s[:1860])
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for d in ['2013/01/01', '2013/01', '2013']:
1943+
assert_series_equal(s[d:], s)
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def test_pindex_qaccess(self):
18551946
pi = PeriodIndex(['2Q05', '3Q05', '4Q05', '1Q06', '2Q06'], freq='Q')
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s = Series(np.random.rand(len(pi)), index=pi).cumsum()

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