BUG: .asfreq on resample on PeriodIndex/TimedeltaIndex are not

doc/source/whatsnew/v0.18.1.txt

@@ -287,6 +287,7 @@ Bug Fixes
 
 
 - Bug in ``.loc`` with out-of-bounds in a large indexer would raise ``IndexError`` rather than ``KeyError`` (:issue:`12527`)
+- Bug in resampling when using a ``TimedeltaIndex`` and ``.asfreq()``, would previously not include the final fencepost (:issue:`12926`)
 - Bug in equality testing with a ``Categorical`` in a ``DataFrame`` (:issue:`12564`)
 - Bug in ``GroupBy.first()``, ``.last()`` returns incorrect row when ``TimeGrouper`` is used (:issue:`7453`)
 

pandas/tseries/frequencies.py

@@ -1124,6 +1124,26 @@ def _maybe_add_count(base, count):
         return base
 
 
+def _maybe_coerce_freq(code):
+    """ we might need to coerce a code to a rule_code
+    and uppercase it
+
+    Parameters
+    ----------
+    source : string
+        Frequency converting from
+
+    Returns
+    -------
+    string code
+    """
+
+    assert code is not None
+    if isinstance(code, offsets.DateOffset):
+        code = code.rule_code
+    return code.upper()
+
+
 def is_subperiod(source, target):
     """
     Returns True if downsampling is possible between source and target
@@ -1140,14 +1160,12 @@ def is_subperiod(source, target):
     -------
     is_subperiod : boolean
     """
-    if isinstance(source, offsets.DateOffset):
-        source = source.rule_code
 
-    if isinstance(target, offsets.DateOffset):
-        target = target.rule_code
+    if target is None or source is None:
+        return False
+    source = _maybe_coerce_freq(source)
+    target = _maybe_coerce_freq(target)
 
-    target = target.upper()
-    source = source.upper()
     if _is_annual(target):
         if _is_quarterly(source):
             return _quarter_months_conform(_get_rule_month(source),
@@ -1195,14 +1213,11 @@ def is_superperiod(source, target):
     -------
     is_superperiod : boolean
     """
-    if isinstance(source, offsets.DateOffset):
-        source = source.rule_code
-
-    if isinstance(target, offsets.DateOffset):
-        target = target.rule_code
+    if target is None or source is None:
+        return False
+    source = _maybe_coerce_freq(source)
+    target = _maybe_coerce_freq(target)
 
-    target = target.upper()
-    source = source.upper()
     if _is_annual(source):
         if _is_annual(target):
             return _get_rule_month(source) == _get_rule_month(target)

pandas/tseries/resample.py

@@ -595,6 +595,14 @@ def _downsample(self, how, **kwargs):
 
         return self._wrap_result(result)
 
+    def _adjust_binner_for_upsample(self, binner):
+        """ adjust our binner when upsampling """
+        if self.closed == 'right':
+            binner = binner[1:]
+        else:
+            binner = binner[:-1]
+        return binner
+
     def _upsample(self, method, limit=None):
         """
         method : string {'backfill', 'bfill', 'pad', 'ffill'}
@@ -614,11 +622,7 @@ def _upsample(self, method, limit=None):
         ax = self.ax
         obj = self._selected_obj
         binner = self.binner
-
-        if self.closed == 'right':
-            res_index = binner[1:]
-        else:
-            res_index = binner[:-1]
+        res_index = self._adjust_binner_for_upsample(binner)
 
         # if we have the same frequency as our axis, then we are equal sampling
         if limit is None and to_offset(ax.inferred_freq) == self.freq:
@@ -764,6 +768,20 @@ class TimedeltaResampler(DatetimeIndexResampler):
     def _get_binner_for_time(self):
         return self.groupby._get_time_delta_bins(self.ax)
 
+    def _adjust_binner_for_upsample(self, binner):
+        """ adjust our binner when upsampling """
+        ax = self.ax
+
+        if is_subperiod(ax.freq, self.freq):
+            # We are actually downsampling
+            # but are in the asfreq path
+            # GH 12926
+            if self.closed == 'right':
+                binner = binner[1:]
+            else:
+                binner = binner[:-1]
+        return binner
+
 
 def resample(obj, kind=None, **kwds):
     """ create a TimeGrouper and return our resampler """
@@ -1004,8 +1022,11 @@ def _get_time_delta_bins(self, ax):
                 data=[], freq=self.freq, name=ax.name)
             return binner, [], labels
 
-        labels = binner = TimedeltaIndex(start=ax[0],
-                                         end=ax[-1],
+        # we need 1 extra bin here to accomodate the self.closed
+        start = ax[0]
+        end = ax[-1]
+        labels = binner = TimedeltaIndex(start=start,
+                                         end=end,
                                          freq=self.freq,
                                          name=ax.name)
 

pandas/tseries/tests/test_frequencies.py

@@ -670,6 +670,15 @@ def test_legacy_offset_warnings(self):
 
 
 def test_is_superperiod_subperiod():
+
+    # input validation
+    assert not (frequencies.is_superperiod(offsets.YearEnd(), None))
+    assert not (frequencies.is_subperiod(offsets.MonthEnd(), None))
+    assert not (frequencies.is_superperiod(None, offsets.YearEnd()))
+    assert not (frequencies.is_subperiod(None, offsets.MonthEnd()))
+    assert not (frequencies.is_superperiod(None, None))
+    assert not (frequencies.is_subperiod(None, None))
+
     assert (frequencies.is_superperiod(offsets.YearEnd(), offsets.MonthEnd()))
     assert (frequencies.is_subperiod(offsets.MonthEnd(), offsets.YearEnd()))
 

pandas/tseries/tests/test_resample.py

@@ -21,6 +21,7 @@
 from pandas.tseries.period import period_range, PeriodIndex, Period
 from pandas.tseries.resample import (DatetimeIndex, TimeGrouper,
                                      DatetimeIndexResampler)
+from pandas.tseries.frequencies import to_offset
 from pandas.tseries.tdi import timedelta_range
 from pandas.util.testing import (assert_series_equal, assert_almost_equal,
                                  assert_frame_equal)
@@ -35,6 +36,16 @@
 resample_methods = downsample_methods + upsample_methods + series_methods
 
 
+def _simple_ts(start, end, freq='D'):
+    rng = date_range(start, end, freq=freq)
+    return Series(np.random.randn(len(rng)), index=rng)
+
+
+def _simple_pts(start, end, freq='D'):
+    rng = period_range(start, end, freq=freq)
+    return Series(np.random.randn(len(rng)), index=rng)
+
+
 class TestResampleAPI(tm.TestCase):
     _multiprocess_can_split_ = True
 
@@ -566,15 +577,63 @@ def test_agg_consistency(self):
         assert_frame_equal(result, expected)
 
 
-class TestResample(tm.TestCase):
+class Base(object):
+    """
+    base class for resampling testing, calling
+    .create_series() generates a series of each index type
+    """
+    def create_index(self, *args, **kwargs):
+        """ return the _index_factory created using the args, kwargs """
+        factory = self._index_factory()
+        return factory(*args, **kwargs)
+
+    def test_asfreq_downsample(self):
+        s = self.create_series()
+
+        result = s.resample('2D').asfreq()
+        expected = s.reindex(s.index.take(np.arange(0, len(s.index), 2)))
+        expected.index.freq = to_offset('2D')
+        assert_series_equal(result, expected)
+
+        frame = s.to_frame('value')
+        result = frame.resample('2D').asfreq()
+        expected = frame.reindex(
+            frame.index.take(np.arange(0, len(frame.index), 2)))
+        expected.index.freq = to_offset('2D')
+        assert_frame_equal(result, expected)
+
+    def test_asfreq_upsample(self):
+        s = self.create_series()
+
+        result = s.resample('1H').asfreq()
+        new_index = self.create_index(s.index[0], s.index[-1], freq='1H')
+        expected = s.reindex(new_index)
+        assert_series_equal(result, expected)
+
+        frame = s.to_frame('value')
+        result = frame.resample('1H').asfreq()
+        new_index = self.create_index(frame.index[0],
+                                      frame.index[-1], freq='1H')
+        expected = frame.reindex(new_index)
+        assert_frame_equal(result, expected)
+
+
+class TestDatetimeIndex(Base, tm.TestCase):
     _multiprocess_can_split_ = True
+    _index_factory = lambda x: date_range
 
     def setUp(self):
         dti = DatetimeIndex(start=datetime(2005, 1, 1),
                             end=datetime(2005, 1, 10), freq='Min')
 
         self.series = Series(np.random.rand(len(dti)), dti)
 
+    def create_series(self):
+        i = date_range(datetime(2005, 1, 1),
+                       datetime(2005, 1, 10), freq='D')
+
+        return Series(np.arange(len(i)), index=i, name='dti')
+
     def test_custom_grouper(self):
 
         dti = DatetimeIndex(freq='Min', start=datetime(2005, 1, 1),
@@ -1798,18 +1857,61 @@ def test_resmaple_dst_anchor(self):
             'D Frequency')
 
 
-def _simple_ts(start, end, freq='D'):
-    rng = date_range(start, end, freq=freq)
-    return Series(np.random.randn(len(rng)), index=rng)
+class TestPeriodIndex(Base, tm.TestCase):
+    _multiprocess_can_split_ = True
+    _index_factory = lambda x: period_range
 
+    def create_series(self):
+        i = period_range(datetime(2005, 1, 1),
+                         datetime(2005, 1, 10), freq='D')
 
-def _simple_pts(start, end, freq='D'):
-    rng = period_range(start, end, freq=freq)
-    return Series(np.random.randn(len(rng)), index=rng)
+        return Series(np.arange(len(i)), index=i, name='pi')
 
+    def test_asfreq_downsample(self):
 
-class TestResamplePeriodIndex(tm.TestCase):
-    _multiprocess_can_split_ = True
+        # series
+        s = self.create_series()
+        expected = s.reindex(s.index.take(np.arange(0, len(s.index), 2)))
+        expected.index = expected.index.to_timestamp()
+        expected.index.freq = to_offset('2D')
+
+        # this is a bug, this *should* return a PeriodIndex
+        # directly
+        # GH 12884
+        result = s.resample('2D').asfreq()
+        assert_series_equal(result, expected)
+
+        # frame
+        frame = s.to_frame('value')
+        expected = frame.reindex(
+            frame.index.take(np.arange(0, len(frame.index), 2)))
+        expected.index = expected.index.to_timestamp()
+        expected.index.freq = to_offset('2D')
+        result = frame.resample('2D').asfreq()
+        assert_frame_equal(result, expected)
+
+    def test_asfreq_upsample(self):
+
+        # this is a bug, this *should* return a PeriodIndex
+        # directly
+        # GH 12884
+        s = self.create_series()
+        new_index = date_range(s.index[0].to_timestamp(how='start'),
+                               (s.index[-1] + 1).to_timestamp(how='start'),
+                               freq='1H',
+                               closed='left')
+        expected = s.to_timestamp().reindex(new_index).to_period()
+        result = s.resample('1H').asfreq()
+        assert_series_equal(result, expected)
+
+        frame = s.to_frame('value')
+        new_index = date_range(frame.index[0].to_timestamp(how='start'),
+                               (frame.index[-1] + 1).to_timestamp(how='start'),
+                               freq='1H',
+                               closed='left')
+        expected = frame.to_timestamp().reindex(new_index).to_period()
+        result = frame.resample('1H').asfreq()
+        assert_frame_equal(result, expected)
 
     def test_annual_upsample_D_s_f(self):
         self._check_annual_upsample_cases('D', 'start', 'ffill')
@@ -2336,6 +2438,29 @@ def test_evenly_divisible_with_no_extra_bins(self):
         assert_frame_equal(result, expected)
 
 
+class TestTimedeltaIndex(Base, tm.TestCase):
+    _multiprocess_can_split_ = True
+    _index_factory = lambda x: timedelta_range
+
+    def create_series(self):
+        i = timedelta_range('1 day',
+                            '10 day', freq='D')
+
+        return Series(np.arange(len(i)), index=i, name='tdi')
+
+    def test_asfreq_bug(self):
+
+        import datetime as dt
+        df = DataFrame(data=[1, 3],
+                       index=[dt.timedelta(), dt.timedelta(minutes=3)])
+        result = df.resample('1T').asfreq()
+        expected = DataFrame(data=[1, np.nan, np.nan, 3],
+                             index=timedelta_range('0 day',
+                                                   periods=4,
+                                                   freq='1T'))
+        assert_frame_equal(result, expected)
+
+
 class TestTimeGrouper(tm.TestCase):
     def setUp(self):
         self.ts = Series(np.random.randn(1000),