BUG: loffset argument not applied for resample().count() on timeseries

closes #12725

The code to do this already existed in the `_downsample` method, which is
called when using functions like `mean`. `max`, etc., but there was
nothing in the `_groupby_and_aggregate` method used for `count` and
`size`. If we pull out the offset code from the `_downsample` method
into a separate method, we can reuse it without duplicating it.

Author: onesandzeroes <[email protected]>

Closes #12757 from onesandzeroes/loffset-count and squashes the following commits:

627429a [onesandzeroes] Add to release notes
fa021bf [onesandzeroes] pep8 style fixes
0c0ca34 [onesandzeroes] Update comment re: issue number
dc79369 [onesandzeroes] Apply loffset when aggregating, e.g. using count()
15aadb9 [onesandzeroes] Extract loffset handling into a general method
70e9765 [onesandzeroes] Add test case for loffset when using count() method

Author: onesandzeroes

doc/source/whatsnew/v0.18.1.txt

@@ -169,3 +169,4 @@ Bug Fixes
 - Bug in ``pivot_table`` when ``margins=True`` and ``dropna=True`` where nulls still contributed to margin count (:issue:`12577`)
 - Bug in ``Series.name`` when ``name`` attribute can be a hashable type (:issue:`12610`)
 - Bug in ``.describe()`` resets categorical columns information (:issue:`11558`)
+- Bug where ``loffset`` argument was not applied when calling ``resample().count()`` on a timeseries (:issue:`12725`)

pandas/tseries/resample.py

@@ -372,8 +372,26 @@ def _groupby_and_aggregate(self, grouper, how, *args, **kwargs):
             # try to evaluate
             result = grouped.apply(how, *args, **kwargs)
 
+        result = self._apply_loffset(result)
+
         return self._wrap_result(result)
 
+    def _apply_loffset(self, result):
+        """if loffset if set, offset the result index"""
+        loffset = self.loffset
+        if isinstance(loffset, compat.string_types):
+            loffset = to_offset(self.loffset)
+
+        needs_offset = (
+            isinstance(loffset, (DateOffset, timedelta)) and
+            isinstance(result.index, DatetimeIndex) and
+            len(result.index) > 0
+        )
+        if needs_offset:
+            result.index = result.index + loffset
+
+        return result
+
     def _wrap_result(self, result):
         """ potentially wrap any results """
         return result
@@ -572,14 +590,7 @@ def _downsample(self, how, **kwargs):
         result = obj.groupby(
             self.grouper, axis=self.axis).aggregate(how, **kwargs)
 
-        loffset = self.loffset
-        if isinstance(loffset, compat.string_types):
-            loffset = to_offset(self.loffset)
-
-        if isinstance(loffset, (DateOffset, timedelta)) and \
-           isinstance(result.index, DatetimeIndex) and \
-           len(result.index) > 0:
-                result.index = result.index + loffset
+        result = self._apply_loffset(result)
 
         return self._wrap_result(result)
 

pandas/tseries/tests/test_resample.py

@@ -937,6 +937,28 @@ def test_resample_loffset(self):
         expected = ser.resample('w-sun', loffset=-bday).last()
         self.assertEqual(result.index[0] - bday, expected.index[0])
 
+    def test_resample_loffset_count(self):
+        # GH 12725
+        start_time = '1/1/2000 00:00:00'
+        rng = date_range(start_time, periods=100, freq='S')
+        ts = Series(np.random.randn(len(rng)), index=rng)
+
+        result = ts.resample('10S', loffset='1s').count()
+
+        expected_index = (
+            date_range(start_time, periods=10, freq='10S') +
+            timedelta(seconds=1)
+        )
+        expected = pd.Series(10, index=expected_index)
+
+        assert_series_equal(result, expected)
+
+        # Same issue should apply to .size() since it goes through
+        #   same code path
+        result = ts.resample('10S', loffset='1s').size()
+
+        assert_series_equal(result, expected)
+
     def test_resample_upsample(self):
         # from daily
         dti = DatetimeIndex(start=datetime(2005, 1, 1),