Fix pandas-dev#20744 . loffset ignored in upsample

Author: johncant

doc/source/whatsnew/v0.23.0.txt

@@ -1200,6 +1200,7 @@ Groupby/Resample/Rolling
 - Bug in :func:`DataFrameGroupBy.cumsum` and :func:`DataFrameGroupBy.cumprod` when ``skipna`` was passed (:issue:`19806`)
 - Bug in :func:`DataFrame.resample` that dropped timezone information (:issue:`13238`)
 - Bug in :func:`DataFrame.groupby` where transformations using ``np.all`` and ``np.any`` were raising a ``ValueError`` (:issue:`20653`)
+- Bug in :func:`DatetimeIndexResampler._upsample` where ``loffset`` was being ignored (:issue:`20744`)
 
 Sparse
 ^^^^^^

pandas/core/resample.py

@@ -967,6 +967,7 @@ def _upsample(self, method, limit=None, fill_value=None):
             result = obj.reindex(res_index, method=method,
                                  limit=limit, fill_value=fill_value)
 
+        result = self._apply_loffset(result)
         return self._wrap_result(result)
 
     def _wrap_result(self, result):

pandas/tests/test_resample.py

@@ -1153,22 +1153,33 @@ def test_resample_loffset(self):
         rng = date_range('1/1/2000 00:00:00', '1/1/2000 00:13:00', freq='min')
         s = Series(np.random.randn(14), index=rng)
 
-        result = s.resample('5min', closed='right', label='right',
-                            loffset=timedelta(minutes=1)).mean()
         idx = date_range('1/1/2000', periods=4, freq='5min')
-        expected = Series([s[0], s[1:6].mean(), s[6:11].mean(), s[11:].mean()],
-                          index=idx + timedelta(minutes=1))
-        assert_series_equal(result, expected)
-
-        expected = s.resample(
+        expected_downsample = Series([s[0], s[1:6].mean(),
+                                      s[6:11].mean(), s[11:].mean()],
+                                     index=idx + timedelta(minutes=1))
+        # GH 20744
+        expected_upsample = Series([s[0], s[5], s[10], s[-1]],
+                                   index=idx + timedelta(minutes=1))
+
+        # loffset should work for upsample and downsample
+        result_downsample = s.resample('5min', closed='right', label='right',
+                                       loffset=timedelta(minutes=1)).mean()
+        result_upsample = s.resample('5min', closed='right', label='right',
+                                     loffset=timedelta(minutes=1)).ffill()
+
+        assert_series_equal(result_downsample, expected_downsample)
+        assert_series_equal(result_upsample, expected_upsample)
+
+        # loffset should allow various types
+        result = s.resample(
             '5min', closed='right', label='right',
             loffset='1min').mean()
-        assert_series_equal(result, expected)
+        assert_series_equal(result, expected_downsample)
 
-        expected = s.resample(
+        result = s.resample(
             '5min', closed='right', label='right',
             loffset=Minute(1)).mean()
-        assert_series_equal(result, expected)
+        assert_series_equal(result, expected_downsample)
 
         assert result.index.freq == Minute(5)