fix for BUG: grouping with tz-aware: Values falls after last bin

doc/source/whatsnew/v0.24.1.rst

@@ -66,7 +66,7 @@ Bug Fixes
 **Reshaping**
 
 - Bug in :func:`merge` when merging by index name would sometimes result in an incorrectly numbered index (:issue:`24212`)
-
+Bug in :meth:`DataFrame.groupby`(:class:`pd.Grouper`(freq='1d')) when there is a time change (DST) and grouping frequency is 1d (:issue:`24972`)
 **Other**
 
 -

pandas/core/resample.py

@@ -30,8 +30,7 @@
 from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
 
 from pandas.tseries.frequencies import to_offset
-from pandas.tseries.offsets import (
-    DateOffset, Day, Nano, Tick, delta_to_nanoseconds)
+from pandas.tseries.offsets import DateOffset, Day, Nano, Tick
 
 _shared_docs_kwargs = dict()
 
@@ -1613,20 +1612,20 @@ def _get_timestamp_range_edges(first, last, offset, closed='left', base=0):
     A tuple of length 2, containing the adjusted pd.Timestamp objects.
     """
     if isinstance(offset, Tick):
-        is_day = isinstance(offset, Day)
-        day_nanos = delta_to_nanoseconds(timedelta(1))
-
-        # #1165 and #24127
-        if (is_day and not offset.nanos % day_nanos) or not is_day:
-            first, last = _adjust_dates_anchored(first, last, offset,
-                                                 closed=closed, base=base)
-            if is_day and first.tz is not None:
-                # _adjust_dates_anchored assumes 'D' means 24H, but first/last
-                # might contain a DST transition (23H, 24H, or 25H).
-                # Ensure first/last snap to midnight.
-                first = first.normalize()
-                last = last.normalize()
-            return first, last
+        if isinstance(offset, Day):
+            # _adjust_dates_anchored assumes 'D' means 24H, but first/last
+            # might contain a DST transition (23H, 24H, or 25H).
+            # So "pretend" the dates are naive when adjusting the endpoints
+            tz = first.tz
+            first = first.tz_localize(None)
+            last = last.tz_localize(None)
+
+        first, last = _adjust_dates_anchored(first, last, offset,
+                                             closed=closed, base=base)
+        if isinstance(offset, Day):
+            first = first.tz_localize(tz)
+            last = last.tz_localize(tz)
+        return first, last
 
     else:
         first = first.normalize()

pandas/tests/groupby/test_timegrouper.py

@@ -650,3 +650,17 @@ def test_scalar_call_versus_list_call(self):
         expected = grouped.count()
 
         assert_frame_equal(result, expected)
+
+    def test_groupby_with_dst_time_change(self):
+        # GH 24972
+        index = pd.DatetimeIndex([1478064900001000000, 1480037118776792000],
+                                 tz='UTC').tz_convert('America/Chicago')
+
+        df = pd.DataFrame([1, 2], index=index)
+        result = df.groupby(pd.Grouper(freq='1d')).last()
+        expected_index_values = pd.date_range('2016-11-02', '2016-11-24',
+                                              freq='d', tz='America/Chicago')
+
+        index = pd.DatetimeIndex(expected_index_values)
+        expected = pd.DataFrame([1.0] + ([np.nan] * 21) + [2.0], index=index)
+        assert_frame_equal(result, expected)