Fix TimedeltaIndex +/- offset array

doc/source/whatsnew/v0.23.0.txt

@@ -308,7 +308,7 @@ Conversion
 - Bug in :class:`WeekOfMonth` and class:`Week` where addition and subtraction did not roll correctly (:issue:`18510`,:issue:`18672`,:issue:`18864`)
 - Bug in :meth:`DatetimeIndex.astype` when converting between timezone aware dtypes, and converting from timezone aware to naive (:issue:`18951`)
 - Bug in :class:`FY5253` where ``datetime`` addition and subtraction incremented incorrectly for dates on the year-end but not normalized to midnight (:issue:`18854`)
-- Bug in :class:`DatetimeIndex` where adding or subtracting an array-like of ``DateOffset`` objects either raised (``np.array``, ``pd.Index``) or broadcast incorrectly (``pd.Series``) (:issue:`18849`)
+- Bug in :class:`DatetimeIndex` and :class:`TimedeltaIndex` where adding or subtracting an array-like of ``DateOffset`` objects either raised (``np.array``, ``pd.Index``) or broadcast incorrectly (``pd.Series``) (:issue:`18849`)
 - Bug in :class:`Series` floor-division where operating on a scalar ``timedelta`` raises an exception (:issue:`18846`)
 - Bug in :class:`FY5253Quarter`, :class:`LastWeekOfMonth` where rollback and rollforward behavior was inconsistent with addition and subtraction behavior (:issue:`18854`)
 - Bug in :class:`Index` constructor with ``dtype=CategoricalDtype(...)`` where ``categories`` and ``ordered`` are not maintained (issue:`19032`)

pandas/core/indexes/timedeltas.py

@@ -1,6 +1,8 @@
 """ implement the TimedeltaIndex """
 
 from datetime import timedelta
+import warnings
+
 import numpy as np
 from pandas.core.dtypes.common import (
     _TD_DTYPE,
@@ -364,8 +366,8 @@ def _add_delta(self, delta):
             # update name when delta is index
             name = com._maybe_match_name(self, delta)
         else:
-            raise ValueError("cannot add the type {0} to a TimedeltaIndex"
-                             .format(type(delta)))
+            raise TypeError("cannot add the type {0} to a TimedeltaIndex"
+                            .format(type(delta)))
 
         result = TimedeltaIndex(new_values, freq='infer', name=name)
         return result
@@ -411,6 +413,47 @@ def _sub_datelike(self, other):
             raise TypeError("cannot subtract a datelike from a TimedeltaIndex")
         return DatetimeIndex(result, name=self.name, copy=False)
 
+    def _add_offset_array(self, other):
+        # Array/Index of DateOffset objects
+        try:
+            # TimedeltaIndex can only operate with a subset of DateOffset
+            # subclasses.  Incompatible classes will raise AttributeError,
+            # which we re-raise as TypeError
+            if isinstance(other, ABCSeries):
+                return NotImplemented
+            elif len(other) == 1:
+                return self + other[0]
+            else:
+                from pandas.errors import PerformanceWarning
+                warnings.warn("Adding/subtracting array of DateOffsets to "
+                              "{} not vectorized".format(type(self)),
+                              PerformanceWarning)
+                return self.astype('O') + np.array(other)
+                # TODO: This works for __add__ but loses dtype in __sub__
+        except AttributeError:
+            raise TypeError("Cannot add non-tick DateOffset to TimedeltaIndex")
+
+    def _sub_offset_array(self, other):
+        # Array/Index of DateOffset objects
+        try:
+            # TimedeltaIndex can only operate with a subset of DateOffset
+            # subclasses.  Incompatible classes will raise AttributeError,
+            # which we re-raise as TypeError
+            if isinstance(other, ABCSeries):
+                return NotImplemented
+            elif len(other) == 1:
+                return self - other[0]
+            else:
+                from pandas.errors import PerformanceWarning
+                warnings.warn("Adding/subtracting array of DateOffsets to "
+                              "{} not vectorized".format(type(self)),
+                              PerformanceWarning)
+                res_values = self.astype('O').values - np.array(other)
+                return self.__class__(res_values, freq='infer')
+        except AttributeError:
+            raise TypeError("Cannot subtrack non-tick DateOffset from"
+                            " TimedeltaIndex")
+
     def _format_native_types(self, na_rep=u('NaT'),
                              date_format=None, **kwargs):
         from pandas.io.formats.format import Timedelta64Formatter

pandas/tests/indexes/timedeltas/test_arithmetic.py

@@ -10,6 +10,7 @@
                     to_timedelta, timedelta_range, date_range,
                     Series,
                     Timestamp, Timedelta)
+from pandas.errors import PerformanceWarning
 
 
 @pytest.fixture(params=[pd.offsets.Hour(2), timedelta(hours=2),
@@ -28,23 +29,98 @@ def freq(request):
 class TestTimedeltaIndexArithmetic(object):
     _holder = TimedeltaIndex
 
-    @pytest.mark.xfail(reason='GH#18824 ufunc add cannot use operands...')
-    def test_tdi_with_offset_array(self):
+    @pytest.mark.parametrize('box', [np.array, pd.Index])
+    def test_tdi_add_offset_array(self, box):
         # GH#18849
-        tdi = pd.TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
-        offs = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
-        expected = pd.TimedeltaIndex(['1 days 01:00:00', '3 days 04:02:00'])
+        tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
+        other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
 
-        res = tdi + offs
+        expected = TimedeltaIndex([tdi[n] + other[n] for n in range(len(tdi))],
+                                  name=tdi.name, freq='infer')
+
+        with tm.assert_produces_warning(PerformanceWarning):
+            res = tdi + other
         tm.assert_index_equal(res, expected)
 
-        res2 = offs + tdi
+        with tm.assert_produces_warning(PerformanceWarning):
+            res2 = other + tdi
         tm.assert_index_equal(res2, expected)
 
-        anchored = np.array([pd.offsets.QuarterEnd(),
-                             pd.offsets.Week(weekday=2)])
+        anchored = box([pd.offsets.QuarterEnd(),
+                        pd.offsets.Week(weekday=2)])
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                tdi + anchored
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                anchored + tdi
+
+    @pytest.mark.parametrize('box', [np.array, pd.Index])
+    def test_tdi_sub_offset_array(self, box):
+        # GH#18824
+        tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
+        other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
+
+        expected = TimedeltaIndex([tdi[n] - other[n] for n in range(len(tdi))],
+                                  name=tdi.name, freq='infer')
+
+        with tm.assert_produces_warning(PerformanceWarning):
+            res = tdi - other
+        tm.assert_index_equal(res, expected)
+
+        anchored = box([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                tdi - anchored
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                anchored - tdi
+
+    @pytest.mark.parametrize('names', [(None, None, None),
+                                       ('foo', 'bar', None),
+                                       ('foo', 'foo', 'foo')])
+    def test_tdi_with_offset_series(self, names):
+        # GH#18849
+        tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'],
+                             name=names[0])
+        other = Series([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)],
+                       name=names[1])
+
+        expected_add = Series([tdi[n] + other[n] for n in range(len(tdi))],
+                              name=names[2])
+
+        with tm.assert_produces_warning(PerformanceWarning):
+            res = tdi + other
+        tm.assert_series_equal(res, expected_add)
+
+        with tm.assert_produces_warning(PerformanceWarning):
+            res2 = other + tdi
+        tm.assert_series_equal(res2, expected_add)
+
+        expected_sub = Series([tdi[n] - other[n] for n in range(len(tdi))],
+                              name=names[2])
+
+        with tm.assert_produces_warning(PerformanceWarning):
+            res3 = tdi - other
+        tm.assert_series_equal(res3, expected_sub)
+
+        anchored = Series([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)],
+                          name=names[1])
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                anchored + tdi
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                tdi + anchored
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                anchored + tdi
+        with pytest.raises(TypeError):
+            with tm.assert_produces_warning(PerformanceWarning):
+                tdi - anchored
         with pytest.raises(TypeError):
-            tdi + anchored
+            with tm.assert_produces_warning(PerformanceWarning):
+                anchored - tdi
 
     # TODO: Split by ops, better name
     def test_numeric_compat(self):