BUG: DatetimeIndex + arraylike of DateOffsets

doc/source/whatsnew/v0.22.0.txt

@@ -354,3 +354,4 @@ Other
 
 - Improved error message when attempting to use a Python keyword as an identifier in a ``numexpr`` backed query (:issue:`18221`)
 - Bug in :class:`Timestamp` where comparison with an array of ``Timestamp`` objects would result in a ``RecursionError`` (:issue:`15183`)
+- 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:`18224`)

pandas/core/indexes/datetimelike.py

@@ -13,7 +13,7 @@
 from pandas.core.dtypes.common import (
     is_integer, is_float,
     is_bool_dtype, _ensure_int64,
-    is_scalar, is_dtype_equal,
+    is_scalar, is_dtype_equal, is_offsetlike,
     is_list_like, is_timedelta64_dtype)
 from pandas.core.dtypes.generic import (
     ABCIndex, ABCSeries,
@@ -650,6 +650,7 @@ def _add_datetimelike_methods(cls):
         def __add__(self, other):
             from pandas.core.index import Index
             from pandas.core.indexes.timedeltas import TimedeltaIndex
+            from pandas.core.indexes.datetimes import DatetimeIndex
             from pandas.tseries.offsets import DateOffset
             if is_timedelta64_dtype(other):
                 return self._add_delta(other)
@@ -662,7 +663,21 @@ def __add__(self, other):
                 return self._add_delta(other)
             elif is_integer(other):
                 return self.shift(other)
-            elif isinstance(other, (Index, datetime, np.datetime64)):
+            elif isinstance(other, (datetime, np.datetime64)):
+                return self._add_datelike(other)
+            elif (isinstance(self, DatetimeIndex) and is_offsetlike(other) and
+                  not isinstance(other, ABCSeries)):
+                # Array of DateOffset objects
+                if 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)
+                    # FIXME: This works for __add__ but loses dtype in __sub__
+            elif isinstance(other, Index):
                 return self._add_datelike(other)
             else:  # pragma: no cover
                 return NotImplemented
@@ -683,10 +698,6 @@ def __sub__(self, other):
                 return self._add_delta(-other)
             elif isinstance(other, DatetimeIndex):
                 return self._sub_datelike(other)
-            elif isinstance(other, Index):
-                raise TypeError("cannot subtract {typ1} and {typ2}"
-                                .format(typ1=type(self).__name__,
-                                        typ2=type(other).__name__))
             elif isinstance(other, (DateOffset, timedelta)):
                 return self._add_delta(-other)
             elif is_integer(other):
@@ -695,6 +706,23 @@ def __sub__(self, other):
                 return self._sub_datelike(other)
             elif isinstance(other, Period):
                 return self._sub_period(other)
+            elif (isinstance(self, DatetimeIndex) and is_offsetlike(other) and
+                  not isinstance(other, ABCSeries)):
+                # Array of DateOffset objects
+                if 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')
+            elif isinstance(other, Index):
+                raise TypeError("cannot subtract {typ1} and {typ2}"
+                                .format(typ1=type(self).__name__,
+                                        typ2=type(other).__name__))
+
             else:  # pragma: no cover
                 return NotImplemented
         cls.__sub__ = __sub__

pandas/tests/indexes/datetimes/test_arithmetic.py

@@ -363,6 +363,46 @@ def test_datetimeindex_sub_timestamp_overflow(self):
             with pytest.raises(OverflowError):
                 dtimin - variant
 
+    @pytest.mark.parametrize('box', [np.array, pd.Index])
+    def test_dti_add_offset_array(self, tz, box):
+        dti = pd.date_range('2017-01-01', periods=2, tz=tz)
+        # TODO: check that `name` propogates correctly
+        other = box([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
+        res = dti + other
+        expected = DatetimeIndex([dti[n] + other[n] for n in range(len(dti))],
+                                 name=dti.name, freq='infer')
+        tm.assert_index_equal(res, expected)
+
+        res2 = other + dti
+        tm.assert_index_equal(res2, expected)
+
+    @pytest.mark.parametrize('box', [np.array, pd.Index])
+    def test_dti_sub_offset_array(self, tz, box):
+        dti = pd.date_range('2017-01-01', periods=2, tz=tz)
+        other = box([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
+        res = dti - other
+        expected = DatetimeIndex([dti[n] - other[n] for n in range(len(dti))],
+                                 name=dti.name, freq='infer')
+        tm.assert_index_equal(res, expected)
+
+    def test_dti_with_offset_series(self, tz):
+        dti = pd.date_range('2017-01-01', periods=2, tz=tz)
+        other = pd.Series([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)],
+                          name='foo')
+
+        expected_add = pd.Series([dti[n] + other[n] for n in range(len(dti))],
+                                 name='foo')
+        res = dti + other
+        tm.assert_series_equal(res, expected_add)
+        res2 = other + dti
+        tm.assert_series_equal(res2, expected_add)
+
+        expected_sub = pd.Series([dti[n] - other[n] for n in range(len(dti))],
+                                 name='foo')
+
+        res3 = dti - other
+        tm.assert_series_equal(res3, expected_sub)
+
 
 # GH 10699
 @pytest.mark.parametrize('klass,assert_func', zip([Series, DatetimeIndex],