fix raise of TypeError when subtracting timedelta array

closes pandas-dev#21980

doc/source/whatsnew/v0.24.0.txt

@@ -441,7 +441,7 @@ Datetimelike
 Timedelta
 ^^^^^^^^^
 
--
+- Fixed bug where array of timestamp and deltas raised a TypeError: unsupported operand type(s) for -: 'numpy.ndarray' and 'Timedelta' (:issue:`21980`)
 -
 -
 

pandas/_libs/tslibs/timedeltas.pyx

@@ -542,10 +542,15 @@ def _binary_op_method_timedeltalike(op, name):
 
         elif hasattr(other, 'dtype'):
             # nd-array like
-            if other.dtype.kind not in ['m', 'M']:
-                # raise rathering than letting numpy return wrong answer
+            try:
+                if other.dtype.kind in ['m', 'M']:
+                    return op(self.to_timedelta64(), other)
+                elif other.dtype.kind == 'O':
+                    return np.array([op(self, x) for x in other])
+                else:
+                    return NotImplemented
+            except:
                 return NotImplemented
-            return op(self.to_timedelta64(), other)
 
         elif not _validate_ops_compat(other):
             return NotImplemented
@@ -929,7 +934,7 @@ cdef class _Timedelta(timedelta):
     def nanoseconds(self):
         """
         Return the number of nanoseconds (n), where 0 <= n < 1 microsecond.
-       
+
         Returns
         -------
         int

pandas/tests/series/test_timeseries.py

@@ -1012,3 +1012,22 @@ def test_get_level_values_box(self):
         index = MultiIndex(levels=levels, labels=labels)
 
         assert isinstance(index.get_level_values(0)[0], Timestamp)
+
+    def test_diff_sub_timedelta(self):
+        # GH 21980
+        arr = np.array([Timestamp('20130101 9:01'),
+                        Timestamp('20121230 9:02')])
+        exp = np.array([Timestamp('20121231 9:01'),
+                        Timestamp('20121229 9:02')])
+        res = arr - pd.Timedelta('1D')
+        tm.assert_numpy_array_equal(res, exp)
+
+    def test_diff_sub_timedelta_mixed(self):
+        # GH 21980
+        now = pd.Timestamp.now()
+        arr = np.array([now,
+                        pd.Timedelta('1D')])
+        exp = np.array([now - pd.Timedelta('1D'),
+                        pd.Timedelta('0D')])
+        res = arr - pd.Timedelta('1D')
+        tm.assert_numpy_array_equal(res, exp)