BUG: Series ops with object dtype may incorrectly fail

closes #13043
closes #13072

doc/source/whatsnew/v0.18.2.txt

@@ -128,8 +128,22 @@ Bug Fixes
 
 
 
+- Bug in ``Series`` arithmetic raises ``TypeError`` if it contains datetime-like as ``object`` dtype (:issue:`13043`)
+
 
 
 - Bug in ``NaT`` - ``Period`` raises ``AttributeError`` (:issue:`13071`)
 - Bug in ``Period`` addition raises ``TypeError`` if ``Period`` is on right hand side (:issue:`13069`)
 - Bug in ``pd.set_eng_float_format()`` that would prevent NaN's from formatting (:issue:`11981`)
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pandas/core/ops.py

@@ -19,6 +19,7 @@
 from pandas.tslib import iNaT
 from pandas.compat import bind_method
 import pandas.core.missing as missing
+import pandas.algos as _algos
 import pandas.core.algorithms as algos
 from pandas.core.common import (is_list_like, notnull, isnull,
                                 _values_from_object, _maybe_match_name,
@@ -600,6 +601,21 @@ def na_op(x, y):
         result = missing.fill_zeros(result, x, y, name, fill_zeros)
         return result
 
+    def safe_na_op(lvalues, rvalues):
+        try:
+            return na_op(lvalues, rvalues)
+        except Exception:
+            if isinstance(rvalues, ABCSeries):
+                if is_object_dtype(rvalues):
+                    # if dtype is object, try elementwise op
+                    return _algos.arrmap_object(rvalues,
+                                                lambda x: op(lvalues, x))
+            else:
+                if is_object_dtype(lvalues):
+                    return _algos.arrmap_object(lvalues,
+                                                lambda x: op(x, rvalues))
+            raise
+
     def wrapper(left, right, name=name, na_op=na_op):
 
         if isinstance(right, pd.DataFrame):
@@ -638,17 +654,17 @@ def wrapper(left, right, name=name, na_op=na_op):
                 if ridx is not None:
                     rvalues = algos.take_1d(rvalues, ridx)
 
-            arr = na_op(lvalues, rvalues)
-
-            return left._constructor(wrap_results(arr), index=index,
+            result = wrap_results(safe_na_op(lvalues, rvalues))
+            return left._constructor(result, index=index,
                                      name=name, dtype=dtype)
         else:
             # scalars
             if (hasattr(lvalues, 'values') and
                     not isinstance(lvalues, pd.DatetimeIndex)):
                 lvalues = lvalues.values
 
-            return left._constructor(wrap_results(na_op(lvalues, rvalues)),
+            result = wrap_results(safe_na_op(lvalues, rvalues))
+            return left._constructor(result,
                                      index=left.index, name=left.name,
                                      dtype=dtype)
 

pandas/tseries/tests/test_period.py

@@ -4151,6 +4151,68 @@ def test_intercept_astype_object(self):
         result = df.values.squeeze()
         self.assertTrue((result[:, 0] == expected.values).all())
 
+    def test_ops_series_timedelta(self):
+        # GH 13043
+        s = pd.Series([pd.Period('2015-01-01', freq='D'),
+                       pd.Period('2015-01-02', freq='D')], name='xxx')
+        self.assertEqual(s.dtype, object)
+
+        exp = pd.Series([pd.Period('2015-01-02', freq='D'),
+                         pd.Period('2015-01-03', freq='D')], name='xxx')
+        tm.assert_series_equal(s + pd.Timedelta('1 days'), exp)
+        tm.assert_series_equal(pd.Timedelta('1 days') + s, exp)
+
+        tm.assert_series_equal(s + pd.tseries.offsets.Day(), exp)
+        tm.assert_series_equal(pd.tseries.offsets.Day() + s, exp)
+
+    def test_ops_series_period(self):
+        # GH 13043
+        s = pd.Series([pd.Period('2015-01-01', freq='D'),
+                       pd.Period('2015-01-02', freq='D')], name='xxx')
+        self.assertEqual(s.dtype, object)
+
+        p = pd.Period('2015-01-10', freq='D')
+        # dtype will be object because of original dtype
+        exp = pd.Series([9, 8], name='xxx', dtype=object)
+        tm.assert_series_equal(p - s, exp)
+        tm.assert_series_equal(s - p, -exp)
+
+        s2 = pd.Series([pd.Period('2015-01-05', freq='D'),
+                        pd.Period('2015-01-04', freq='D')], name='xxx')
+        self.assertEqual(s2.dtype, object)
+
+        exp = pd.Series([4, 2], name='xxx', dtype=object)
+        tm.assert_series_equal(s2 - s, exp)
+        tm.assert_series_equal(s - s2, -exp)
+
+    def test_ops_frame_period(self):
+        # GH 13043
+        df = pd.DataFrame({'A': [pd.Period('2015-01', freq='M'),
+                                 pd.Period('2015-02', freq='M')],
+                           'B': [pd.Period('2014-01', freq='M'),
+                                 pd.Period('2014-02', freq='M')]})
+        self.assertEqual(df['A'].dtype, object)
+        self.assertEqual(df['B'].dtype, object)
+
+        p = pd.Period('2015-03', freq='M')
+        # dtype will be object because of original dtype
+        exp = pd.DataFrame({'A': np.array([2, 1], dtype=object),
+                            'B': np.array([14, 13], dtype=object)})
+        tm.assert_frame_equal(p - df, exp)
+        tm.assert_frame_equal(df - p, -exp)
+
+        df2 = pd.DataFrame({'A': [pd.Period('2015-05', freq='M'),
+                                  pd.Period('2015-06', freq='M')],
+                            'B': [pd.Period('2015-05', freq='M'),
+                                  pd.Period('2015-06', freq='M')]})
+        self.assertEqual(df2['A'].dtype, object)
+        self.assertEqual(df2['B'].dtype, object)
+
+        exp = pd.DataFrame({'A': np.array([4, 4], dtype=object),
+                            'B': np.array([16, 16], dtype=object)})
+        tm.assert_frame_equal(df2 - df, exp)
+        tm.assert_frame_equal(df - df2, -exp)
+
 
 if __name__ == '__main__':
     import nose

pandas/tseries/tests/test_timedeltas.py

@@ -413,6 +413,38 @@ def test_ops_series(self):
         tm.assert_series_equal(expected, td * other)
         tm.assert_series_equal(expected, other * td)
 
+    def test_ops_series_object(self):
+        # GH 13043
+        s = pd.Series([pd.Timestamp('2015-01-01', tz='US/Eastern'),
+                       pd.Timestamp('2015-01-01', tz='Asia/Tokyo')],
+                      name='xxx')
+        self.assertEqual(s.dtype, object)
+
+        exp = pd.Series([pd.Timestamp('2015-01-02', tz='US/Eastern'),
+                         pd.Timestamp('2015-01-02', tz='Asia/Tokyo')],
+                        name='xxx')
+        tm.assert_series_equal(s + pd.Timedelta('1 days'), exp)
+        tm.assert_series_equal(pd.Timedelta('1 days') + s, exp)
+
+        # object series & object series
+        s2 = pd.Series([pd.Timestamp('2015-01-03', tz='US/Eastern'),
+                        pd.Timestamp('2015-01-05', tz='Asia/Tokyo')],
+                       name='xxx')
+        self.assertEqual(s2.dtype, object)
+        exp = pd.Series([pd.Timedelta('2 days'), pd.Timedelta('4 days')],
+                        name='xxx')
+        tm.assert_series_equal(s2 - s, exp)
+        tm.assert_series_equal(s - s2, -exp)
+
+        s = pd.Series([pd.Timedelta('01:00:00'), pd.Timedelta('02:00:00')],
+                      name='xxx', dtype=object)
+        self.assertEqual(s.dtype, object)
+
+        exp = pd.Series([pd.Timedelta('01:30:00'), pd.Timedelta('02:30:00')],
+                        name='xxx')
+        tm.assert_series_equal(s + pd.Timedelta('00:30:00'), exp)
+        tm.assert_series_equal(pd.Timedelta('00:30:00') + s, exp)
+
     def test_compare_timedelta_series(self):
         # regresssion test for GH5963
         s = pd.Series([timedelta(days=1), timedelta(days=2)])