BUG: series assignment with a boolean indexer

RELEASE.rst

@@ -55,6 +55,7 @@ pandas 0.10.1
   - Add ``logx`` option to DataFrame/Series.plot (GH2327_, #2565)
   - Support reading gzipped data from file-like object
   - ``pivot_table`` aggfunc can be anything used in GroupBy.aggregate (GH2643_)
+  - Add methods ``neg`` and ``inv`` to Series
 
 **Bug fixes**
 
@@ -78,6 +79,7 @@ pandas 0.10.1
   - Exclude non-numeric data from DataFrame.quantile by default (GH2625_)
   - Fix a Cython C int64 boxing issue causing read_csv to return incorrect
     results (GH2599_)
+  - Fix setitem on a Series with a boolean key and a non-scalar as value (GH2686_)
 
 **API Changes**
 
@@ -98,6 +100,7 @@ pandas 0.10.1
 .. _GH2625: https://github.com/pydata/pandas/issues/2625
 .. _GH2643: https://github.com/pydata/pandas/issues/2643
 .. _GH2637: https://github.com/pydata/pandas/issues/2637
+.. _GH2686: https://github.com/pydata/pandas/issues/2686
 
 pandas 0.10.0
 =============

pandas/core/series.py

@@ -604,6 +604,9 @@ def where(self, cond, other=nan, inplace=False):
         if len(cond) != len(self):
             raise ValueError('condition must have same length as series')
 
+        if cond.dtype != np.bool_:
+            cond = cond.astype(np.bool_)
+
         ser = self if inplace else self.copy()
         if not isinstance(other, (list, tuple, np.ndarray)):
             ser._set_with(~cond, other)
@@ -661,9 +664,9 @@ def __setitem__(self, key, value):
 
         if _is_bool_indexer(key):
             key = self._check_bool_indexer(key)
-            key = np.asarray(key, dtype=bool)
-
-        self._set_with(key, value)
+            self.where(~key,value,inplace=True)
+        else:
+            self._set_with(key, value)
 
     def _set_with(self, key, value):
         # other: fancy integer or otherwise
@@ -695,7 +698,7 @@ def _set_with(self, key, value):
                 else:
                     return self._set_values(key, value)
             elif key_type == 'boolean':
-                self._set_values(key, value)
+                    self._set_values(key, value)
             else:
                 self._set_labels(key, value)
 
@@ -740,6 +743,12 @@ def _check_bool_indexer(self, key):
                 raise ValueError('cannot index with vector containing '
                                  'NA / NaN values')
 
+        # coerce to bool type
+        if not hasattr(result, 'shape'):
+            result = np.array(result)
+        if result.dtype != np.bool_:
+            result = result.astype(np.bool_)
+
         return result
 
     def __setslice__(self, i, j, value):
@@ -1097,6 +1106,15 @@ def iteritems(self):
     __le__ = _comp_method(operator.le, '__le__')
     __eq__ = _comp_method(operator.eq, '__eq__')
     __ne__ = _comp_method(operator.ne, '__ne__')
+
+    # inversion
+    def __neg__(self):
+        arr = operator.neg(self.values)
+        return Series(arr, self.index, name=self.name)
+
+    def __invert__(self):
+        arr = operator.inv(self.values)
+        return Series(arr, self.index, name=self.name)
 
     # binary logic
     __or__ = _bool_method(operator.or_, '__or__')

pandas/tests/test_series.py

@@ -1044,6 +1044,22 @@ def test_ix_setitem(self):
         self.assertEquals(self.series[d1], 4)
         self.assertEquals(self.series[d2], 6)
 
+    def test_setitem_boolean(self):
+        mask = self.series > self.series.median()
+
+        # similiar indexed series
+        result = self.series.copy()
+        result[mask] = self.series*2
+        expected = self.series*2
+        assert_series_equal(result[mask], expected[mask])
+
+        # needs alignment
+        result = self.series.copy()
+        result[mask] = (self.series*2)[0:5]
+        expected = (self.series*2)[0:5].reindex_like(self.series)
+        expected[-mask] = self.series[mask]
+        assert_series_equal(result[mask], expected[mask])
+
     def test_ix_setitem_boolean(self):
         mask = self.series > self.series.median()
 
@@ -1517,6 +1533,12 @@ def check(series, other):
         check(self.ts, self.ts[::2])
         check(self.ts, 5)
 
+    def test_neg(self):
+        assert_series_equal(-self.series, -1 * self.series)
+
+    def test_invert(self):
+        assert_series_equal(-(self.series < 0), ~(self.series < 0))
+
     def test_operators(self):
 
         def _check_op(series, other, op, pos_only=False):
@@ -3211,9 +3233,9 @@ def test_interpolate_index_values(self):
         expected = s.copy()
         bad = isnull(expected.values)
         good = -bad
-        expected[bad] = np.interp(vals[bad], vals[good], s.values[good])
+        expected = Series(np.interp(vals[bad], vals[good], s.values[good]), index=s.index[bad])
 
-        assert_series_equal(result, expected)
+        assert_series_equal(result[bad], expected)
 
     def test_weekday(self):
         # Just run the function