ENH: added neg/inv operators to series

 fixed setitem with boolean indexer to accept an object needing alignment (e.g. a partial series)

Author: jreback

pandas/core/series.py

@@ -616,6 +616,9 @@ def where(self, cond, other=nan, inplace=False):
  if len(cond) != len(self):
  raise ValueError('condition must have same length as series')
 
+ if not 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)
@@ -672,10 +675,11 @@ def __setitem__(self, key, value):
  # Could not hash item
 
  if _is_bool_indexer(key):
+ #import pdb; pdb.set_
  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
@@ -707,13 +711,7 @@ def _set_with(self, key, value):
  else:
  return self._set_values(key, value)
  elif key_type == 'boolean':
-
- # scalar setting with boolean key
- if np.isscalar(value):
  self._set_values(key, value)
- # we have a key mask and a value that is np.array like
- else:
- np.putmask(self.values, key, value)
  else:
  self._set_labels(key, value)
 
@@ -758,6 +756,12 @@ 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 not result.dtype == np.bool_:
+ result = result.astype(np.bool_)
+
  return result
 
  def __setslice__(self, i, j, value):
@@ -1115,6 +1119,15 @@ 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

@@ -1047,11 +1047,19 @@ def test_ix_setitem(self):
  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()
 
@@ -1525,6 +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):