Merge pull request #8026 from jreback/series_map

BUG: related to GH5080, get_indexer choking on boolean type promotion (GH8024)

Author: jreback

doc/source/v0.15.0.txt

@@ -217,7 +217,7 @@ Internal Refactoring
 
 In 0.15.0 ``Index`` has internally been refactored to no longer sub-class ``ndarray``
 but instead subclass ``PandasObject``, similarly to the rest of the pandas objects. This change allows very easy sub-classing and creation of new index types. This should be
-a transparent change with only very limited API implications (:issue:`5080`, :issue:`7439`, :issue:`7796`)
+a transparent change with only very limited API implications (:issue:`5080`, :issue:`7439`, :issue:`7796`, :issue:`8024`)
 
 - you may need to unpickle pandas version < 0.15.0 pickles using ``pd.read_pickle`` rather than ``pickle.load``. See :ref:`pickle docs <io.pickle>`
 - when plotting with a ``PeriodIndex``. The ``matplotlib`` internal axes will now be arrays of ``Period`` rather than a ``PeriodIndex``. (this is similar to how a ``DatetimeIndex`` passes arrays of ``datetimes`` now)

pandas/core/index.py

@@ -1506,6 +1506,9 @@ def _possibly_promote(self, other):
         from pandas.tseries.index import DatetimeIndex
         if self.inferred_type == 'date' and isinstance(other, DatetimeIndex):
             return DatetimeIndex(self), other
+        elif self.inferred_type == 'boolean':
+            if self.dtype != 'object':
+                return self.astype('object'), other.astype('object')
         return self, other
 
     def groupby(self, to_groupby):

pandas/tests/test_series.py

@@ -4968,6 +4968,13 @@ def test_map(self):
         result = self.ts.map(lambda x: x * 2)
         self.assert_numpy_array_equal(result, self.ts * 2)
 
+    def test_map_compat(self):
+        # related GH 8024
+        s = Series([True,True,False],index=[1,2,3])
+        result = s.map({ True : 'foo', False : 'bar' })
+        expected = Series(['foo','foo','bar'],index=[1,2,3])
+        assert_series_equal(result,expected)
+
     def test_map_int(self):
         left = Series({'a': 1., 'b': 2., 'c': 3., 'd': 4})
         right = Series({1: 11, 2: 22, 3: 33})