BUG: binary operator method alignment with integer level (GH9463)

Author: jorisvandenbossche

doc/source/whatsnew/v0.16.0.txt

@@ -228,7 +228,7 @@ Bug Fixes
 
 
 
-
+- Bug in binary operator method (eg ``.mul()``) alignment with integer levels (:issue:`9463`).
 
 
 

pandas/core/generic.py

@@ -3172,30 +3172,25 @@ def _align_series(self, other, join='outer', axis=None, level=None,
 
         else:
 
-            # for join compat if we have an unnamed index, but
-            # are specifying a level join
-            other_index = other.index
-            if level is not None and other.index.name is None:
-                other_index = other_index.set_names([level])
-
             # one has > 1 ndim
             fdata = self._data
             if axis == 0:
                 join_index = self.index
                 lidx, ridx = None, None
-                if not self.index.equals(other_index):
-                    join_index, lidx, ridx = self.index.join(
-                        other_index, how=join, return_indexers=True)
+                if not self.index.equals(other.index):
+                    join_index, lidx, ridx = \
+                        self.index.join(other.index, how=join, level=level,
+                                        return_indexers=True)
 
                 if lidx is not None:
                     fdata = fdata.reindex_indexer(join_index, lidx, axis=1)
 
             elif axis == 1:
                 join_index = self.columns
                 lidx, ridx = None, None
-                if not self.columns.equals(other_index):
+                if not self.columns.equals(other.index):
                     join_index, lidx, ridx = \
-                        self.columns.join(other_index, how=join,
+                        self.columns.join(other.index, how=join, level=level,
                                           return_indexers=True)
 
                 if lidx is not None:

pandas/tests/test_frame.py

@@ -5428,6 +5428,35 @@ def test_binary_ops_align(self):
             expected = pd.concat([ opa(df.loc[idx[:,i],:],v) for i, v in x.iteritems() ]).reindex_like(df).sortlevel()
             assert_frame_equal(result, expected)
 
+        ## GH9463 (alignment level of dataframe with series)
+
+        midx = MultiIndex.from_product([['A', 'B'],['a', 'b']])
+        df = DataFrame(np.ones((2,4), dtype='int64'), columns=midx)
+        s = pd.Series({'a':1, 'b':2})
+
+        df2 = df.copy()
+        df2.columns.names = ['lvl0', 'lvl1']
+        s2 = s.copy()
+        s2.index.name = 'lvl1'
+
+        # different cases of integer/string level names:
+        res1 = df.mul(s, axis=1, level=1)
+        res2 = df.mul(s2, axis=1, level=1)
+        res3 = df2.mul(s, axis=1, level=1)
+        res4 = df2.mul(s2, axis=1, level=1)
+        res5 = df2.mul(s, axis=1, level='lvl1')
+        res6 = df2.mul(s2, axis=1, level='lvl1')
+
+        exp = DataFrame(np.array([[1, 2, 1, 2], [1, 2, 1, 2]], dtype='int64'),
+                        columns=midx)
+
+        for res in [res1, res2]:
+            assert_frame_equal(res, exp)
+
+        exp.columns.names = ['lvl0', 'lvl1']
+        for res in [res3, res4, res5, res6]:
+            assert_frame_equal(res, exp)
+
     def test_arith_mixed(self):
 
         left = DataFrame({'A': ['a', 'b', 'c'],