BUG: bug in setitem with multi-index and a 0-dim ndarray (GH7218)

Author: jreback

doc/source/release.rst

@@ -522,7 +522,7 @@ Bug Fixes
 - Bug in ``query``/``eval`` where global constants were not looked up correctly
   (:issue:`7178`)
 - Bug in recognizing out-of-bounds positional list indexers with ``iloc`` and a multi-axis tuple indexer (:issue:`7189`)
-- Bug in setitem with a single value, multi-index and integer indices (:issue:`7190`)
+- Bug in setitem with a single value, multi-index and integer indices (:issue:`7190`, :issue:`7218`)
 - Bug in expressions evaluation with reversed ops, showing in series-dataframe ops (:issue:`7198`, :issue:`7192`)
 - Bug in multi-axis indexing with > 2 ndim and a multi-index (:issue:`7199`)
 

pandas/core/indexing.py

@@ -339,7 +339,7 @@ def _setitem_with_indexer(self, indexer, value):
 
                 # require that we are setting the right number of values that
                 # we are indexing
-                if is_list_like(value) and lplane_indexer != len(value):
+                if is_list_like(value) and np.iterable(value) and lplane_indexer != len(value):
 
                     if len(obj[idx]) != len(value):
                         raise ValueError(
@@ -386,7 +386,7 @@ def setter(item, v):
 
             def can_do_equal_len():
                 """ return True if we have an equal len settable """
-                if not len(labels) == 1:
+                if not len(labels) == 1 or not np.iterable(value):
                     return False
 
                 l = len(value)

pandas/tests/test_indexing.py

@@ -619,14 +619,20 @@ def test_loc_setitem_multiindex(self):
         self.assertEqual(result, 0)
 
         df = DataFrame(-999,columns=['A', 'w', 'l', 'a', 'x', 'X', 'd', 'profit'], index=index)
-        df.loc[(t,n),'X'] = 0
+        df.loc[(t,n),'X'] = 1
         result = df.loc[(t,n),'X']
-        self.assertEqual(result, 0)
+        self.assertEqual(result, 1)
 
         df = DataFrame(columns=['A', 'w', 'l', 'a', 'x', 'X', 'd', 'profit'], index=index)
-        df.loc[(t,n),'X'] = 0
+        df.loc[(t,n),'X'] = 2
         result = df.loc[(t,n),'X']
-        self.assertEqual(result, 0)
+        self.assertEqual(result, 2)
+
+        # GH 7218, assinging with 0-dim arrays
+        df = DataFrame(-999,columns=['A', 'w', 'l', 'a', 'x', 'X', 'd', 'profit'], index=index)
+        df.loc[(t,n), 'X'] = np.array(3)
+        result = df.loc[(t,n),'X']
+        self.assertEqual(result,3)
 
     def test_loc_setitem_dups(self):