Merge pull request pandas-dev#4756 from jreback/nested

BUG/ER:  (GH2702) Bug with Series indexing not raising an error when the right-hand-side has an incorrect length

Author: jreback

doc/source/release.rst

@@ -321,6 +321,7 @@ See :ref:`Internal Refactoring<whatsnew_0130.refactoring>`
     etc. (:issue:`4718`, :issue:`4628`)
   - Bug in using ``iloc/loc`` with a cross-sectional and duplicate indicies (:issue:`4726`)
   - Bug with using ``QUOTE_NONE`` with ``to_csv`` causing ``Exception``. (:issue:`4328`)
+  - Bug with Series indexing not raising an error when the right-hand-side has an incorrect length (:issue:`2702`)
 
 pandas 0.12
 ===========

pandas/core/internals.py

@@ -547,10 +547,41 @@ def setitem(self, indexer, value):
             dtype, _ = com._maybe_promote(arr_value.dtype)
             values = values.astype(dtype)
 
+        transf = (lambda x: x.T) if self.ndim == 2 else (lambda x: x)
+        values = transf(values)
+        l = len(values)
+
+        # length checking
+        # boolean with truth values == len of the value is ok too
+        if isinstance(indexer, (np.ndarray, list)):
+            if is_list_like(value) and len(indexer) != len(value):
+                if not (isinstance(indexer, np.ndarray) and indexer.dtype == np.bool_ and len(indexer[indexer]) == len(value)):
+                    raise ValueError("cannot set using a list-like indexer with a different length than the value")
+
+        # slice
+        elif isinstance(indexer, slice):
+
+            if is_list_like(value) and l:
+                start = indexer.start
+                stop = indexer.stop
+                step = indexer.step
+                if start is None:
+                    start = 0
+                elif start < 0:
+                    start += l
+                if stop is None or stop > l:
+                    stop = len(values)
+                elif stop < 0:
+                    stop += l
+                if step is None:
+                    step = 1
+                elif step < 0:
+                    step = abs(step)
+                if (stop-start) / step != len(value):
+                    raise ValueError("cannot set using a slice indexer with a different length than the value")
+
         try:
             # set and return a block
-            transf = (lambda x: x.T) if self.ndim == 2 else (lambda x: x)
-            values = transf(values)
             values[indexer] = value
 
             # coerce and try to infer the dtypes of the result
@@ -561,7 +592,9 @@ def setitem(self, indexer, value):
             values = self._try_coerce_result(values)
             values = self._try_cast_result(values, dtype)
             return [make_block(transf(values), self.items, self.ref_items, ndim=self.ndim, fastpath=True)]
-        except:
+        except (ValueError, TypeError) as detail:
+            raise
+        except (Exception) as detail:
             pass
 
         return [ self ]

pandas/core/series.py

@@ -1096,10 +1096,9 @@ def _set_labels(self, key, value):
         self._set_values(indexer, value)
 
     def _set_values(self, key, value):
-        values = self.values
         if isinstance(key, Series):
             key = key.values
-        values[key] = _index.convert_scalar(values, value)
+        self._data = self._data.setitem(key,value)
 
     # help out SparseSeries
     _get_val_at = ndarray.__getitem__

pandas/tests/test_series.py

@@ -1284,6 +1284,59 @@ def f():
         expected = Series(np.nan,index=[9])
         assert_series_equal(result, expected)
 
+    def test_where_setitem_invalid(self):
+
+        # GH 2702
+        # make sure correct exceptions are raised on invalid list assignment
+
+        # slice
+        s = Series(list('abc'))
+        def f():
+            s[0:3] = list(range(27))
+        self.assertRaises(ValueError, f)
+
+        s[0:3] = list(range(3))
+        expected = Series([0,1,2])
+        assert_series_equal(s, expected)
+
+        # slice with step
+        s = Series(list('abcdef'))
+        def f():
+            s[0:4:2] = list(range(27))
+        self.assertRaises(ValueError, f)
+
+        s = Series(list('abcdef'))
+        s[0:4:2] = list(range(2))
+        expected = Series([0,'b',1,'d','e','f'])
+        assert_series_equal(s, expected)
+
+        # neg slices
+        s = Series(list('abcdef'))
+        def f():
+            s[:-1] = list(range(27))
+        self.assertRaises(ValueError, f)
+
+        s[-3:-1] = list(range(2))
+        expected = Series(['a','b','c',0,1,'f'])
+        assert_series_equal(s, expected)
+
+        # list
+        s = Series(list('abc'))
+        def f():
+            s[[0,1,2]] = list(range(27))
+        self.assertRaises(ValueError, f)
+
+        s = Series(list('abc'))
+        def f():
+            s[[0,1,2]] = list(range(2))
+        self.assertRaises(ValueError, f)
+
+        # scalar
+        s = Series(list('abc'))
+        s[0] = list(range(10))
+        expected = Series([list(range(10)),'b','c'])
+        assert_series_equal(s, expected)
+
     def test_where_broadcast(self):
         # Test a variety of differently sized series
         for size in range(2, 6):
@@ -2550,22 +2603,23 @@ def test_between(self):
         expected = s[5:16].dropna()
         assert_series_equal(result, expected)
 
-    def test_setitem_na_exception(self):
-        def testme1():
-            s = Series([2, 3, 4, 5, 6, 7, 8, 9, 10])
-            s[::2] = np.nan
-
-        def testme2():
-            s = Series([True, True, False, False])
-            s[::2] = np.nan
+    def test_setitem_na(self):
+        # these induce dtype changes
+        expected = Series([np.nan, 3, np.nan, 5, np.nan, 7, np.nan, 9, np.nan])
+        s = Series([2, 3, 4, 5, 6, 7, 8, 9, 10])
+        s[::2] = np.nan
+        assert_series_equal(s, expected)
 
-        def testme3():
-            s = Series(np.arange(10))
-            s[:5] = np.nan
+        # get's coerced to float, right?
+        expected = Series([np.nan, 1, np.nan, 0])
+        s = Series([True, True, False, False])
+        s[::2] = np.nan
+        assert_series_equal(s, expected)
 
-        self.assertRaises(Exception, testme1)
-        self.assertRaises(Exception, testme2)
-        self.assertRaises(Exception, testme3)
+        expected = Series([np.nan, np.nan, np.nan, np.nan, np.nan, 5, 6, 7, 8, 9])
+        s = Series(np.arange(10))
+        s[:5] = np.nan
+        assert_series_equal(s, expected)
 
     def test_scalar_na_cmp_corners(self):
         s = Series([2, 3, 4, 5, 6, 7, 8, 9, 10])