TST/DOC: addtl tests and docs for (GH6056)

doc/source/release.rst

@@ -136,7 +136,7 @@ Bug Fixes
   - Bug in Series.xs with a multi-index (:issue:`6018`)
   - Bug in Series construction of mixed type with datelike and an integer (which should result in
     object type and not automatic conversion) (:issue:`6028`)
-  - Possible segfault when chained indexing with an object array under numpy 1.7.1 (:issue:`6016`)
+  - Possible segfault when chained indexing with an object array under numpy 1.7.1 (:issue:`6026`, :issue:`6056`)
   - Bug in setting using fancy indexing a single element with a non-scalar (e.g. a list),
     (:issue:`6043`)
   - Regression in ``.get(None)`` indexing from 0.12 (:issue:`5652`)

doc/source/tutorials.rst

@@ -1,8 +1,8 @@
 .. _tutorials:
 
-****************
-Pandas Tutorials
-****************
+*********
+Tutorials
+*********
 
 This is a guide to many pandas tutorials, geared mainly for new users.
 

doc/source/v0.13.1.txt

@@ -15,6 +15,28 @@ There are several new or updated docs sections including:
 - :ref:`Tutorials<tutorials>`, a guide to community developed pandas tutorials.
 - :ref:`Pandas Ecosystem<ecosystem>`, a guide to complementary projects built on top of pandas.
 
+.. warning::
+
+   0.13.1 fixes a bug that was caused by a combination of having numpy < 1.8, and doing
+   chained assignent on a string-like array. Please review :ref:`the docs<indexing.view_versus_copy>`,
+   chained indexing can have unexpected results and should generally be avoided.
+
+   This would previously segfault:
+
+   .. ipython:: python
+
+      df = DataFrame(dict(A = np.array(['foo','bar','bah','foo','bar'])))
+      df['A'].iloc[0] = np.nan
+      df
+
+   The recommended way to do this type of assignment is:
+
+   .. ipython:: python
+
+      df = DataFrame(dict(A = np.array(['foo','bar','bah','foo','bar'])))
+      df.ix[0,'A'] = np.nan
+      df
+
 API changes
 ~~~~~~~~~~~
 

pandas/tests/test_indexing.py

@@ -2015,6 +2015,18 @@ def test_setitem_chained_setfault(self):
         df.response[mask] = 'none'
         assert_frame_equal(df, DataFrame({'response': mdata, 'response1' : data }))
 
+        # GH 6056
+        expected = DataFrame(dict(A = [np.nan,'bar','bah','foo','bar']))
+        df = DataFrame(dict(A = np.array(['foo','bar','bah','foo','bar'])))
+        df['A'].iloc[0] = np.nan
+        result = df.head()
+        assert_frame_equal(result, expected)
+
+        df = DataFrame(dict(A = np.array(['foo','bar','bah','foo','bar'])))
+        df.A.iloc[0] = np.nan
+        result = df.head()
+        assert_frame_equal(result, expected)
+
     def test_detect_chained_assignment(self):
 
         pd.set_option('chained_assignment','raise')