PR: Panel and Panel.from_dict() don't honor ordering when passed OrderedDict

RELEASE.rst

@@ -287,6 +287,7 @@ pandas 0.11.0
   - Fix Python ascii file parsing when integer falls outside of floating point
     spacing (GH3258_)
   - fixed pretty priniting of sets (GH3294_)
+  - Panel() and Panel.from_dict() now respects ordering when give OrderedDict (GH3303_)
 
 .. _GH3294: https://github.com/pydata/pandas/issues/3294
 .. _GH622: https://github.com/pydata/pandas/issues/622

pandas/core/panel.py

@@ -13,7 +13,7 @@
 from pandas.core.index import (Index, MultiIndex, _ensure_index,
                                _get_combined_index)
 from pandas.core.indexing import _maybe_droplevels, _is_list_like
-from pandas.core.internals import (BlockManager, 
+from pandas.core.internals import (BlockManager,
                                    create_block_manager_from_arrays,
                                    create_block_manager_from_blocks)
 from pandas.core.series import Series
@@ -274,14 +274,18 @@ def _from_axes(cls, data, axes):
             return cls(data, **d)
 
     def _init_dict(self, data, axes, dtype=None):
+        from pandas.util.compat import OrderedDict
         haxis = axes.pop(self._het_axis)
 
         # prefilter if haxis passed
         if haxis is not None:
             haxis = _ensure_index(haxis)
-            data = dict((k, v) for k, v in data.iteritems() if k in haxis)
+            data = OrderedDict((k, v) for k, v in data.iteritems() if k in haxis)
         else:
-            haxis = Index(_try_sort(data.keys()))
+            ks = data.keys()
+            if not isinstance(data,OrderedDict):
+                ks = _try_sort(ks)
+            haxis = Index(ks)
 
         for k, v in data.iteritems():
             if isinstance(v, dict):
@@ -341,11 +345,11 @@ def from_dict(cls, data, intersect=False, orient='items', dtype=None):
         -------
         Panel
         """
-        from collections import defaultdict
+        from pandas.util.compat import OrderedDict,OrderedDefaultdict
 
         orient = orient.lower()
         if orient == 'minor':
-            new_data = defaultdict(dict)
+            new_data = OrderedDefaultdict(dict)
             for col, df in data.iteritems():
                 for item, s in df.iteritems():
                     new_data[item][col] = s
@@ -354,7 +358,10 @@ def from_dict(cls, data, intersect=False, orient='items', dtype=None):
             raise ValueError('only recognize items or minor for orientation')
 
         d = cls._homogenize_dict(cls, data, intersect=intersect, dtype=dtype)
-        d[cls._info_axis] = Index(sorted(d['data'].keys()))
+        ks = d['data'].keys()
+        if not isinstance(d['data'],OrderedDict):
+            ks = list(sorted(ks))
+        d[cls._info_axis] = Index(ks)
         return cls(**d)
 
     def __getitem__(self, key):
@@ -1491,9 +1498,13 @@ def _homogenize_dict(self, frames, intersect=True, dtype=None):
         -------
         dict of aligned results & indicies
         """
-        result = {}
+        from pandas.util.compat import OrderedDict
 
-        adj_frames = {}
+        result = dict()
+        if isinstance(frames,OrderedDict): # caller differs dict/ODict, presered type
+            result = OrderedDict()
+
+        adj_frames = OrderedDict()
         for k, v in frames.iteritems():
             if isinstance(v, dict):
                 adj_frames[k] = self._constructor_sliced(v)

pandas/tests/test_panel.py

@@ -19,7 +19,9 @@
                                  assert_frame_equal,
                                  assert_series_equal,
                                  assert_almost_equal,
-                                 ensure_clean)
+                                 ensure_clean,
+                                 makeCustomDataframe as mkdf
+    )
 import pandas.core.panel as panelm
 import pandas.util.testing as tm
 
@@ -904,6 +906,16 @@ def test_constructor_dict_mixed(self):
         data['ItemB'] = self.panel['ItemB'].values[:, :-1]
         self.assertRaises(Exception, Panel, data)
 
+    def test_ctor_orderedDict(self):
+        from pandas.util.compat import OrderedDict
+        keys = list(set(np.random.randint(0,5000,100)))[:50] # unique random int  keys
+        d = OrderedDict([(k,mkdf(10,5)) for k in keys])
+        p = Panel(d)
+        self.assertTrue(list(p.items) == keys)
+
+        p = Panel.from_dict(d)
+        self.assertTrue(list(p.items) == keys)
+
     def test_constructor_resize(self):
         data = self.panel._data
         items = self.panel.items[:-1]

pandas/util/compat.py

@@ -475,3 +475,28 @@ def __and__(self, other):
     Counter = _Counter
 else:
     from collections import OrderedDict, Counter
+
+# http://stackoverflow.com/questions/4126348
+# Thanks to @martineau at SO
+
+class OrderedDefaultdict(OrderedDict):
+    def __init__(self, *args, **kwargs):
+        newdefault = None
+        newargs = ()
+        if args:
+            newdefault = args[0]
+            if not (newdefault is None or callable(newdefault)):
+                raise TypeError('first argument must be callable or None')
+            newargs = args[1:]
+        self.default_factory = newdefault
+        super(self.__class__, self).__init__(*newargs, **kwargs)
+
+    def __missing__ (self, key):
+        if self.default_factory is None:
+            raise KeyError(key)
+        self[key] = value = self.default_factory()
+        return value
+
+    def __reduce__(self):  # optional, for pickle support
+        args = self.default_factory if self.default_factory else tuple()
+        return type(self), args, None, None, self.items()