BUG: addtl fix for compat summary of groupby/resample with dicts

closes #9052  closes #12332

Author: Jeff Reback <jeff@reback.net>

Closes #12329 from jreback/groupby_compat and squashes the following commits:

0d8561e [Jeff Reback] BUG: resampling with a how could trigger asfreq instead
66c23aa [Jeff Reback] BUG: addtl fix for compat summary of groupby/resample with dicts

doc/source/whatsnew/v0.18.0.txt

@@ -581,7 +581,7 @@ other anchored offsets like ``MonthBegin`` and ``YearBegin``.
 Resample API
 ^^^^^^^^^^^^
 
-Like the change in the window functions API :ref:`above <whatsnew_0180.enhancements.moments>`, ``.resample(...)`` is changing to have a more groupby-like API. (:issue:`11732`, :issue:`12702`, :issue:`12202`).
+Like the change in the window functions API :ref:`above <whatsnew_0180.enhancements.moments>`, ``.resample(...)`` is changing to have a more groupby-like API. (:issue:`11732`, :issue:`12702`, :issue:`12202`, :issue:`12332`).
 
 .. ipython:: python
 

pandas/core/groupby.py

@@ -2526,7 +2526,8 @@ def aggregate(self, func_or_funcs, *args, **kwargs):
             return getattr(self, func_or_funcs)(*args, **kwargs)
 
         if hasattr(func_or_funcs, '__iter__'):
-            ret = self._aggregate_multiple_funcs(func_or_funcs, _level)
+            ret = self._aggregate_multiple_funcs(func_or_funcs,
+                                                 (_level or 0) + 1)
         else:
             cyfunc = self._is_cython_func(func_or_funcs)
             if cyfunc and not args and not kwargs:
@@ -2546,6 +2547,18 @@ def aggregate(self, func_or_funcs, *args, **kwargs):
         if not self.as_index:  # pragma: no cover
             print('Warning, ignoring as_index=True')
 
+        # _level handled at higher
+        if not _level and isinstance(ret, dict):
+            from pandas import concat
+
+            # our result is a Series-like
+            if len(ret) == 1:
+                ret = concat([r for r in ret.values()],
+                             axis=1)
+
+            # our result is a DataFrame like
+            else:
+                ret = concat(ret, axis=1)
         return ret
 
     agg = aggregate
@@ -2571,14 +2584,6 @@ def _aggregate_multiple_funcs(self, arg, _level):
                     columns.append(com._get_callable_name(f))
             arg = lzip(columns, arg)
 
-        # for a ndim=1, disallow a nested dict for an aggregator as
-        # this is a mis-specification of the aggregations, via a
-        # specificiation error
-        # e.g. g['A'].agg({'A': ..., 'B': ...})
-        if self.name in columns and len(columns) > 1:
-            raise SpecificationError('invalid aggregation names specified '
-                                     'for selected objects')
-
         results = {}
         for name, func in arg:
             obj = self

pandas/tests/test_groupby.py

@@ -1558,6 +1558,13 @@ def f():
             'ra', 'std'), ('rb', 'mean'), ('rb', 'std')])
         assert_frame_equal(result, expected, check_like=True)
 
+        # same name as the original column
+        # GH9052
+        expected = g['D'].agg({'result1': np.sum, 'result2': np.mean})
+        expected = expected.rename(columns={'result1': 'D'})
+        result = g['D'].agg({'D': np.sum, 'result2': np.mean})
+        assert_frame_equal(result, expected, check_like=True)
+
     def test_multi_iter(self):
         s = Series(np.arange(6))
         k1 = np.array(['a', 'a', 'a', 'b', 'b', 'b'])

pandas/tseries/resample.py

@@ -500,7 +500,7 @@ def _downsample(self, how, **kwargs):
         # do we have a regular frequency
         if ax.freq is not None or ax.inferred_freq is not None:
 
-            if len(self.grouper.binlabels) > len(ax):
+            if len(self.grouper.binlabels) > len(ax) and how is None:
 
                 # let's do an asfreq
                 return self.asfreq()

pandas/tseries/tests/test_resample.py

@@ -419,25 +419,32 @@ def test_agg_misc(self):
             assert_frame_equal(result, expected, check_like=True)
 
         # series like aggs
-        expected = pd.concat([t['A'].sum(),
-                              t['A'].std()],
-                             axis=1)
-        expected.columns = ['sum', 'std']
-
         for t in [r, g]:
-            result = r['A'].agg({'A': ['sum', 'std']})
+            result = t['A'].agg({'A': ['sum', 'std']})
+            expected = pd.concat([t['A'].sum(),
+                                  t['A'].std()],
+                                 axis=1)
+            expected.columns = ['sum', 'std']
+
+            assert_frame_equal(result, expected, check_like=True)
+
+            expected = pd.concat([t['A'].agg(['sum', 'std']),
+                                  t['A'].agg(['mean', 'std'])],
+                                 axis=1)
+            expected.columns = pd.MultiIndex.from_tuples([('A', 'sum'),
+                                                          ('A', 'std'),
+                                                          ('B', 'mean'),
+                                                          ('B', 'std')])
+            result = t['A'].agg({'A': ['sum', 'std'], 'B': ['mean', 'std']})
             assert_frame_equal(result, expected, check_like=True)
 
         # errors
+        # invalid names in the agg specification
         for t in [r, g]:
 
-            # invalid names in the agg specification
             def f():
-                r['A'].agg({'A': ['sum', 'std'], 'B': ['mean', 'std']})
-            self.assertRaises(SpecificationError, f)
-
-            def f():
-                r[['A']].agg({'A': ['sum', 'std'], 'B': ['mean', 'std']})
+                r[['A']].agg({'A': ['sum', 'std'],
+                              'B': ['mean', 'std']})
             self.assertRaises(SpecificationError, f)
 
     def test_agg_nested_dicts(self):
@@ -918,6 +925,19 @@ def test_resample_ohlc(self):
         self.assertEqual(xs['low'], s[:5].min())
         self.assertEqual(xs['close'], s[4])
 
+    def test_resample_ohlc_result(self):
+
+        # GH 12332
+        index = pd.date_range('1-1-2000', '2-15-2000', freq='h')
+        index = index.union(pd.date_range('4-15-2000', '5-15-2000', freq='h'))
+        s = Series(range(len(index)), index=index)
+
+        a = s.loc[:'4-15-2000'].resample('30T').ohlc()
+        self.assertIsInstance(a, DataFrame)
+
+        b = s.loc[:'4-14-2000'].resample('30T').ohlc()
+        self.assertIsInstance(b, DataFrame)
+
     def test_resample_ohlc_dataframe(self):
         df = (
             pd.DataFrame({