cleanup debugging

Author: chris-b1

doc/source/whatsnew/v0.19.0.txt

@@ -948,7 +948,7 @@ Bug Fixes
 - Bug in ``pd.read_hdf()`` returns incorrect result when a ``DataFrame`` with a ``categorical`` column and a query which doesn't match any values (:issue:`13792`)
 - Bug in ``pd.to_datetime()`` raise ``AttributeError`` with NaN and the other string is not valid when errors='ignore' (:issue:`12424`)
 
-
+- Bug in ``groupby`` where a ``TimeGrouper`` selection is used with the ``key`` or ``level`` arguments with a ``PeriodIndex`` (:issue:`14008`)
 - Bug in ``Series`` comparison operators when dealing with zero dim NumPy arrays (:issue:`13006`)
 - Bug in ``groupby`` where ``apply`` returns different result depending on whether first result is ``None`` or not (:issue:`12824`)
 - Bug in ``groupby(..).nth()`` where the group key is included inconsistently if called after ``.head()/.tail()`` (:issue:`12839`)

pandas/tseries/resample.py

@@ -719,10 +719,10 @@ def _upsample(self, method, limit=None):
         if self.axis:
             raise AssertionError('axis must be 0')
         if self.from_selection:
-            raise NotImplementedError("Upsampling from level= or on= selection "
-                                      "is not supported, use .set_index(...) "
-                                      "to explicitly set index to "
-                                      "datetime-like")
+            raise NotImplementedError("Upsampling from level= or on= selection"
+                                      " is not supported, use .set_index(...)"
+                                      " to explicitly set index to"
+                                      " datetime-like")
 
         ax = self.ax
         obj = self._selected_obj
@@ -864,12 +864,11 @@ def _upsample(self, method, limit=None):
         .fillna
 
         """
-        # import pdb; pdb.set_trace()
         if self.from_selection:
-            raise NotImplementedError("Upsampling from level= or on= selection "
-                                      "is not supported, use .set_index(...) "
-                                      "to explicitly set index to "
-                                      "datetime-like")
+            raise NotImplementedError("Upsampling from level= or on= selection"
+                                      " is not supported, use .set_index(...)"
+                                      " to explicitly set index to"
+                                      " datetime-like")
         # we may need to actually resample as if we are timestamps
         if self.kind == 'timestamp':
             return super(PeriodIndexResampler, self)._upsample(method,

pandas/tseries/tests/test_resample.py

@@ -386,8 +386,6 @@ def test_agg_consistency(self):
         assert_frame_equal(result, expected)
 
 
-
-
 class Base(object):
     """
     base class for resampling testing, calling
@@ -515,7 +513,6 @@ def test_agg(self):
                           columns=list('AB'),
                           index=index)
         df_col = df.reset_index()
-        print df_col
         df_mult = df_col.copy()
         df_mult.index = pd.MultiIndex.from_arrays([range(10), df.index],
                                                   names=['index', 'date'])
@@ -733,11 +730,11 @@ def test_selection_api_validation(self):
         index = self.create_series().index
         df = pd.DataFrame({'date': index,
                            'a': np.arange(len(index), dtype=np.int64)},
-                           index=pd.MultiIndex.from_arrays([
-                               np.arange(len(index), dtype=np.int64),
-                               index], names=['v', 'd']))
+                          index=pd.MultiIndex.from_arrays([
+                              np.arange(len(index), dtype=np.int64),
+                              index], names=['v', 'd']))
         df_exp = pd.DataFrame({'a': np.arange(len(index), dtype=np.int64)},
-                               index=index)
+                              index=index)
 
         # non DatetimeIndex
         with tm.assertRaises(TypeError):