BUG: closes bug in BinGrouper.group_info where returned values are not compatible with base class

doc/source/whatsnew/v0.17.0.txt

@@ -747,6 +747,7 @@ Bug Fixes
 - Bug in ``Index`` construction with a mixed list of tuples (:issue:`10697`)
 - Bug in ``DataFrame.reset_index`` when index contains `NaT`. (:issue:`10388`)
 - Bug in ``ExcelReader`` when worksheet is empty (:issue:`6403`)
+- Bug in ``BinGrouper.group_info`` where returned values are not compatible with base class (:issue:`10914`)
 
 
 - Bug causing ``DataFrame.where`` to not respect the ``axis`` parameter when the frame has a symmetric shape. (:issue:`9736`)

pandas/core/groupby.py

@@ -1790,8 +1790,10 @@ def indices(self):
 
     @cache_readonly
     def group_info(self):
-        # for compat
-        return self.bins, self.binlabels, self.ngroups
+        ngroups = self.ngroups
+        obs_group_ids = np.arange(ngroups)
+        comp_ids = np.repeat(np.arange(ngroups), np.diff(np.r_[0, self.bins]))
+        return comp_ids, obs_group_ids, ngroups
 
     @cache_readonly
     def ngroups(self):

pandas/tseries/tests/test_resample.py

@@ -916,6 +916,31 @@ def test_resample_timegrouper(self):
             result = df.groupby(pd.Grouper(freq='M', key='A')).count()
             assert_frame_equal(result, expected)
 
+    def test_resample_group_info(self):  # GH10914
+        for n, k in product((10000, 100000), (10, 100, 1000)):
+            dr = date_range(start='2015-08-27', periods=n // 10, freq='T')
+            ts = Series(np.random.randint(0, n // k, n),
+                        index=np.random.choice(dr, n))
+
+            left = ts.resample('30T', how='nunique')
+            ix = date_range(start=ts.index.min(),
+                            end=ts.index.max(),
+                            freq='30T')
+
+            vals = ts.values
+            bins = np.searchsorted(ix.values, ts.index, side='right')
+
+            sorter = np.lexsort((vals, bins))
+            vals, bins = vals[sorter], bins[sorter]
+
+            mask = np.r_[True, vals[1:] != vals[:-1]]
+            mask |= np.r_[True, bins[1:] != bins[:-1]]
+
+            arr = np.bincount(bins[mask] - 1, minlength=len(ix))
+            right = Series(arr, index=ix)
+
+            assert_series_equal(left, right)
+
     def test_resmaple_dst_anchor(self):
         # 5172
         dti = DatetimeIndex([datetime(2012, 11, 4, 23)], tz='US/Eastern')