diff --git a/doc/source/whatsnew/v0.20.0.txt b/doc/source/whatsnew/v0.20.0.txt
index 4708abe4d592e..868ae003b8cd5 100644
--- a/doc/source/whatsnew/v0.20.0.txt
+++ b/doc/source/whatsnew/v0.20.0.txt
@@ -585,3 +585,5 @@ Bug Fixes
 - Bug in ``Series.replace`` and ``DataFrame.replace`` which failed on empty replacement dicts (:issue:`15289`)
 - Bug in ``pd.melt()`` where passing a tuple value for ``value_vars`` caused a ``TypeError`` (:issue:`15348`)
 - Bug in ``.eval()`` which caused multiline evals to fail with local variables not on the first line (:issue:`15342`)
+
+- Bug in ``groupby().nunique()`` when using ``TimeGrouper`` and a gap existed in the dates the values wouldn't be correct (:issue:`13453`)
diff --git a/pandas/core/groupby.py b/pandas/core/groupby.py
index 23c835318b0e6..ba2de295fa0a9 100644
--- a/pandas/core/groupby.py
+++ b/pandas/core/groupby.py
@@ -3032,7 +3032,7 @@ def nunique(self, dropna=True):
         # we might have duplications among the bins
         if len(res) != len(ri):
             res, out = np.zeros(len(ri), dtype=out.dtype), res
-            res[ids] = out
+            res[ids[idx]] = out
 
         return Series(res,
                       index=ri,
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index d53446870beb1..59cbcab23b9e7 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -4159,6 +4159,19 @@ def test_nunique_with_empty_series(self):
         expected = pd.Series(name='name', dtype='int64')
         tm.assert_series_equal(result, expected)
 
+    def test_nunique_with_timegrouper(self):
+        # GH 13453
+        test = pd.DataFrame({
+            'time': [Timestamp('2016-06-28 09:35:35'),
+                     Timestamp('2016-06-28 16:09:30'),
+                     Timestamp('2016-06-28 16:46:28')],
+            'data': ['1', '2', '3']}).set_index('time')
+        result = test.groupby(pd.TimeGrouper(freq='h'))['data'].nunique()
+        expected = test.groupby(
+            pd.TimeGrouper(freq='h')
+        )['data'].apply(pd.Series.nunique)
+        tm.assert_series_equal(result, expected)
+
     def test_numpy_compat(self):
         # see gh-12811
         df = pd.DataFrame({'A': [1, 2, 1], 'B': [1, 2, 3]})
diff --git a/pandas/tests/tseries/test_resample.py b/pandas/tests/tseries/test_resample.py
index afb44887fe7d1..95ce1b980a548 100755
--- a/pandas/tests/tseries/test_resample.py
+++ b/pandas/tests/tseries/test_resample.py
@@ -1939,6 +1939,28 @@ def test_resample_nunique(self):
         result = df.ID.groupby(pd.Grouper(freq='D')).nunique()
         assert_series_equal(result, expected)
 
+    def test_resample_nunique_with_date_gap(self):
+        # GH 13453
+        index = pd.date_range('1-1-2000', '2-15-2000', freq='h')
+        index2 = pd.date_range('4-15-2000', '5-15-2000', freq='h')
+        index3 = index.append(index2)
+        s = pd.Series(range(len(index3)), index=index3)
+        r = s.resample('M')
+
+        # Since all elements are unique, these should all be the same
+        results = [
+            r.count(),
+            r.nunique(),
+            r.agg(pd.Series.nunique),
+            r.agg('nunique')
+        ]
+
+        for res1 in results:
+            for res2 in results:
+                if res1 is not res2:
+                    print('running')
+                    assert_series_equal(res1, res2)
+
     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')