diff --git a/doc/source/api.rst b/doc/source/api.rst
index 3c7ca6d5c2326..98279fbbe6796 100644
--- a/doc/source/api.rst
+++ b/doc/source/api.rst
@@ -345,6 +345,7 @@ Computations / Descriptive Stats
    Series.var
    Series.unique
    Series.nunique
+   Series.is_unique
    Series.value_counts
 
 Reindexing / Selection / Label manipulation
diff --git a/doc/source/whatsnew/v0.18.0.txt b/doc/source/whatsnew/v0.18.0.txt
index 2c97cae80ae2a..d446bf2dd1977 100644
--- a/doc/source/whatsnew/v0.18.0.txt
+++ b/doc/source/whatsnew/v0.18.0.txt
@@ -108,6 +108,7 @@ Other enhancements
 - A simple version of ``Panel.round()`` is now implemented (:issue:`11763`)
 - For Python 3.x, ``round(DataFrame)``, ``round(Series)``, ``round(Panel)`` will work (:issue:`11763`)
 - ``Dataframe`` has gained a ``_repr_latex_`` method in order to allow for automatic conversion to latex in a ipython/jupyter notebook using nbconvert. Options ``display.latex.escape`` and ``display.latex.longtable`` have been added to the configuration and are used automatically by the ``to_latex`` method.(:issue:`11778`)
+- ``Series`` have an ``is_unique`` attribute (:issue:`11946`)
 
 .. _whatsnew_0180.enhancements.rounding:
 
diff --git a/pandas/core/base.py b/pandas/core/base.py
index a1e1c20344ea4..cb29ab11dd34e 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -797,6 +797,17 @@ def nunique(self, dropna=True):
             n -= 1
         return n
 
+    @property
+    def is_unique(self):
+        """
+        Return if values in the object are unique or not.
+
+        Returns
+        -------
+        is_unique : bool 
+        """
+        return self.nunique() == len(self)
+
     def memory_usage(self, deep=False):
         """
         Memory usage of my values
diff --git a/pandas/tests/test_series.py b/pandas/tests/test_series.py
index ad79406c70704..c8a4b1d1ae924 100644
--- a/pandas/tests/test_series.py
+++ b/pandas/tests/test_series.py
@@ -1,4 +1,4 @@
-# coding=utf-8
+# coding=utf-8
 # pylint: disable-msg=E1101,W0612
 
 import re
@@ -8205,6 +8205,12 @@ class SubclassedFrame(DataFrame):
         expected = SubclassedFrame({'X': [1, 2, 3]})
         assert_frame_equal(result, expected)
 
+    def test_is_unique(self):
+        # GH11946
+        s = Series(np.random.randint(0,10,size=1000))
+        self.assertFalse(s.is_unique)
+        s = Series(np.arange(1000))
+        self.assertTrue(s.is_unique)
 
 class TestSeriesNonUnique(tm.TestCase):