diff --git a/doc/source/release.rst b/doc/source/release.rst
index b5a11091779ec..728dddbe8b979 100644
--- a/doc/source/release.rst
+++ b/doc/source/release.rst
@@ -475,6 +475,8 @@ Bug Fixes
   caused possible color/class mismatch (:issue:`6956`)
 - Bug in ``radviz`` and ``andrews_curves`` where multiple values of 'color'
   were being passed to plotting method (:issue:`6956`)
+- Bug in ``Float64Index.isin()`` where containing ``nan`` s would make indices
+  claim that they contained all the things (:issue:`7066`).
 
 pandas 0.13.1
 -------------
diff --git a/pandas/core/index.py b/pandas/core/index.py
index ff6ee79bf24e4..c3619b992028d 100644
--- a/pandas/core/index.py
+++ b/pandas/core/index.py
@@ -2096,7 +2096,8 @@ def isin(self, values):
         """
         value_set = set(values)
         return lib.ismember_nans(self._array_values(), value_set,
-                                 self._hasnans)
+                                 isnull(list(value_set)).any())
+
 
 class MultiIndex(Index):
 
diff --git a/pandas/tests/test_index.py b/pandas/tests/test_index.py
index 206c85124e122..dafbfd07ca51d 100644
--- a/pandas/tests/test_index.py
+++ b/pandas/tests/test_index.py
@@ -913,6 +913,25 @@ def test_contains_not_nans(self):
         i = Float64Index([1.0, 2.0, np.nan])
         self.assertTrue(1.0 in i)
 
+    def test_doesnt_contain_all_the_things(self):
+        i = Float64Index([np.nan])
+        self.assertFalse(i.isin([0]).item())
+        self.assertFalse(i.isin([1]).item())
+        self.assertTrue(i.isin([np.nan]).item())
+
+    def test_nan_multiple_containment(self):
+        i = Float64Index([1.0, np.nan])
+        np.testing.assert_array_equal(i.isin([1.0]), np.array([True, False]))
+        np.testing.assert_array_equal(i.isin([2.0, np.pi]),
+                                      np.array([False, False]))
+        np.testing.assert_array_equal(i.isin([np.nan]),
+                                      np.array([False, True]))
+        np.testing.assert_array_equal(i.isin([1.0, np.nan]),
+                                      np.array([True, True]))
+        i = Float64Index([1.0, 2.0])
+        np.testing.assert_array_equal(i.isin([np.nan]),
+                                      np.array([False, False]))
+
 
 class TestInt64Index(tm.TestCase):
     _multiprocess_can_split_ = True