diff --git a/sklearn/datasets/base.py b/sklearn/datasets/base.py
index 2305f60ebbb54..d37b308a6d5d8 100644
--- a/sklearn/datasets/base.py
+++ b/sklearn/datasets/base.py
@@ -322,7 +322,7 @@ def load_wine(return_X_y=False):
                                 'proline'])
 
 
-def load_iris(return_X_y=False):
+def load_iris(return_X_y=False, as_frame=False):
     """Load and return the iris dataset (classification).
 
     The iris dataset is a classic and very easy multi-class classification
@@ -382,11 +382,19 @@ def load_iris(return_X_y=False):
     if return_X_y:
         return data, target
 
+    feature_names = ['sepal length (cm)', 'sepal width (cm)',
+                     'petal length (cm)', 'petal width (cm)']
+
+    if as_frame:
+        from pandas import Series, DataFrame
+        data_frame = DataFrame(data, columns=feature_names)
+        target_series = pd.Series(target, name="class")
+        return data_frame, target_series
+
     return Bunch(data=data, target=target,
                  target_names=target_names,
                  DESCR=fdescr,
-                 feature_names=['sepal length (cm)', 'sepal width (cm)',
-                                'petal length (cm)', 'petal width (cm)'],
+                 feature_names=feature_names,
                  filename=iris_csv_filename)
 
 
diff --git a/sklearn/datasets/tests/test_base.py b/sklearn/datasets/tests/test_base.py
index 091735b986a3f..61c495c01f1de 100644
--- a/sklearn/datasets/tests/test_base.py
+++ b/sklearn/datasets/tests/test_base.py
@@ -29,6 +29,7 @@
 from sklearn.utils.testing import assert_true
 from sklearn.utils.testing import assert_equal
 from sklearn.utils.testing import assert_raises
+from sklearn.utils.testing import SkipTest
 
 
 DATA_HOME = tempfile.mkdtemp(prefix="scikit_learn_data_home_test_")
@@ -202,6 +203,15 @@ def test_load_iris():
     check_return_X_y(res, partial(load_iris))
 
 
+def test_load_iris_as_frame():
+    try:
+        data_frame, target_series = load_iris(as_frame=True)
+        assert_equal(data_frame.shape, (150, 4))
+        assert_equal(target_series.shape[0], 150)
+    except IOError as :
+        SkipTest("Pandas is needed to run the test")
+
+
 def test_load_wine():
     res = load_wine()
     assert_equal(res.data.shape, (178, 13))