diff --git a/RELEASE.rst b/RELEASE.rst
index 981fa5bed257d..7767129de084a 100644
--- a/RELEASE.rst
+++ b/RELEASE.rst
@@ -22,6 +22,12 @@ Where to get it
 * Binary installers on PyPI: http://pypi.python.org/pypi/pandas
 * Documentation: http://pandas.pydata.org
 
+**API Changes**
+
+  - arguments to DataFrame.clip were inconsistent to numpy and Series clipping (GH2747_)
+
+.. _GH2747: https://github.com/pydata/pandas/issues/2747
+
 pandas 0.10.1
 =============
 
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 301ea9d28d001..d625fb87e3fd5 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -5029,7 +5029,7 @@ def f(arr):
         data = self._get_numeric_data() if numeric_only else self
         return data.apply(f, axis=axis)
 
-    def clip(self, upper=None, lower=None):
+    def clip(self, lower=None, upper=None):
         """
         Trim values at input threshold(s)
 
@@ -5042,6 +5042,11 @@ def clip(self, upper=None, lower=None):
         -------
         clipped : DataFrame
         """
+
+        # GH 2747 (arguments were reversed)
+        if lower is not None and upper is not None:
+            lower, upper = min(lower,upper), max(lower,upper)
+            
         return self.apply(lambda x: x.clip(lower=lower, upper=upper))
 
     def clip_upper(self, threshold):
diff --git a/pandas/tests/test_frame.py b/pandas/tests/test_frame.py
index 09747ba3f09f0..d55e7a7b65fe3 100644
--- a/pandas/tests/test_frame.py
+++ b/pandas/tests/test_frame.py
@@ -6470,6 +6470,22 @@ def test_clip(self):
         double = self.frame.clip(upper=median, lower=median)
         self.assert_(not (double.values != median).any())
 
+    def test_dataframe_clip(self):
+
+        # GH #2747
+        df = DataFrame(np.random.randn(1000,2))
+
+        for lb, ub in [(-1,1),(1,-1)]:
+            clipped_df = df.clip(lb, ub)
+
+            lb, ub = min(lb,ub), max(ub,lb)
+            lb_mask = df.values <= lb
+            ub_mask = df.values >= ub
+            mask = ~lb_mask & ~ub_mask
+            self.assert_((clipped_df.values[lb_mask] == lb).all() == True)
+            self.assert_((clipped_df.values[ub_mask] == ub).all() == True)
+            self.assert_((clipped_df.values[mask] == df.values[mask]).all() == True)
+        
     def test_get_X_columns(self):
         # numeric and object columns