Improve comments, replace np.isscalar with lib.isscalar, and fix file modes

Author: evanpw

pandas/core/generic.py

@@ -2809,7 +2809,7 @@ def clip(self, lower=None, upper=None, out=None, axis=None):
         ----------
         lower : float or array_like, default None
         upper : float or array_like, default None
-        axis : int, optional
+        axis : int or string axis name, optional
             Align object with lower and upper along the given axis.
 
         Returns
@@ -2821,7 +2821,7 @@ def clip(self, lower=None, upper=None, out=None, axis=None):
 
         # GH 2747 (arguments were reversed)
         if lower is not None and upper is not None:
-            if np.isscalar(lower) and np.isscalar(upper):
+            if lib.isscalar(lower) and lib.isscalar(upper):
                 lower, upper = min(lower, upper), max(lower, upper)
 
         result = self
@@ -2839,7 +2839,7 @@ def clip_upper(self, threshold, axis=None):
         Parameters
         ----------
         threshold : float or array_like
-        axis : int, optional
+        axis : int or string axis name, optional
             Align object with threshold along the given axis.
 
         See also
@@ -2867,7 +2867,7 @@ def clip_lower(self, threshold, axis=None):
         Parameters
         ----------
         threshold : float or array_like
-        axis : int, optional
+        axis : int or string axis name, optional
             Align object with threshold along the given axis.
 
         See also

pandas/tests/test_frame.py

@@ -11254,6 +11254,8 @@ def test_dataframe_clip(self):
             self.assertTrue((clipped_df.values[mask] == df.values[mask]).all() == True)
 
     def test_clip_against_series(self):
+        # GH #6966
+
         df = DataFrame(np.random.randn(1000, 2))
         lb = Series(np.random.randn(1000))
         ub = lb + 1

pandas/tests/test_series.py

@@ -4885,6 +4885,8 @@ def test_clip_types_and_nulls(self):
             self.assertEqual(list(isnull(s)), list(isnull(u)))
 
     def test_clip_against_series(self):
+        # GH #6966
+
         s = Series([1.0, 1.0, 4.0])
         threshold = Series([1.0, 2.0, 3.0])