PERF: improved clip performance

closes pandas-dev#15400

Author: jreback

asv_bench/benchmarks/series_methods.py

@@ -111,6 +111,7 @@ def setup(self):
     def time_series_dropna_int64(self):
         self.s.dropna()
 
+
 class series_dropna_datetime(object):
     goal_time = 0.2
 
@@ -120,3 +121,13 @@ def setup(self):
 
     def time_series_dropna_datetime(self):
         self.s.dropna()
+
+
+class series_clip(object):
+    goal_time = 0.2
+
+    def setup(self):
+        self.s = pd.Series(np.random.randn(50))
+
+    def time_series_dropna_datetime(self):
+        self.s.clip(0, 1)

pandas/core/generic.py

@@ -14,6 +14,7 @@
     _ensure_int64,
     needs_i8_conversion,
     is_scalar,
+    is_number,
     is_integer, is_bool,
     is_bool_dtype,
     is_numeric_dtype,
@@ -4122,26 +4123,29 @@ def clip(self, lower=None, upper=None, axis=None, *args, **kwargs):
         Examples
         --------
         >>> df
-          0         1
+                  0         1
         0  0.335232 -1.256177
         1 -1.367855  0.746646
         2  0.027753 -1.176076
         3  0.230930 -0.679613
         4  1.261967  0.570967
+
         >>> df.clip(-1.0, 0.5)
                   0         1
         0  0.335232 -1.000000
         1 -1.000000  0.500000
         2  0.027753 -1.000000
         3  0.230930 -0.679613
         4  0.500000  0.500000
+
         >>> t
         0   -0.3
         1   -0.2
         2   -0.1
         3    0.0
         4    0.1
         dtype: float64
+
         >>> df.clip(t, t + 1, axis=0)
                   0         1
         0  0.335232 -0.300000
@@ -4160,6 +4164,24 @@ def clip(self, lower=None, upper=None, axis=None, *args, **kwargs):
             if is_scalar(lower) and is_scalar(upper):
                 lower, upper = min(lower, upper), max(lower, upper)
 
+        # fast-path for scalars
+        if ((lower is None or (is_scalar(lower) and is_number(lower))) and
+                (upper is None or (is_scalar(upper) and is_number(upper)))):
+
+            if ((lower is not None and np.any(isnull(lower))) or
+                    (upper is not None and np.any(isnull(upper)))):
+                raise ValueError("Cannot use an NA value as a clip threshold")
+
+            mask = isnull(self)
+            result = self.values
+            if upper is not None:
+                result = np.where(result >= upper, upper, result)
+            if lower is not None:
+                result = np.where(result <= lower, lower, result)
+            result[mask] = np.nan
+            return self._constructor(
+                result, **self._construct_axes_dict()).__finalize__(self)
+
         result = self
         if lower is not None:
             result = result.clip_lower(lower, axis)

pandas/tests/series/test_analytics.py

@@ -1011,6 +1011,7 @@ def test_clip_against_series(self):
 
         lower = Series([1.0, 2.0, 3.0])
         upper = Series([1.5, 2.5, 3.5])
+
         assert_series_equal(s.clip(lower, upper), Series([1.0, 2.0, 3.5]))
         assert_series_equal(s.clip(1.5, upper), Series([1.5, 1.5, 3.5]))