CLN: ASV replace

asv_bench/benchmarks/replace.py

@@ -1,70 +1,58 @@
-from .pandas_vb_common import *
+import numpy as np
+import pandas as pd
 
+from .pandas_vb_common import setup  # noqa
 
-class replace_fillna(object):
-    goal_time = 0.2
-
-    def setup(self):
-        self.N = 1000000
-        try:
-            self.rng = date_range('1/1/2000', periods=self.N, freq='min')
-        except NameError:
-            self.rng = DatetimeIndex('1/1/2000', periods=self.N, offset=datetools.Minute())
-            self.date_range = DateRange
-        self.ts = Series(np.random.randn(self.N), index=self.rng)
 
-    def time_replace_fillna(self):
-        self.ts.fillna(0.0, inplace=True)
+class NaN(object):
 
-
-class replace_large_dict(object):
     goal_time = 0.2
+    params = [True, False]
+    param_names = ['inplace']
 
-    def setup(self):
-        self.n = (10 ** 6)
-        self.start_value = (10 ** 5)
-        self.to_rep = {i: self.start_value + i for i in range(self.n)}
-        self.s = Series(np.random.randint(self.n, size=(10 ** 3)))
-
-    def time_replace_large_dict(self):
-        self.s.replace(self.to_rep, inplace=True)
+    def setup(self, inplace):
+        N = 10**6
+        rng = pd.date_range('1/1/2000', periods=N, freq='min')
+        data = np.random.randn(N)
+        data[::2] = np.nan
+        self.ts = pd.Series(data, index=rng)
 
+    def time_fillna(self, inplace):
+        self.ts.fillna(0.0, inplace=inplace)
 
-class replace_convert(object):
-    goal_time = 0.5
+    def time_replace(self, inplace):
+        self.ts.replace(np.nan, 0.0, inplace=inplace)
 
-    def setup(self):
-        self.n = (10 ** 3)
-        self.to_ts = {i: pd.Timestamp(i) for i in range(self.n)}
-        self.to_td = {i: pd.Timedelta(i) for i in range(self.n)}
-        self.s = Series(np.random.randint(self.n, size=(10 ** 3)))
-        self.df = DataFrame({'A': np.random.randint(self.n, size=(10 ** 3)),
-                             'B': np.random.randint(self.n, size=(10 ** 3))})
 
-    def time_replace_series_timestamp(self):
-        self.s.replace(self.to_ts)
+class ReplaceDict(object):
 
-    def time_replace_series_timedelta(self):
-        self.s.replace(self.to_td)
+    goal_time = 0.2
+    params = [True, False]
+    param_names = ['inplace']
 
-    def time_replace_frame_timestamp(self):
-        self.df.replace(self.to_ts)
+    def setup(self, inplace):
+        N = 10**5
+        start_value = 10**5
+        self.to_rep = dict(enumerate(np.arange(N) + start_value))
+        self.s = pd.Series(np.random.randint(N, size=10**3))
 
-    def time_replace_frame_timedelta(self):
-        self.df.replace(self.to_td)
+    def time_replace_series(self, inplace):
+        self.s.replace(self.to_rep, inplace=inplace)
 
 
-class replace_replacena(object):
-    goal_time = 0.2
+class Convert(object):
 
-    def setup(self):
-        self.N = 1000000
-        try:
-            self.rng = date_range('1/1/2000', periods=self.N, freq='min')
-        except NameError:
-            self.rng = DatetimeIndex('1/1/2000', periods=self.N, offset=datetools.Minute())
-            self.date_range = DateRange
-        self.ts = Series(np.random.randn(self.N), index=self.rng)
-
-    def time_replace_replacena(self):
-        self.ts.replace(np.nan, 0.0, inplace=True)
+    goal_time = 0.5
+    params = (['DataFrame', 'Series'], ['Timestamp', 'Timedelta'])
+    param_names = ['contructor', 'replace_data']
+
+    def setup(self, contructor, replace_data):
+        N = 10**3
+        data = {'Series': pd.Series(np.random.randint(N, size=N)),
+                'DataFrame': pd.DataFrame({'A': np.random.randint(N, size=N),
+                                           'B': np.random.randint(N, size=N)})}
+        self.to_replace = {i: getattr(pd, replace_data) for i in range(N)}
+        self.data = data[contructor]
+
+    def time_replace(self, contructor, replace_data):
+        self.data.replace(self.to_replace)