Clean-up timedelta/period/plotting benchmarks

Author: jorisvandenbossche

asv_bench/benchmarks/period.py

@@ -1,31 +1,33 @@
+import pandas as pd
 from pandas import Series, Period, PeriodIndex, date_range
 
 
-class create_period_index_from_date_range(object):
+class Constructor(object):
     goal_time = 0.2
 
-    def time_period_index(self):
-        # Simulate irregular PeriodIndex
-        PeriodIndex(date_range('1985', periods=1000).to_pydatetime(), freq='D')
+    def setup(self):
+        self.rng = date_range('1985', periods=1000)
+        self.rng2 = date_range('1985', periods=1000).to_pydatetime()
+
+    def time_from_date_range(self):
+        PeriodIndex(self.rng, freq='D')
 
+    def time_from_pydatetime(self):
+        PeriodIndex(self.rng2, freq='D')
 
-class period_setitem(object):
+
+class DataFrame(object):
     goal_time = 0.2
 
     def setup(self):
-        self.N = 100000
-        self.rng = date_range(start='1/1/2000', periods=self.N, freq='T')
-        if hasattr(Series, 'convert'):
-            Series.resample = Series.convert
-        self.ts = Series(np.random.randn(self.N), index=self.rng)
-        self.rng = period_range(start='1/1/1990', freq='S', periods=20000)
-        self.df = DataFrame(index=range(len(self.rng)))
-
-    def time_period_setitem(self):
+        self.rng = pd.period_range(start='1/1/1990', freq='S', periods=20000)
+        self.df = pd.DataFrame(index=range(len(self.rng)))
+
+    def time_setitem_period_column(self):
         self.df['col'] = self.rng
 
 
-class period_algorithm(object):
+class Algorithms(object):
     goal_time = 0.2
 
     def setup(self):
@@ -34,16 +36,16 @@ def setup(self):
         self.s = Series(data * 1000)
         self.i = PeriodIndex(data, freq='M')
 
-    def time_period_series_drop_duplicates(self):
+    def time_drop_duplicates_pseries(self):
         self.s.drop_duplicates()
 
-    def time_period_index_drop_duplicates(self):
+    def time_drop_duplicates_pindex(self):
         self.i.drop_duplicates()
 
-    def time_period_series_value_counts(self):
+    def time_value_counts_pseries(self):
         self.s.value_counts()
 
-    def time_period_index_value_counts(self):
+    def time_value_counts_pindex(self):
         self.i.value_counts()
 
 

asv_bench/benchmarks/plotting.py

@@ -7,7 +7,7 @@ def date_range(start=None, end=None, periods=None, freq=None):
 from pandas.tools.plotting import andrews_curves
 
 
-class plot_timeseries_period(object):
+class TimeseriesPlotting(object):
     goal_time = 0.2
 
     def setup(self):
@@ -17,11 +17,11 @@ def setup(self):
         self.M = 5
         self.df = DataFrame(np.random.randn(self.N, self.M), index=date_range('1/1/1975', periods=self.N))
 
-    def time_plot_timeseries_period(self):
+    def time_plot_regular(self):
         self.df.plot()
 
 
-class plot_andrews_curves(object):
+class Misc(object):
     goal_time = 0.6
 
     def setup(self):

asv_bench/benchmarks/timedelta.py

@@ -2,7 +2,7 @@
 from pandas import to_timedelta, Timestamp
 
 
-class Timedelta(object):
+class ToTimedelta(object):
     goal_time = 0.2
 
     def setup(self):
@@ -12,6 +12,9 @@ def setup(self):
         self.arr3 = np.random.randint(0, 60, size=10000)
         self.arr3 = ['00:00:{0:02d}'.format(i) for i in self.arr3]
 
+        self.arr4 = list(self.arr2)
+        self.arr4[-1] = 'apple'
+
     def time_convert_int(self):
         to_timedelta(self.arr, unit='s')
 
@@ -21,23 +24,14 @@ def time_convert_string(self):
     def time_convert_string_seconds(self):
         to_timedelta(self.arr3)
 
+    def time_convert_coerce(self):
+        to_timedelta(self.arr4, errors='coerce')
 
-class timedelta_convert_bad_parse(object):
-    goal_time = 0.2
-
-    def setup(self):
-        self.arr = np.random.randint(0, 1000, size=10000)
-        self.arr = ['{0} days'.format(i) for i in self.arr]
-        self.arr[-1] = 'apple'
-
-    def time_timedelta_convert_coerce(self):
-        to_timedelta(self.arr, errors='coerce')
-
-    def time_timedelta_convert_ignore(self):
-        to_timedelta(self.arr, errors='ignore')
+    def time_convert_ignore(self):
+        to_timedelta(self.arr4, errors='ignore')
 
 
-class timedelta_add_overflow(object):
+class Ops(object):
     goal_time = 0.2
 
     def setup(self):