CLN: ASV timeseries
State: closed

- [x] closes #8144 (benchmarks now have random seed where appropriate)

Split up the some benchmarks and utilized `param`s where available. I think `to_datetime(...,cache=True)` is tagged for v0.23 so that's probably why the `ToDatetimeCache` benchmarks don't work yet? 

```
[  0.00%] ·· Building for existing-py_home_matt_anaconda_envs_pandas_dev_bin_python
[  0.00%] ·· Benchmarking existing-py_home_matt_anaconda_envs_pandas_dev_bin_python
[  2.38%] ··· Running timeseries.AsOf.time_asof                              ok
[  2.38%] ···· 
               ============= ========
                constructor          
               ------------- --------
                 DataFrame    25.9ms 
                   Series     13.8ms 
               ============= ========

[  4.76%] ··· Running timeseries.AsOf.time_asof_nan                          ok
[  4.76%] ···· 
               ============= ========
                constructor          
               ------------- --------
                 DataFrame    27.8ms 
                   Series     13.4ms 
               ============= ========

[  7.14%] ··· Running timeseries.AsOf.time_asof_nan_single                   ok
[  7.14%] ···· 
               ============= ========
                constructor          
               ------------- --------
                 DataFrame    7.96ms 
                   Series     6.70ms 
               ============= ========

[  9.52%] ··· Running timeseries.AsOf.time_asof_single                       ok
[  9.52%] ···· 
               ============= ========
                constructor          
               ------------- --------
                 DataFrame    7.98ms 
                   Series     225μs  
               ============= ========

[ 11.90%] ··· Running timeseries.AsOf.time_asof_single_early                 ok
[ 11.90%] ···· 
               ============= =======
                constructor         
               ------------- -------
                 DataFrame    406μs 
                   Series     168μs 
               ============= =======

[ 14.29%] ··· Running timeseries.DatetimeAccessor.time_dt_accessor        141μs
[ 16.67%] ··· Running ...DatetimeAccessor.time_dt_accessor_normalize     15.5ms
[ 19.05%] ··· Running timeseries.DatetimeIndex.time_add_timedelta            ok
[ 19.05%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       1.09ms 
                 repeated    6.01ms 
                 tz_aware    5.13ms 
                 tz_naive    5.09ms 
               ============ ========

[ 21.43%] ··· Running timeseries.DatetimeIndex.time_get                      ok
[ 21.43%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       66.7μs 
                 repeated    58.7μs 
                 tz_aware    91.8μs 
                 tz_naive    65.2μs 
               ============ ========

[ 23.81%] ··· Running timeseries.DatetimeIndex.time_normalize                ok
[ 23.81%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       743μs  
                 repeated    11.7ms 
                 tz_aware    52.3ms 
                 tz_naive    11.6ms 
               ============ ========

[ 26.19%] ··· Running ...atetimeIndex.time_timeseries_is_month_start         ok
[ 26.19%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       364μs  
                 repeated    6.08ms 
                 tz_aware    11.4ms 
                 tz_naive    6.24ms 
               ============ ========

[ 28.57%] ··· Running timeseries.DatetimeIndex.time_to_date                  ok
[ 28.57%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       18.1ms 
                 repeated    498ms  
                 tz_aware    1.98s  
                 tz_naive    503ms  
               ============ ========

[ 30.95%] ··· Running timeseries.DatetimeIndex.time_to_pydatetime            ok
[ 30.95%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       2.41ms 
                 repeated    64.7ms 
                 tz_aware    602ms  
                 tz_naive    67.2ms 
               ============ ========

[ 33.33%] ··· Running timeseries.DatetimeIndex.time_to_time                  ok
[ 33.33%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       19.0ms 
                 repeated    506ms  
                 tz_aware    2.00s  
                 tz_naive    509ms  
               ============ ========

[ 35.71%] ··· Running timeseries.DatetimeIndex.time_unique                   ok
[ 35.71%] ···· 
               ============ ========
                index_type          
               ------------ --------
                   dst       592μs  
                 repeated    2.21ms 
                 tz_aware    7.59ms 
                 tz_naive    8.03ms 
               ============ ========

[ 38.10%] ··· Running timeseries.Factorize.time_factorize                    ok
[ 38.10%] ···· 
               ============ ========
                    t               
               ------------ --------
                   None      27.6ms 
                Asia/Tokyo   28.8ms 
               ============ ========

[ 40.48%] ··· Running timeseries.InferFreq.time_infer_freq                   ok
[ 40.48%] ···· 
               ====== ========
                freq          
               ------ --------
                None   1.84ms 
                 D     1.84ms 
                 B     2.81ms 
               ====== ========

[ 42.86%] ··· Running timeseries.IrregularOps.time_add                    477ms
[ 45.24%] ··· Running timeseries.Iteration.time_iter                         ok
[ 45.24%] ···· 
               =========================================== =======
                                time_index                        
               ------------------------------------------- -------
                 <function date_range at 0x7f428622a050>    1.06s 
                <function period_range at 0x7f4285d5c2a8>   5.69s 
               =========================================== =======

[ 47.62%] ··· Running timeseries.Iteration.time_iter_preexit                 ok
[ 47.62%] ···· 
               =========================================== ========
                                time_index                         
               ------------------------------------------- --------
                 <function date_range at 0x7f428622a050>    23.4ms 
                <function period_range at 0x7f4285d5c2a8>   61.1ms 
               =========================================== ========

[ 50.00%] ··· Running timeseries.Lookup.time_lookup_and_cleanup          6.01ms
[ 52.38%] ··· Running timeseries.ResampleDataFrame.time_method               ok
[ 52.38%] ···· 
               ======== ========
                method          
               -------- --------
                 max     6.67ms 
                 mean    5.88ms 
                 min     6.60ms 
               ======== ========

[ 54.76%] ··· Running timeseries.ResampleDatetetime64.time_resample      7.28ms
[ 57.14%] ··· Running timeseries.ResampleSeries.time_resample                ok
[ 57.14%] ···· 
               ========== ====== ======== ========
               --                      method     
               ----------------- -----------------
                 index     freq    mean     ohlc  
               ========== ====== ======== ========
                 period    5min   31.0ms   34.2ms 
                 period     1D    25.2ms   26.4ms 
                datetime   5min   18.0ms   21.6ms 
                datetime    1D    12.2ms   13.5ms 
               ========== ====== ======== ========

[ 59.52%] ··· Running timeseries.ResetIndex.time_reest_datetimeindex         ok
[ 59.52%] ···· 
               ============ ========
                    t               
               ------------ --------
                   None      1.15ms 
                US/Eastern   1.34ms 
               ============ ========

[ 61.90%] ··· Running timeseries.SortIndex.time_get_slice                    ok
[ 61.90%] ···· 
               =========== =======
                monotonic         
               ----------- -------
                   True     322μs 
                  False     283μs 
               =========== =======

[ 64.29%] ··· Running timeseries.SortIndex.time_sort_index                   ok
[ 64.29%] ···· 
               =========== ========
                monotonic          
               ----------- --------
                   True     1.72ms 
                  False     17.8ms 
               =========== ========

[ 66.67%] ··· Running timeseries.TimeDatetimeConverter.time_convert      12.5ms
[ 69.05%] ··· Running ...s.ToDatetimeCache.time_dup_seconds_and_unit     failed
[ 69.05%] ···· 
               ======= ========
                cache          
               ------- --------
                 True   failed 
                False   failed 
               ======= ========

[ 69.05%] ····· 
                
                For parameters: True
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 377, in time_dup_seconds_and_unit
                    to_datetime(self.dup_numeric_seconds, unit='s', cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'
                
                For parameters: False
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 377, in time_dup_seconds_and_unit
                    to_datetime(self.dup_numeric_seconds, unit='s', cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'

[ 71.43%] ··· Running ...eries.ToDatetimeCache.time_dup_string_dates     failed
[ 71.43%] ···· 
               ======= ========
                cache          
               ------- --------
                 True   failed 
                False   failed 
               ======= ========

[ 71.43%] ····· 
                
                For parameters: True
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 380, in time_dup_string_dates
                    to_datetime(self.dup_string_dates, cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'
                
                For parameters: False
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 380, in time_dup_string_dates
                    to_datetime(self.dup_string_dates, cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'

[ 73.81%] ··· Running ...etimeCache.time_dup_string_dates_and_format     failed
[ 73.81%] ···· 
               ======= ========
                cache          
               ------- --------
                 True   failed 
                False   failed 
               ======= ========

[ 73.81%] ····· 
                
                For parameters: True
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 383, in time_dup_string_dates_and_format
                    to_datetime(self.dup_string_dates, format='%Y-%m-%d', cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'
                
                For parameters: False
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 383, in time_dup_string_dates_and_format
                    to_datetime(self.dup_string_dates, format='%Y-%m-%d', cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'

[ 76.19%] ··· Running ...atetimeCache.time_dup_string_tzoffset_dates     failed
[ 76.19%] ···· 
               ======= ========
                cache          
               ------- --------
                 True   failed 
                False   failed 
               ======= ========

[ 76.19%] ····· 
                
                For parameters: True
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 386, in time_dup_string_tzoffset_dates
                    to_datetime(self.dup_string_with_tz, cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'
                
                For parameters: False
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 386, in time_dup_string_tzoffset_dates
                    to_datetime(self.dup_string_with_tz, cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'

[ 78.57%] ··· Running ...oDatetimeCache.time_unique_seconds_and_unit     failed
[ 78.57%] ···· 
               ======= ========
                cache          
               ------- --------
                 True   failed 
                False   failed 
               ======= ========

[ 78.57%] ····· 
                
                For parameters: True
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 374, in time_unique_seconds_and_unit
                    to_datetime(self.unique_numeric_seconds, unit='s', cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'
                
                For parameters: False
                Traceback (most recent call last):
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 818, in <module>
                    commands[mode](args)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 795, in main_run
                    result = benchmark.do_run()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 349, in do_run
                    return self.run(*self._current_params)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 424, in run
                    samples, number = self.benchmark_timing(timer, repeat, warmup_time, number=number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 471, in benchmark_timing
                    timing = timer.timeit(number)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 202, in timeit
                    timing = self.inner(it, self.timer)
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/timeit.py", line 100, in inner
                    _func()
                  File "/home/matt/anaconda/envs/pandas_dev/lib/python2.7/site-packages/asv/benchmark.py", line 415, in <lambda>
                    func = lambda: self.func(*param)
                  File "/home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py", line 374, in time_unique_seconds_and_unit
                    to_datetime(self.unique_numeric_seconds, unit='s', cache=cache)
                TypeError: to_datetime() got an unexpected keyword argument 'cache'

[ 80.95%] ··· Running timeseries.ToDatetimeFormat.time_exact              2.02s
[ 83.33%] ··· Running timeseries.ToDatetimeFormat.time_no_exact           1.93s
[ 85.71%] ··· Running timeseries.ToDatetimeISO8601.time_iso8601          9.93ms
[ 88.10%] ··· Running ...eries.ToDatetimeISO8601.time_iso8601_format     10.2ms
[ 90.48%] ··· Running ...oDatetimeISO8601.time_iso8601_format_no_sep     9.67ms
[ 92.86%] ··· Running ...series.ToDatetimeISO8601.time_iso8601_nosep     9.84ms
[ 95.24%] ··· Running ...DatetimeISO8601.time_iso8601_tz_spaceformat      619ms
[ 97.62%] ··· Running ...ies.ToDatetimeYYYYMMDD.time_format_YYYYMMDD     15.1ms
[100.00%] ··· Running timeseries.TzLocalize.time_infer_dst               4.84ms
[100.00%] ····· /home/matt/Projects/pandas-mroeschke/asv_bench/benchmarks/timeseries.py:77: FutureWarning: the infer_dst=True keyword is deprecated, use ambiguous='infer' instead
                self.index.tz_localize('US/Eastern', infer_dst=True)
```


Labels:
name: Benchmark
description: Performance (ASV) benchmarks

Comments:
thanks!