RLS: 1.3.1 · Issue #42343 · pandas-dev/pandas (original) (raw)
Tracking issue for the 1.3.1 release.
before after ratio
[7c48ff44] [f00ed8f4]
<v1.2.5^0> <v1.3.0^0>
+ 2.43±0.03ms 28.4±1ms 11.66 indexing.InsertColumns.time_assign_list_like_with_setitem
+ 5.79±0.08ms 29.9±0.4ms 5.17 frame_methods.MaskBool.time_frame_mask_bools
+ 88.7±0.9μs 453±5μs 5.11 inference.ToTimedelta.time_convert_int
+ 82.6±2ms 386±1ms 4.67 frame_ctor.FromDicts.time_nested_dict_int64
+ 363±10μs 1.26±0.01ms 3.48 stat_ops.FrameOps.time_op('prod', 'int', 1)
+ 537±7μs 1.84±0.01ms 3.43 stat_ops.FrameOps.time_op('mean', 'int', 1)
+ 341±3μs 1.09±0.01ms 3.21 stat_ops.FrameOps.time_op('sum', 'int', 1)
+ 643±10μs 1.95±0.01ms 3.03 rolling.EWMMethods.time_ewm('Series', 1000, 'float', 'mean')
+ 626±6μs 1.88±0.03ms 3.00 rolling.EWMMethods.time_ewm('Series', 10, 'float', 'mean')
+ 678±9μs 2.00±0.04ms 2.95 rolling.EWMMethods.time_ewm('Series', 10, 'int', 'mean')
+ 696±10μs 2.01±0.01ms 2.89 rolling.EWMMethods.time_ewm('Series', 1000, 'int', 'mean')
+ 592±9μs 1.68±0.01ms 2.84 stat_ops.FrameOps.time_op('mean', 'int', 0)
+ 758±10μs 2.11±0.02ms 2.79 rolling.EWMMethods.time_ewm('DataFrame', 10, 'float', 'mean')
+ 1.34±0.01ms 3.73±0.1ms 2.78 stat_ops.FrameOps.time_op('std', 'int', 0)
+ 804±10μs 2.21±0.03ms 2.75 rolling.EWMMethods.time_ewm('DataFrame', 10, 'int', 'mean')
+ 479±4μs 1.32±0.04ms 2.75 stat_ops.FrameOps.time_op('sum', 'int', 0)
+ 213±4ns 583±8ns 2.74 tslibs.timestamp.TimestampProperties.time_freqstr(None, 'B')
+ 218±2ns 592±4ns 2.72 tslibs.timestamp.TimestampProperties.time_freqstr(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B')
+ 1.32±0.03ms 3.58±0.04ms 2.70 stat_ops.FrameOps.time_op('var', 'int', 0)
+ 221±2ns 595±9ns 2.69 tslibs.timestamp.TimestampProperties.time_freqstr(tzlocal(), 'B')
+ 216±2ns 582±6ns 2.69 tslibs.timestamp.TimestampProperties.time_freqstr(datetime.timezone(datetime.timedelta(seconds=3600)), 'B')
+ 212±4ns 567±10ns 2.68 tslibs.timestamp.TimestampProperties.time_freqstr(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B')