Closed
Description
I ran a full benchmark on a separate machine locally, comparing current master against 0.25.3.
Some identified cases:
- Indexing slowdown due to
extract_array, reproducer below at PERF: performance regression in 1.0 compared to 0.25 #30790 (comment) -
Index.__new__, reproducer below at PERF: performance regression in 1.0 compared to 0.25 #30790 (comment) - IntervalIndex (or all ExtensionIndex?) attribute access: PERF: regression in getattr for IntervalIndex #30742
-
asofdue to additional copy / take: DEPR: is_copy arg of take #30615
Full results:
before after ratio
[62a87bf4] [526b2f36]
<v0.25.3^0> <benchmarks-run>
+ 31.4±0.4ms 127±1ms 4.03 eval.Eval.time_chained_cmp('python', 'all')
+ 41.7±0.4ms 129±0.9ms 3.08 eval.Eval.time_chained_cmp('python', 1)
+ 12.5±0.04μs 37.1±0.2μs 2.98 indexing.NonNumericSeriesIndexing.time_getitem_scalar('string', 'non_monotonic')
+ 14.8±0.07μs 38.3±0.6μs 2.59 indexing.NonNumericSeriesIndexing.time_getitem_scalar('string', 'unique_monotonic_inc')
+ 87.8±8μs 220±20μs 2.50 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc')
+ 58.4±0.2μs 142±0.3μs 2.43 ctors.SeriesDtypesConstructors.time_index_from_array_string
+ 208±2μs 502±3μs 2.41 groupby.GroupByMethods.time_dtype_as_group('object', 'all', 'transformation')
+ 208±1μs 497±2μs 2.39 groupby.GroupByMethods.time_dtype_as_group('object', 'all', 'direct')
+ 210±0.7μs 499±7μs 2.38 groupby.GroupByMethods.time_dtype_as_group('object', 'any', 'transformation')
+ 209±2μs 496±3μs 2.37 groupby.GroupByMethods.time_dtype_as_group('object', 'any', 'direct')
+ 210±2μs 497±2μs 2.37 groupby.GroupByMethods.time_dtype_as_field('int', 'all', 'transformation')
+ 213±2μs 504±6μs 2.37 groupby.GroupByMethods.time_dtype_as_field('float', 'all', 'transformation')
+ 20.8±0.3μs 49.2±0.6μs 2.36 indexing.NonNumericSeriesIndexing.time_getitem_scalar('string', 'nonunique_monotonic_inc')
+ 210±1μs 497±4μs 2.36 groupby.GroupByMethods.time_dtype_as_field('int', 'all', 'direct')
+ 213±2μs 503±2μs 2.36 groupby.GroupByMethods.time_dtype_as_group('int', 'all', 'direct')
+ 214±3μs 504±2μs 2.36 groupby.GroupByMethods.time_dtype_as_group('int', 'all', 'transformation')
+ 213±2μs 500±3μs 2.35 groupby.GroupByMethods.time_dtype_as_field('float', 'all', 'direct')
+ 218±2μs 513±2μs 2.35 groupby.GroupByMethods.time_dtype_as_group('float', 'all', 'direct')
+ 215±1μs 505±2μs 2.35 groupby.GroupByMethods.time_dtype_as_group('int', 'any', 'direct')
+ 213±0.9μs 499±3μs 2.34 groupby.GroupByMethods.time_dtype_as_field('int', 'any', 'transformation')
+ 219±2μs 514±2μs 2.34 groupby.GroupByMethods.time_dtype_as_group('float', 'all', 'transformation')
+ 215±0.9μs 504±3μs 2.34 groupby.GroupByMethods.time_dtype_as_group('int', 'any', 'transformation')
+ 214±1μs 501±3μs 2.34 groupby.GroupByMethods.time_dtype_as_field('float', 'any', 'transformation')
+ 219±1μs 512±2μs 2.33 groupby.GroupByMethods.time_dtype_as_group('float', 'any', 'transformation')
+ 219±2μs 511±1μs 2.33 groupby.GroupByMethods.time_dtype_as_group('datetime', 'all', 'transformation')
+ 213±2μs 497±3μs 2.33 groupby.GroupByMethods.time_dtype_as_field('int', 'any', 'direct')
+ 220±2μs 514±2μs 2.33 groupby.GroupByMethods.time_dtype_as_group('datetime', 'any', 'direct')
+ 220±2μs 513±3μs 2.33 groupby.GroupByMethods.time_dtype_as_group('float', 'any', 'direct')
+ 221±2μs 512±4μs 2.32 groupby.GroupByMethods.time_dtype_as_group('datetime', 'any', 'transformation')
+ 216±2μs 500±2μs 2.32 groupby.GroupByMethods.time_dtype_as_field('float', 'any', 'direct')
+ 220±2μs 509±1μs 2.32 groupby.GroupByMethods.time_dtype_as_group('datetime', 'all', 'direct')
+ 217±1μs 498±2μs 2.30 groupby.GroupByMethods.time_dtype_as_field('datetime', 'all', 'direct')
+ 218±2μs 498±2μs 2.29 groupby.GroupByMethods.time_dtype_as_field('datetime', 'all', 'transformation')
+ 219±0.5μs 497±1μs 2.27 groupby.GroupByMethods.time_dtype_as_field('datetime', 'any', 'direct')
+ 218±0.6μs 496±0.9μs 2.27 groupby.GroupByMethods.time_dtype_as_field('datetime', 'any', 'transformation')
+ 583±3ms 1.32±0s 2.27 groupby.Apply.time_copy_overhead_single_col
+ 223±0.7μs 495±0.8μs 2.22 groupby.GroupByMethods.time_dtype_as_field('float', 'shift', 'direct')
+ 1.47±0.01s 3.26±0.01s 2.21 groupby.Apply.time_copy_function_multi_col
+ 223±1μs 494±0.6μs 2.21 groupby.GroupByMethods.time_dtype_as_field('float', 'shift', 'transformation')
+ 28.2±2ms 62.2±0.4ms 2.21 frame_methods.Apply.time_apply_ref_by_name
+ 7.63±0.2ms 16.8±0.1ms 2.20 timeseries.AsOf.time_asof('DataFrame')
+ 228±0.9μs 494±1μs 2.17 groupby.GroupByMethods.time_dtype_as_group('object', 'shift', 'direct')
+ 229±0.4μs 493±1μs 2.15 groupby.GroupByMethods.time_dtype_as_group('object', 'shift', 'transformation')
+ 237±1μs 509±0.2μs 2.14 groupby.GroupByMethods.time_dtype_as_group('float', 'shift', 'direct')
+ 238±0.4μs 509±0.6μs 2.14 groupby.GroupByMethods.time_dtype_as_group('float', 'shift', 'transformation')
+ 231±0.9μs 493±0.8μs 2.14 groupby.GroupByMethods.time_dtype_as_field('datetime', 'shift', 'transformation')
+ 234±5μs 500±1μs 2.14 groupby.GroupByMethods.time_dtype_as_group('datetime', 'shift', 'direct')
+ 231±0.9μs 491±0.5μs 2.13 groupby.GroupByMethods.time_dtype_as_field('datetime', 'shift', 'direct')
+ 236±3μs 499±2μs 2.12 groupby.GroupByMethods.time_dtype_as_group('datetime', 'shift', 'transformation')
+ 250±0.4μs 511±1μs 2.05 groupby.GroupByMethods.time_dtype_as_field('int', 'shift', 'direct')
+ 253±0.5μs 517±1μs 2.04 groupby.GroupByMethods.time_dtype_as_group('int', 'shift', 'transformation')
+ 250±0.6μs 509±0.5μs 2.03 groupby.GroupByMethods.time_dtype_as_field('int', 'shift', 'transformation')
+ 255±2μs 517±2μs 2.03 groupby.GroupByMethods.time_dtype_as_group('int', 'shift', 'direct')
+ 2.16±0ms 4.32±0.3ms 2.00 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'sum')
+ 285±3μs 566±7μs 1.99 groupby.GroupByMethods.time_dtype_as_field('datetime', 'last', 'transformation')
+ 2.17±0.02ms 4.30±0.7ms 1.99 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'sum')
+ 285±3μs 564±2μs 1.97 groupby.GroupByMethods.time_dtype_as_field('datetime', 'last', 'direct')
+ 296±0.9μs 577±3μs 1.94 groupby.GroupByMethods.time_dtype_as_field('datetime', 'first', 'transformation')
+ 25.3±0.2μs 49.2±0.4μs 1.94 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc')
+ 2.29±0.01ms 4.46±0.3ms 1.94 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'mean')
+ 298±2μs 577±1μs 1.93 groupby.GroupByMethods.time_dtype_as_field('datetime', 'first', 'direct')
+ 2.30±0.04ms 4.43±0.6ms 1.93 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'mean')
+ 285±1μs 545±0.4μs 1.91 groupby.GroupByMethods.time_dtype_as_group('object', 'bfill', 'direct')
+ 285±1μs 544±2μs 1.91 groupby.GroupByMethods.time_dtype_as_group('object', 'ffill', 'direct')
+ 285±1μs 544±1μs 1.91 groupby.GroupByMethods.time_dtype_as_group('object', 'bfill', 'transformation')
+ 286±0.5μs 545±0.8μs 1.91 groupby.GroupByMethods.time_dtype_as_group('object', 'ffill', 'transformation')
+ 290±1μs 552±2μs 1.90 groupby.GroupByMethods.time_dtype_as_group('datetime', 'ffill', 'transformation')
+ 289±2μs 551±1μs 1.90 groupby.GroupByMethods.time_dtype_as_group('datetime', 'bfill', 'transformation')
+ 289±3μs 548±0.8μs 1.90 groupby.GroupByMethods.time_dtype_as_group('datetime', 'bfill', 'direct')
+ 290±0.6μs 549±0.6μs 1.90 groupby.GroupByMethods.time_dtype_as_group('datetime', 'ffill', 'direct')
+ 2.96±0.2ms 5.50±0.4ms 1.86 rolling.ExpandingMethods.time_expanding('Series', 'int', 'sum')
+ 312±3μs 572±1μs 1.83 groupby.GroupByMethods.time_dtype_as_field('datetime', 'max', 'transformation')
+ 311±2μs 569±3μs 1.83 groupby.GroupByMethods.time_dtype_as_field('datetime', 'max', 'direct')
+ 327±3μs 599±10μs 1.83 groupby.GroupByMethods.time_dtype_as_field('float', 'last', 'direct')
+ 330±2μs 596±2μs 1.81 groupby.GroupByMethods.time_dtype_as_field('float', 'last', 'transformation')
+ 327±1μs 583±0.9μs 1.78 groupby.GroupByMethods.time_dtype_as_field('datetime', 'min', 'direct')
+ 326±1μs 582±2μs 1.78 groupby.GroupByMethods.time_dtype_as_field('datetime', 'min', 'transformation')
+ 3.24±0.2ms 5.72±0.4ms 1.76 rolling.ExpandingMethods.time_expanding('Series', 'int', 'mean')
+ 345±3μs 607±3μs 1.76 groupby.GroupByMethods.time_dtype_as_field('float', 'first', 'transformation')
+ 347±2μs 610±3μs 1.76 groupby.GroupByMethods.time_dtype_as_field('float', 'first', 'direct')
+ 3.32±0.04ms 5.77±0.4ms 1.74 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'kurt')
+ 2.19±0.01ms 3.80±0.07ms 1.73 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'nearest')
+ 1.98±0.02ms 3.44±0.4ms 1.73 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'sum')
+ 2.19±0.01ms 3.79±0.02ms 1.73 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'lower')
+ 2.20±0.01ms 3.79±0.02ms 1.73 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'linear')
+ 2.19±0.02ms 3.79±0.1ms 1.73 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'higher')
+ 2.20±0.01ms 3.79±0ms 1.73 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'lower')
+ 2.20±0.01ms 3.79±0.02ms 1.72 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'higher')
+ 2.19±0.01ms 3.77±0.01ms 1.72 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'midpoint')
+ 3.37±0.07ms 5.79±0.5ms 1.72 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'kurt')
+ 2.20±0.02ms 3.78±0.08ms 1.72 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'linear')
+ 2.20±0.01ms 3.78±0.01ms 1.72 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'midpoint')
+ 2.20±0.01ms 3.77±0.01ms 1.72 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'nearest')
+ 2.18±0ms 3.74±0.07ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'nearest')
+ 355±2μs 608±4μs 1.71 groupby.GroupByMethods.time_dtype_as_field('float', 'sum', 'transformation')
+ 2.17±0ms 3.72±0.07ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'midpoint')
+ 2.18±0.01ms 3.73±0.1ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'higher')
+ 2.18±0.01ms 3.73±0.09ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'midpoint')
+ 354±2μs 606±1μs 1.71 groupby.GroupByMethods.time_dtype_as_field('float', 'sum', 'direct')
+ 3.24±0.2ms 5.54±0.4ms 1.71 rolling.Methods.time_rolling('Series', 1000, 'int', 'sum')
+ 390±0.8μs 666±1μs 1.71 groupby.GroupByMethods.time_dtype_as_field('float', 'ffill', 'transformation')
+ 2.18±0.01ms 3.72±0.1ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'linear')
+ 2.18±0.01ms 3.71±0.08ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'linear')
+ 2.18±0.01ms 3.73±0.08ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'lower')
+ 2.18±0ms 3.72±0.07ms 1.71 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'higher')
+ 355±2μs 606±4μs 1.70 groupby.GroupByMethods.time_dtype_as_field('float', 'mean', 'direct')
+ 2.18±0.01ms 3.71±0.07ms 1.70 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'nearest')
+ 356±0.6μs 606±2μs 1.70 groupby.GroupByMethods.time_dtype_as_field('float', 'mean', 'transformation')
+ 2.18±0.01ms 3.71±0.08ms 1.70 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'lower')
+ 389±0.8μs 662±1μs 1.70 groupby.GroupByMethods.time_dtype_as_field('float', 'bfill', 'transformation')
+ 357±1μs 607±2μs 1.70 groupby.GroupByMethods.time_dtype_as_field('float', 'prod', 'direct')
+ 390±0.9μs 662±2μs 1.70 groupby.GroupByMethods.time_dtype_as_field('float', 'ffill', 'direct')
+ 390±0.6μs 661±2μs 1.70 groupby.GroupByMethods.time_dtype_as_field('float', 'bfill', 'direct')
+ 3.28±0.06ms 5.55±0.5ms 1.69 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'skew')
+ 3.36±0.2ms 5.68±0.4ms 1.69 rolling.Methods.time_rolling('Series', 1000, 'int', 'mean')
+ 352±0.5μs 595±0.4μs 1.69 groupby.GroupByMethods.time_dtype_as_field('object', 'shift', 'transformation')
+ 359±2μs 605±3μs 1.69 groupby.GroupByMethods.time_dtype_as_field('float', 'prod', 'transformation')
+ 352±0.9μs 594±2μs 1.69 groupby.GroupByMethods.time_dtype_as_field('object', 'shift', 'direct')
+ 368±2μs 619±2μs 1.68 groupby.GroupByMethods.time_dtype_as_field('float', 'var', 'transformation')
+ 366±2μs 616±4μs 1.68 groupby.GroupByMethods.time_dtype_as_field('float', 'min', 'transformation')
+ 369±2μs 620±0.8μs 1.68 groupby.GroupByMethods.time_dtype_as_field('float', 'var', 'direct')
+ 366±1μs 612±1μs 1.67 groupby.GroupByMethods.time_dtype_as_field('float', 'min', 'direct')
+ 364±0.7μs 608±2μs 1.67 groupby.GroupByMethods.time_dtype_as_field('float', 'max', 'transformation')
+ 364±1μs 607±2μs 1.67 groupby.GroupByMethods.time_dtype_as_field('float', 'max', 'direct')
+ 395±0.5μs 659±0.8μs 1.67 groupby.GroupByMethods.time_dtype_as_field('datetime', 'bfill', 'direct')
+ 395±0.7μs 659±2μs 1.67 groupby.GroupByMethods.time_dtype_as_field('datetime', 'ffill', 'direct')
+ 394±0.6μs 657±2μs 1.67 groupby.GroupByMethods.time_dtype_as_field('datetime', 'bfill', 'transformation')
+ 395±0.1μs 655±1μs 1.66 groupby.GroupByMethods.time_dtype_as_field('datetime', 'ffill', 'transformation')
+ 392±1μs 649±1μs 1.65 groupby.GroupByMethods.time_dtype_as_group('object', 'last', 'transformation')
+ 393±2μs 650±1μs 1.65 groupby.GroupByMethods.time_dtype_as_group('object', 'last', 'direct')
+ 392±3μs 646±3μs 1.65 groupby.GroupByMethods.time_dtype_as_field('float', 'median', 'transformation')
+ 391±2μs 644±2μs 1.65 groupby.GroupByMethods.time_dtype_as_field('float', 'median', 'direct')
+ 3.86±0.1ms 6.34±0.03ms 1.64 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'count')
+ 397±0.6μs 652±2μs 1.64 groupby.GroupByMethods.time_dtype_as_group('object', 'first', 'transformation')
+ 410±0.5μs 671±2μs 1.64 groupby.GroupByMethods.time_dtype_as_group('int', 'last', 'transformation')
+ 410±2μs 670±1μs 1.63 groupby.GroupByMethods.time_dtype_as_group('int', 'last', 'direct')
+ 398±1μs 650±1μs 1.63 groupby.GroupByMethods.time_dtype_as_group('object', 'first', 'direct')
+ 421±1μs 688±0.8μs 1.63 groupby.GroupByMethods.time_dtype_as_group('float', 'last', 'transformation')
+ 2.87±0.2ms 4.68±0.3ms 1.63 rolling.ExpandingMethods.time_expanding('Series', 'float', 'sum')
+ 422±2μs 688±1μs 1.63 groupby.GroupByMethods.time_dtype_as_group('float', 'last', 'direct')
+ 419±2μs 684±3μs 1.63 groupby.GroupByMethods.time_dtype_as_group('datetime', 'last', 'direct')
+ 404±2μs 658±2μs 1.63 groupby.GroupByMethods.time_dtype_as_field('int', 'last', 'direct')
+ 418±1μs 682±3μs 1.63 groupby.GroupByMethods.time_dtype_as_group('datetime', 'last', 'transformation')
+ 405±2μs 659±2μs 1.63 groupby.GroupByMethods.time_dtype_as_field('int', 'last', 'transformation')
+ 421±2μs 684±2μs 1.62 groupby.GroupByMethods.time_dtype_as_group('datetime', 'first', 'direct')
+ 422±0.8μs 681±2μs 1.61 groupby.GroupByMethods.time_dtype_as_group('datetime', 'first', 'transformation')
+ 7.11±0.09ms 11.4±0.3ms 1.61 timeseries.AsOf.time_asof_nan('DataFrame')
+ 429±2μs 686±1μs 1.60 groupby.GroupByMethods.time_dtype_as_group('float', 'first', 'direct')
+ 420±1μs 671±0.8μs 1.60 groupby.GroupByMethods.time_dtype_as_field('int', 'first', 'transformation')
+ 421±0.9μs 672±1μs 1.60 groupby.GroupByMethods.time_dtype_as_field('int', 'first', 'direct')
+ 427±0.7μs 681±1μs 1.60 groupby.GroupByMethods.time_dtype_as_group('int', 'first', 'transformation')
+ 427±1μs 681±2μs 1.59 groupby.GroupByMethods.time_dtype_as_group('int', 'first', 'direct')
+ 430±3μs 687±0.7μs 1.59 groupby.GroupByMethods.time_dtype_as_group('float', 'first', 'transformation')
+ 448±1μs 708±2μs 1.58 groupby.GroupByMethods.time_dtype_as_group('float', 'ffill', 'transformation')
+ 449±0.7μs 708±2μs 1.58 groupby.GroupByMethods.time_dtype_as_group('float', 'bfill', 'direct')
+ 448±1μs 706±1μs 1.58 groupby.GroupByMethods.time_dtype_as_group('float', 'bfill', 'transformation')
+ 449±1μs 706±2μs 1.57 groupby.GroupByMethods.time_dtype_as_group('float', 'ffill', 'direct')
+ 2.02±0.02ms 3.17±0.6ms 1.57 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'sum')
+ 453±2μs 710±3μs 1.57 groupby.GroupByMethods.time_dtype_as_group('int', 'bfill', 'direct')
+ 452±2μs 707±1μs 1.57 groupby.GroupByMethods.time_dtype_as_group('int', 'ffill', 'direct')
+ 3.85±0.06ms 6.02±0.02ms 1.56 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'count')
+ 450±1μs 703±0.9μs 1.56 groupby.GroupByMethods.time_dtype_as_field('int', 'bfill', 'transformation')
+ 449±1μs 700±1μs 1.56 groupby.GroupByMethods.time_dtype_as_field('int', 'ffill', 'transformation')
+ 3.91±0.07ms 6.09±0.06ms 1.56 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'count')
+ 452±2μs 705±2μs 1.56 groupby.GroupByMethods.time_dtype_as_group('int', 'bfill', 'transformation')
+ 453±2μs 706±2μs 1.56 groupby.GroupByMethods.time_dtype_as_group('int', 'ffill', 'transformation')
+ 450±1μs 700±1μs 1.56 groupby.GroupByMethods.time_dtype_as_field('int', 'bfill', 'direct')
+ 4.12±0.1ms 6.41±0.04ms 1.55 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'count')
+ 450±1μs 700±0.9μs 1.55 groupby.GroupByMethods.time_dtype_as_field('int', 'ffill', 'direct')
+ 3.16±0.02ms 4.91±0.09ms 1.55 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'min')
+ 4.04±0.06ms 6.27±0.1ms 1.55 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'count')
+ 3.11±0.01ms 4.81±0.08ms 1.55 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 1, 'higher')
+ 447±1μs 691±1μs 1.55 groupby.GroupByMethods.time_dtype_as_group('float', 'max', 'direct')
+ 3.11±0.01ms 4.81±0.08ms 1.55 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 1, 'linear')
+ 446±0.9μs 689±0.9μs 1.55 groupby.GroupByMethods.time_dtype_as_group('float', 'max', 'transformation')
+ 521±1μs 805±2μs 1.54 groupby.GroupByMethods.time_dtype_as_field('datetime', 'quantile', 'transformation')
+ 446±2μs 688±2μs 1.54 groupby.GroupByMethods.time_dtype_as_group('datetime', 'min', 'transformation')
+ 3.17±0.01ms 4.89±0.08ms 1.54 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'max')
+ 448±0.8μs 690±0.4μs 1.54 groupby.GroupByMethods.time_dtype_as_group('float', 'min', 'transformation')
+ 448±1μs 691±1μs 1.54 groupby.GroupByMethods.time_dtype_as_group('float', 'min', 'direct')
+ 1.83±0.01ms 2.83±0.3ms 1.54 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'sum')
+ 3.13±0.02ms 4.82±0.06ms 1.54 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0, 'lower')
+ 442±0.5μs 680±0.4μs 1.54 groupby.GroupByMethods.time_dtype_as_group('int', 'max', 'transformation')
+ 3.10±0.02ms 4.76±0.08ms 1.54 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'max')
+ 444±0.7μs 682±1μs 1.53 groupby.GroupByMethods.time_dtype_as_group('int', 'min', 'transformation')
+ 13.7±0.9μs 21.1±0.2μs 1.53 algorithms.MaybeConvertObjects.time_maybe_convert_objects
+ 441±0.8μs 676±0.8μs 1.53 groupby.GroupByMethods.time_dtype_as_field('int', 'max', 'direct')
+ 442±0.8μs 679±0.7μs 1.53 groupby.GroupByMethods.time_dtype_as_group('int', 'max', 'direct')
+ 448±2μs 687±2μs 1.53 groupby.GroupByMethods.time_dtype_as_group('datetime', 'min', 'direct')
+ 3.13±0.01ms 4.80±0.07ms 1.53 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0, 'midpoint')
+ 4.08±0.06ms 6.26±0.1ms 1.53 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'count')
+ 524±2μs 803±2μs 1.53 groupby.GroupByMethods.time_dtype_as_field('datetime', 'quantile', 'direct')
+ 479±1μs 735±0.2μs 1.53 groupby.GroupByMethods.time_dtype_as_field('int', 'var', 'transformation')
+ 3.13±0.01ms 4.80±0.07ms 1.53 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0, 'linear')
+ 3.10±0.01ms 4.76±0.07ms 1.53 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 1, 'lower')
+ 447±0.4μs 685±2μs 1.53 groupby.GroupByMethods.time_dtype_as_group('datetime', 'max', 'transformation')
+ 3.13±0.01ms 4.79±0.08ms 1.53 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0, 'nearest')
+ 443±0.7μs 678±1μs 1.53 groupby.GroupByMethods.time_dtype_as_field('int', 'min', 'transformation')
+ 445±0.7μs 681±0.9μs 1.53 groupby.GroupByMethods.time_dtype_as_group('int', 'min', 'direct')
+ 3.13±0.01ms 4.79±0.06ms 1.53 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0, 'higher')
+ 443±0.5μs 677±1μs 1.53 groupby.GroupByMethods.time_dtype_as_field('int', 'min', 'direct')
+ 3.11±0.01ms 4.76±0.09ms 1.53 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 1, 'midpoint')
+ 447±2μs 683±1μs 1.53 groupby.GroupByMethods.time_dtype_as_group('datetime', 'max', 'direct')
+ 3.14±0.03ms 4.79±0.09ms 1.53 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'min')
+ 3.12±0.01ms 4.75±0.08ms 1.52 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 1, 'nearest')
+ 3.28±0.02ms 4.99±0.09ms 1.52 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'max')
+ 3.29±0.05ms 5.01±0.1ms 1.52 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'min')
+ 4.40±0.3ms 6.68±0.4ms 1.52 rolling.ExpandingMethods.time_expanding('Series', 'int', 'kurt')
+ 18.8±0.2μs 28.6±0.3μs 1.52 categoricals.CategoricalSlicing.time_getitem_list_like('monotonic_incr')
+ 444±1μs 674±2μs 1.52 groupby.GroupByMethods.time_dtype_as_field('int', 'max', 'transformation')
+ 481±3μs 731±2μs 1.52 groupby.GroupByMethods.time_dtype_as_field('int', 'var', 'direct')
+ 497±3μs 753±2μs 1.52 groupby.GroupByMethods.time_dtype_as_group('float', 'var', 'transformation')
+ 19.0±0.4μs 28.8±0.3μs 1.51 categoricals.CategoricalSlicing.time_getitem_list_like('monotonic_decr')
+ 497±3μs 753±2μs 1.51 groupby.GroupByMethods.time_dtype_as_group('float', 'var', 'direct')
+ 2.17±0.02ms 3.28±0.6ms 1.51 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'mean')
+ 3.26±0.01ms 4.90±0.01ms 1.51 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'min')
+ 3.24±0.01ms 4.87±0.02ms 1.50 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'max')
+ 19.1±0.5μs 28.6±0.2μs 1.50 categoricals.CategoricalSlicing.time_getitem_list_like('non_monotonic')
+ 2.02±0.04ms 3.03±0.4ms 1.50 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'sum')
+ 3.28±0.01ms 4.91±0.01ms 1.50 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'max')
+ 106±0.5μs 158±1μs 1.50 timeseries.SortIndex.time_sort_index(True)
+ 3.33±0.05ms 4.96±0.01ms 1.49 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'min')
+ 3.16±0.01ms 4.70±0.01ms 1.49 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'max')
+ 3.16±0.02ms 4.70±0.02ms 1.49 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'midpoint')
+ 3.17±0.01ms 4.70±0.03ms 1.48 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'lower')
+ 3.17±0.01ms 4.70±0.03ms 1.48 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'linear')
+ 3.16±0.01ms 4.69±0.02ms 1.48 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'higher')
+ 4.55±0.3ms 6.73±0.4ms 1.48 rolling.Methods.time_rolling('Series', 1000, 'int', 'kurt')
+ 3.14±0.2ms 4.65±0.3ms 1.48 rolling.Methods.time_rolling('Series', 10, 'float', 'sum')
+ 2.18±0.03ms 3.23±0.2ms 1.48 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'mean')
+ 3.21±0.01ms 4.74±0.01ms 1.48 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'min')
+ 3.17±0.02ms 4.69±0.02ms 1.48 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'nearest')
+ 3.22±0.02ms 4.75±0.02ms 1.47 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'midpoint')
+ 3.14±0.2ms 4.62±0.3ms 1.47 rolling.Methods.time_rolling('Series', 1000, 'float', 'sum')
+ 3.22±0.02ms 4.75±0.03ms 1.47 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'nearest')
+ 3.22±0.02ms 4.73±0.02ms 1.47 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'linear')
+ 585±2μs 859±3μs 1.47 multiindex_object.Values.time_datetime_level_values_sliced
+ 3.23±0.01ms 4.74±0.02ms 1.47 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'higher')
+ 3.22±0.02ms 4.72±0.01ms 1.46 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'lower')
+ 4.56±0.3ms 6.67±0.4ms 1.46 rolling.ExpandingMethods.time_expanding('Series', 'int', 'skew')
+ 2.16±0.04ms 3.16±0.7ms 1.46 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'mean')
+ 3.27±0.2ms 4.78±0.3ms 1.46 rolling.Methods.time_rolling('Series', 10, 'float', 'mean')
+ 538±3μs 786±3μs 1.46 groupby.GroupByMethods.time_dtype_as_field('float', 'std', 'direct')
+ 2.03±0.01ms 2.96±0.4ms 1.46 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'mean')
+ 541±2μs 787±4μs 1.46 groupby.GroupByMethods.time_dtype_as_field('float', 'std', 'transformation')
+ 3.31±0.05ms 4.82±0.8ms 1.45 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'skew')
+ 4.51±0.3ms 6.55±0.4ms 1.45 rolling.Methods.time_rolling('Series', 1000, 'int', 'skew')
+ 643±2μs 934±2μs 1.45 groupby.GroupByMethods.time_dtype_as_group('float', 'quantile', 'direct')
+ 645±2μs 936±2μs 1.45 groupby.GroupByMethods.time_dtype_as_group('float', 'quantile', 'transformation')
+ 3.23±0.2ms 4.69±0.4ms 1.45 rolling.Methods.time_rolling('Series', 10, 'int', 'sum')
+ 3.28±0.2ms 4.76±0.3ms 1.45 rolling.Methods.time_rolling('Series', 1000, 'float', 'mean')
+ 627±1μs 909±3μs 1.45 groupby.GroupByMethods.time_dtype_as_field('int', 'quantile', 'direct')
+ 628±0.7μs 911±2μs 1.45 groupby.GroupByMethods.time_dtype_as_field('int', 'quantile', 'transformation')
+ 638±1μs 924±3μs 1.45 groupby.GroupByMethods.time_dtype_as_group('int', 'quantile', 'direct')
+ 641±0.9μs 928±2μs 1.45 groupby.GroupByMethods.time_dtype_as_group('datetime', 'quantile', 'direct')
+ 641±1μs 926±1μs 1.45 groupby.GroupByMethods.time_dtype_as_group('datetime', 'quantile', 'transformation')
+ 638±2μs 921±3μs 1.44 groupby.GroupByMethods.time_dtype_as_group('int', 'quantile', 'transformation')
+ 633±1μs 914±5μs 1.44 groupby.GroupByMethods.time_dtype_as_field('float', 'quantile', 'direct')
+ 633±2μs 911±1μs 1.44 groupby.GroupByMethods.time_dtype_as_field('float', 'quantile', 'transformation')
+ 3.16±0.2ms 4.54±0.4ms 1.44 rolling.ExpandingMethods.time_expanding('Series', 'float', 'mean')
+ 3.36±0.2ms 4.83±0.4ms 1.44 rolling.Methods.time_rolling('Series', 10, 'int', 'mean')
+ 599±1μs 858±2μs 1.43 groupby.GroupByMethods.time_dtype_as_field('object', 'ffill', 'direct')
+ 598±1μs 856±3μs 1.43 groupby.GroupByMethods.time_dtype_as_field('object', 'bfill', 'direct')
+ 599±1μs 856±2μs 1.43 groupby.GroupByMethods.time_dtype_as_field('object', 'bfill', 'transformation')
+ 601±1μs 859±2μs 1.43 groupby.GroupByMethods.time_dtype_as_field('object', 'ffill', 'transformation')
+ 8.43±0.7ms 11.9±0.2ms 1.41 series_methods.NanOps.time_func('std', 1000000, 'float64')
+ 3.14±0.02ms 4.40±0.4ms 1.40 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'kurt')
+ 7.77±0.2ms 10.8±0.02ms 1.39 timeseries.ResampleSeries.time_resample('period', '5min', 'ohlc')
+ 651±3μs 900±2μs 1.38 groupby.GroupByMethods.time_dtype_as_field('int', 'std', 'direct')
+ 653±3μs 898±2μs 1.38 groupby.GroupByMethods.time_dtype_as_field('int', 'std', 'transformation')
+ 3.22±0.02ms 4.41±0.3ms 1.37 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'kurt')
+ 5.65±0.06ms 7.75±0.09ms 1.37 indexing.NonNumericSeriesIndexing.time_getitem_list_like('string', 'nonunique_monotonic_inc')
+ 679±2μs 930±3μs 1.37 groupby.GroupByMethods.time_dtype_as_group('float', 'std', 'transformation')
+ 681±3μs 930±3μs 1.37 groupby.GroupByMethods.time_dtype_as_group('float', 'std', 'direct')
+ 3.19±0.02ms 4.35±0.8ms 1.37 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'kurt')
+ 753±10μs 1.03±0.01ms 1.36 groupby.GroupByMethods.time_dtype_as_field('object', 'all', 'direct')
+ 752±10μs 1.02±0.01ms 1.36 groupby.GroupByMethods.time_dtype_as_field('object', 'all', 'transformation')
+ 756±10μs 1.03±0.01ms 1.36 groupby.GroupByMethods.time_dtype_as_field('object', 'any', 'direct')
+ 3.26±0.2ms 4.41±0.1ms 1.35 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'higher')
+ 3.26±0.2ms 4.40±0.09ms 1.35 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'higher')
+ 761±7μs 1.03±0.01ms 1.35 groupby.GroupByMethods.time_dtype_as_field('object', 'any', 'transformation')
+ 3.27±0.2ms 4.40±0.1ms 1.35 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'midpoint')
+ 3.26±0.2ms 4.39±0.1ms 1.35 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'lower')
+ 3.26±0.2ms 4.39±0.1ms 1.35 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'nearest')
+ 6.49±0.09ms 8.73±0.2ms 1.35 timeseries.ResampleSeries.time_resample('period', '1D', 'ohlc')
+ 3.26±0.2ms 4.38±0.1ms 1.34 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'linear')
+ 3.32±0.04ms 4.46±0.4ms 1.34 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'skew')
+ 3.81±0.03ms 5.11±0.1ms 1.34 rolling.ExpandingMethods.time_expanding('Series', 'int', 'std')
+ 3.26±0.2ms 4.38±0.1ms 1.34 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'linear')
+ 3.00±0.01ms 4.03±0.2ms 1.34 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'kurt')
+ 3.29±0.2ms 4.40±0.1ms 1.34 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'nearest')
+ 3.24±0.2ms 4.33±0.05ms 1.34 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'linear')
+ 16.5±0.06μs 22.0±0.3μs 1.34 categoricals.CategoricalSlicing.time_getitem_slice('monotonic_decr')
+ 3.29±0.2ms 4.40±0.1ms 1.34 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'midpoint')
+ 3.25±0.2ms 4.33±0.05ms 1.34 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'lower')
+ 4.45±0.3ms 5.94±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'nearest')
+ 4.45±0.3ms 5.93±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'linear')
+ 4.45±0.3ms 5.91±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'higher')
+ 1.04±0.01ms 1.39±0.01ms 1.33 ctors.SeriesConstructors.time_series_constructor(<class 'list'>, False, 'float')
+ 3.29±0.2ms 4.37±0.06ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'nearest')
+ 3.25±0.2ms 4.32±0.05ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'midpoint')
+ 1.09±0.01ms 1.45±0.01ms 1.33 ctors.SeriesConstructors.time_series_constructor(<class 'list'>, True, 'float')
+ 4.50±0.3ms 5.97±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'linear')
+ 3.31±0.2ms 4.39±0.1ms 1.33 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'lower')
+ 4.45±0.3ms 5.91±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'lower')
+ 3.25±0.3ms 4.32±0.06ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'midpoint')
+ 3.25±0.2ms 4.31±0.05ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'linear')
+ 3.25±0.2ms 4.32±0.05ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'higher')
+ 4.49±0.3ms 5.97±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'higher')
+ 3.26±0.2ms 4.32±0.05ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'nearest')
+ 25.2±0.4ms 33.4±0.4ms 1.33 io.hdf.HDF.time_read_hdf('fixed')
+ 4.45±0.3ms 5.90±0.4ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'midpoint')
+ 4.51±0.3ms 5.98±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'nearest')
+ 4.51±0.3ms 5.98±0.3ms 1.33 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'midpoint')
+ 5.98±0.01ms 7.92±0.1ms 1.32 indexing.NonNumericSeriesIndexing.time_getitem_list_like('string', 'non_monotonic')
+ 3.25±0.2ms 4.31±0.05ms 1.32 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'lower')
+ 3.15±0.03ms 4.17±0.3ms 1.32 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'skew')
+ 3.14±0.02ms 4.15±0.8ms 1.32 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'skew')
+ 4.52±0.3ms 5.97±0.3ms 1.32 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'lower')
+ 5.94±0.06ms 7.85±0.1ms 1.32 indexing.NonNumericSeriesIndexing.time_getitem_list_like('string', 'unique_monotonic_inc')
+ 4.56±0.3ms 6.01±0.4ms 1.32 rolling.Methods.time_rolling('Series', 10, 'int', 'kurt')
+ 3.28±0.2ms 4.32±0.05ms 1.32 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'higher')
+ 17.0±0.2μs 22.4±0.2μs 1.32 categoricals.CategoricalSlicing.time_getitem_slice('non_monotonic')
+ 16.8±0.09μs 22.0±0.4μs 1.31 categoricals.CategoricalSlicing.time_getitem_slice('monotonic_incr')
+ 540±5μs 708±9μs 1.31 period.Indexing.time_intersection
+ 4.29±0.3ms 5.62±0.4ms 1.31 rolling.ExpandingMethods.time_expanding('Series', 'float', 'kurt')
+ 4.39±0.3ms 5.71±0.1ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'nearest')
+ 4.40±0.3ms 5.71±0.2ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'lower')
+ 976±6μs 1.27±0.01ms 1.30 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'nonunique_monotonic_inc')
+ 4.37±0.3ms 5.68±0.1ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'nearest')
+ 962±10μs 1.25±0.02ms 1.30 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'non_monotonic')
+ 4.37±0.3ms 5.68±0.3ms 1.30 rolling.Methods.time_rolling('Series', 10, 'float', 'max')
+ 4.38±0.3ms 5.68±0.1ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'higher')
+ 4.40±0.3ms 5.71±0.1ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'linear')
+ 4.39±0.3ms 5.70±0.1ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'midpoint')
+ 684±3μs 887±2μs 1.30 groupby.GroupByMethods.time_dtype_as_field('object', 'first', 'direct')
+ 4.38±0.3ms 5.68±0.09ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'linear')
+ 4.38±0.3ms 5.67±0.1ms 1.30 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'midpoint')
+ 4.38±0.3ms 5.67±0.1ms 1.29 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'lower')
+ 4.41±0.3ms 5.70±0.1ms 1.29 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'higher')
+ 6.20±0.07μs 7.99±0.1μs 1.29 categoricals.Indexing.time_get_loc
+ 1.24±0ms 1.59±0.01ms 1.29 frame_methods.Quantile.time_frame_quantile(1)
+ 1.89±0ms 2.43±0.01ms 1.29 groupby.GroupByMethods.time_dtype_as_field('float', 'pct_change', 'direct')
+ 685±5μs 882±2μs 1.29 groupby.GroupByMethods.time_dtype_as_field('object', 'first', 'transformation')
+ 37.5±0.3ms 48.3±0.6ms 1.29 frame_ctor.FromDicts.time_nested_dict_index
+ 679±3μs 873±3μs 1.29 groupby.GroupByMethods.time_dtype_as_field('object', 'last', 'direct')
+ 1.89±0ms 2.43±0.01ms 1.29 groupby.GroupByMethods.time_dtype_as_field('float', 'pct_change', 'transformation')
+ 405±2μs 521±3μs 1.29 index_object.IntervalIndexMethod.time_intersection(1000)
+ 291±3μs 373±2μs 1.28 join_merge.Concat.time_concat_empty_left(1)
+ 679±4μs 872±3μs 1.28 groupby.GroupByMethods.time_dtype_as_field('object', 'last', 'transformation')
+ 4.39±0.3ms 5.63±0.2ms 1.28 rolling.Methods.time_rolling('Series', 10, 'float', 'min')
+ 422±3μs 539±1μs 1.28 index_object.IntervalIndexMethod.time_intersection_one_duplicate(1000)
+ 292±3μs 373±2μs 1.28 join_merge.Concat.time_concat_empty_right(1)
+ 980±9μs 1.25±0.01ms 1.28 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'unique_monotonic_inc')
+ 904±6μs 1.15±0.01ms 1.27 stat_ops.SeriesOps.time_op('std', 'float')
+ 463±0.2ns 589±9ns 1.27 indexing.MethodLookup.time_lookup_iloc
+ 3.17±0.01ms 4.04±0.2ms 1.27 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'skew')
+ 689±2μs 874±1μs 1.27 groupby.GroupByMethods.time_dtype_as_field('int', 'prod', 'direct')
+ 4.51±0.3ms 5.72±0.4ms 1.27 rolling.Methods.time_rolling('Series', 10, 'int', 'skew')
+ 691±4μs 875±3μs 1.27 groupby.GroupByMethods.time_dtype_as_field('int', 'mean', 'direct')
+ 37.8±0.1ms 47.8±0.7ms 1.27 frame_ctor.FromDicts.time_nested_dict_index_columns
+ 831±6μs 1.05±0ms 1.27 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'non_monotonic')
+ 4.44±0.3ms 5.61±0.07ms 1.26 rolling.Methods.time_rolling('Series', 1000, 'float', 'max')
+ 689±3μs 871±2μs 1.26 groupby.GroupByMethods.time_dtype_as_field('int', 'prod', 'transformation')
+ 703±1μs 888±2μs 1.26 groupby.GroupByMethods.time_dtype_as_group('int', 'mean', 'transformation')
+ 691±2μs 873±2μs 1.26 groupby.GroupByMethods.time_dtype_as_field('int', 'mean', 'transformation')
+ 739±2μs 933±4μs 1.26 groupby.GroupByMethods.time_dtype_as_group('int', 'median', 'direct')
+ 829±5μs 1.05±0ms 1.26 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'unique_monotonic_inc')
+ 4.52±0.2ms 5.71±0.06ms 1.26 rolling.ExpandingMethods.time_expanding('Series', 'int', 'min')
+ 703±2μs 887±2μs 1.26 groupby.GroupByMethods.time_dtype_as_group('int', 'mean', 'direct')
+ 633±5μs 798±2μs 1.26 groupby.GroupByMethods.time_dtype_as_group('int', 'var', 'direct')
+ 4.49±0.3ms 5.66±0.08ms 1.26 rolling.Methods.time_rolling('Series', 1000, 'float', 'min')
+ 737±1μs 928±1μs 1.26 groupby.GroupByMethods.time_dtype_as_group('int', 'median', 'transformation')
+ 631±3μs 794±1μs 1.26 groupby.GroupByMethods.time_dtype_as_group('int', 'var', 'transformation')
+ 1.98±0.01ms 2.49±0ms 1.26 groupby.GroupByMethods.time_dtype_as_field('int', 'pct_change', 'direct')
+ 2.81±0.05ms 3.52±0.01ms 1.26 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'std')
+ 731±3μs 918±20μs 1.26 groupby.GroupByMethods.time_dtype_as_field('int', 'median', 'transformation')
+ 731±3μs 918±2μs 1.26 groupby.GroupByMethods.time_dtype_as_field('int', 'median', 'direct')
+ 4.48±0.3ms 5.62±0.2ms 1.25 rolling.Methods.time_rolling('Series', 10, 'int', 'min')
+ 4.52±0.2ms 5.67±0.07ms 1.25 rolling.ExpandingMethods.time_expanding('Series', 'int', 'max')
+ 1.98±0ms 2.48±0.01ms 1.25 groupby.GroupByMethods.time_dtype_as_field('int', 'pct_change', 'transformation')
+ 104±3μs 130±0.6μs 1.25 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
+ 2.07±0ms 2.58±0.01ms 1.25 groupby.GroupByMethods.time_dtype_as_group('int', 'pct_change', 'direct')
+ 4.47±0.3ms 5.59±0.4ms 1.25 rolling.Methods.time_rolling('Series', 10, 'float', 'kurt')
+ 4.46±0.2ms 5.58±0.2ms 1.25 rolling.ExpandingMethods.time_expanding('Series', 'float', 'max')
+ 725±1μs 906±1μs 1.25 timeseries.ResetIndex.time_reest_datetimeindex('US/Eastern')
+ 111±2ms 138±1ms 1.25 reshape.Cut.time_qcut_timedelta(1000)
+ 1.08±0.01ms 1.35±0.01ms 1.25 indexing.NonNumericSeriesIndexing.time_getitem_list_like('period', 'non_monotonic')
+ 2.06±0ms 2.57±0.01ms 1.25 groupby.GroupByMethods.time_dtype_as_group('int', 'pct_change', 'transformation')
+ 37.6±0.4ms 46.8±0.6ms 1.25 frame_ctor.FromDicts.time_list_of_dict
+ 1.18±0ms 1.47±0ms 1.24 groupby.GroupByMethods.time_dtype_as_field('float', 'sem', 'direct')
+ 53.3±0.3μs 66.3±0.6μs 1.24 indexing.CategoricalIndexIndexing.time_getitem_list_like('monotonic_decr')
+ 2.82±0.04ms 3.51±0.01ms 1.24 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'std')
+ 468±3ns 582±3ns 1.24 indexing.MethodLookup.time_lookup_loc
+ 53.7±0.5μs 66.7±0.4μs 1.24 indexing.CategoricalIndexIndexing.time_getitem_list_like('non_monotonic')
+ 4.46±0.3ms 5.54±0.4ms 1.24 rolling.Methods.time_rolling('Series', 1000, 'float', 'kurt')
+ 4.47±0.2ms 5.55±0.2ms 1.24 rolling.Methods.time_rolling('Series', 10, 'int', 'max')
+ 1.18±0ms 1.47±0.01ms 1.24 groupby.GroupByMethods.time_dtype_as_field('float', 'sem', 'transformation')
+ 2.21±0.01ms 2.75±0.01ms 1.24 groupby.GroupByMethods.time_dtype_as_group('float', 'pct_change', 'direct')
+ 2.22±0.01ms 2.75±0ms 1.24 groupby.GroupByMethods.time_dtype_as_group('float', 'pct_change', 'transformation')
+ 46.5±0.2ms 57.8±0.4ms 1.24 frame_ctor.FromDicts.time_nested_dict
+ 53.6±0.6μs 66.5±0.6μs 1.24 indexing.CategoricalIndexIndexing.time_getitem_list_like('monotonic_incr')
+ 4.48±0.3ms 5.55±0.2ms 1.24 rolling.ExpandingMethods.time_expanding('Series', 'float', 'min')
+ 739±1μs 916±2μs 1.24 groupby.GroupByMethods.time_dtype_as_group('int', 'sum', 'direct')
+ 36.5±0.8μs 45.2±0.2μs 1.24 indexing.CategoricalIndexIndexing.time_getitem_slice('monotonic_decr')
+ 774±2μs 958±3μs 1.24 groupby.GroupByMethods.time_dtype_as_group('float', 'median', 'direct')
+ 765±1μs 946±3μs 1.24 groupby.GroupByMethods.time_dtype_as_group('float', 'mean', 'transformation')
+ 12.6±0.3ms 15.5±0.08ms 1.24 io.hdf.HDFStoreDataFrame.time_query_store_table_wide
+ 4.47±0.3ms 5.52±0.4ms 1.24 rolling.ExpandingMethods.time_expanding('Series', 'float', 'skew')
+ 727±2μs 897±2μs 1.23 groupby.GroupByMethods.time_dtype_as_field('int', 'sum', 'transformation')
+ 75.4±0.8ms 93.0±0.2ms 1.23 reshape.Cut.time_qcut_datetime(1000)
+ 741±3μs 913±3μs 1.23 groupby.GroupByMethods.time_dtype_as_group('int', 'prod', 'direct')
+ 766±3μs 943±2μs 1.23 groupby.GroupByMethods.time_dtype_as_group('float', 'sum', 'transformation')
+ 743±2μs 914±1μs 1.23 groupby.GroupByMethods.time_dtype_as_group('int', 'sum', 'transformation')
+ 768±2μs 945±2μs 1.23 groupby.GroupByMethods.time_dtype_as_group('float', 'mean', 'direct')
+ 777±3μs 957±0.7μs 1.23 groupby.GroupByMethods.time_dtype_as_group('float', 'median', 'transformation')
+ 743±2μs 913±1μs 1.23 groupby.GroupByMethods.time_dtype_as_group('int', 'prod', 'transformation')
+ 3.31±0.03μs 4.06±0.03μs 1.23 categoricals.Contains.time_categorical_index_contains
+ 4.42±0.3ms 5.43±0.4ms 1.23 rolling.Methods.time_rolling('Series', 1000, 'float', 'skew')
+ 730±3μs 896±2μs 1.23 groupby.GroupByMethods.time_dtype_as_field('int', 'sum', 'direct')
+ 771±5μs 946±2μs 1.23 groupby.GroupByMethods.time_dtype_as_group('float', 'prod', 'direct')
+ 2.98±0.02ms 3.65±0.01ms 1.23 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'std')
+ 770±3μs 943±0.7μs 1.23 groupby.GroupByMethods.time_dtype_as_group('float', 'prod', 'transformation')
+ 156±1ms 191±0.3ms 1.22 inference.ToNumericDowncast.time_downcast('string-float', 'unsigned')
+ 1.29±0ms 1.58±0.01ms 1.22 groupby.GroupByMethods.time_dtype_as_field('int', 'sem', 'direct')
+ 4.43±0.3ms 5.42±0.4ms 1.22 rolling.Methods.time_rolling('Series', 10, 'float', 'skew')
+ 1.29±0ms 1.57±0.01ms 1.22 groupby.GroupByMethods.time_dtype_as_field('int', 'sem', 'transformation')
+ 770±9μs 941±2μs 1.22 groupby.GroupByMethods.time_dtype_as_group('float', 'sum', 'direct')
+ 4.51±0.3ms 5.51±0.1ms 1.22 rolling.Methods.time_rolling('Series', 1000, 'int', 'max')
+ 156±0.9ms 190±0.8ms 1.22 inference.ToNumericDowncast.time_downcast('string-float', 'integer')
+ 147±3μs 180±1μs 1.22 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc')
+ 148±0.9μs 181±0.4μs 1.22 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
+ 1.34±0ms 1.63±0.01ms 1.22 groupby.GroupByMethods.time_dtype_as_group('float', 'sem', 'direct')
+ 47.3±0.1ms 57.7±0.7ms 1.22 frame_ctor.FromDicts.time_nested_dict_columns
+ 4.57±0.3ms 5.57±0.1ms 1.22 rolling.Methods.time_rolling('Series', 1000, 'int', 'min')
+ 156±2ms 190±0.4ms 1.22 inference.ToNumericDowncast.time_downcast('string-float', 'signed')
+ 674±0.8μs 821±2μs 1.22 groupby.GroupByMethods.time_dtype_as_field('object', 'nunique', 'direct')
+ 1.34±0.01ms 1.63±0.01ms 1.22 groupby.GroupByMethods.time_dtype_as_group('float', 'sem', 'transformation')
+ 725±9μs 882±3μs 1.22 timeseries.ResetIndex.time_reest_datetimeindex(None)
+ 8.02±0.05μs 9.75±0.04μs 1.22 categoricals.Indexing.time_shallow_copy
+ 147±0.8μs 179±0.2μs 1.22 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc')
+ 148±0.3μs 180±0.3μs 1.22 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc')
+ 1.17±0.02ms 1.41±0.01ms 1.21 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'nonunique_monotonic_inc')
+ 26.3±0.07ms 31.8±0.08ms 1.21 strings.Contains.time_contains(False)
+ 3.00±0.01ms 3.62±0.01ms 1.21 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'std')
+ 3.25±0.01ms 3.92±0.02ms 1.21 io.csv.ReadCSVFloatPrecision.time_read_csv(';', '.', 'round_trip')
+ 2.99±0.03ms 3.61±0.01ms 1.21 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'std')
+ 458±0.4μs 553±3μs 1.21 categoricals.Constructor.time_from_codes_all_int8
+ 326±4μs 394±7μs 1.21 reindex.Fillna.time_float_32('backfill')
+ 3.23±0.01ms 3.90±0.7ms 1.21 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'sum')
+ 3.21±0.02ms 3.88±0.7ms 1.21 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'sum')
+ 66.8±0.6μs 80.5±1μs 1.20 categoricals.IsMonotonic.time_categorical_series_is_monotonic_increasing
+ 11.5±0.2μs 13.8±0.7μs 1.20 indexing.CategoricalIndexIndexing.time_get_loc_scalar('monotonic_incr')
+ 65.3±1ms 78.4±1ms 1.20 reshape.Cut.time_cut_timedelta(1000)
+ 3.21±0.02ms 3.86±0.7ms 1.20 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'sum')
+ 3.26±0.01ms 3.90±0.01ms 1.20 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '.', 'round_trip')
+ 67.0±0.6μs 80.0±1μs 1.20 categoricals.IsMonotonic.time_categorical_series_is_monotonic_decreasing
+ 1.17±0.04μs 1.40±0.06μs 1.19 index_cached_properties.IndexCache.time_is_monotonic('RangeIndex')
+ 942±2μs 1.13±0ms 1.19 groupby.GroupByMethods.time_dtype_as_field('datetime', 'cummin', 'transformation')
+ 1.05±0.01ms 1.26±0.02ms 1.19 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'non_monotonic')
+ 943±2μs 1.12±0ms 1.19 groupby.GroupByMethods.time_dtype_as_field('datetime', 'cummin', 'direct')
+ 38.3±2μs 45.6±0.4μs 1.19 indexing.CategoricalIndexIndexing.time_getitem_slice('monotonic_incr')
+ 3.13±0.01ms 3.72±0.01ms 1.19 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'std')
+ 3.84±0.1ms 4.56±0.4ms 1.19 stat_ops.SeriesMultiIndexOps.time_op(0, 'mean')
+ 473±0.8μs 562±2μs 1.19 timeseries.ToDatetimeCacheSmallCount.time_unique_date_strings(True, 50)
+ 5.89±0.02ms 7.00±0.01ms 1.19 timeseries.ResampleSeries.time_resample('period', '5min', 'mean')
+ 810±4μs 962±3μs 1.19 groupby.GroupByMethods.time_dtype_as_group('int', 'std', 'direct')
+ 472±0.9μs 561±2μs 1.19 timeseries.ToDatetimeCacheSmallCount.time_unique_date_strings(False, 50)
+ 811±2μs 962±2μs 1.19 groupby.GroupByMethods.time_dtype_as_group('int', 'std', 'transformation')
+ 8.41±0.03μs 9.98±0.1μs 1.19 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'non_monotonic')
+ 8.18±0.1ms 9.69±0.04ms 1.18 groupby.Apply.time_scalar_function_single_col
+ 40.2±0.1μs 47.6±2μs 1.18 ctors.SeriesDtypesConstructors.time_index_from_array_floats
+ 175±0.5μs 207±1μs 1.18 series_methods.NanOps.time_func('std', 1000, 'float64')
+ 3.47±0.01ms 4.10±0.7ms 1.18 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'mean')
+ 3.52±0.05ms 4.16±0.8ms 1.18 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'mean')
+ 34.0±0.07ms 40.1±0.2ms 1.18 strings.Methods.time_len
+ 43.3±0.3ms 51.0±0.08ms 1.18 reshape.Cut.time_cut_datetime(1000)
+ 40.8±0.2ms 48.1±1ms 1.18 stat_ops.FrameMultiIndexOps.time_op(0, 'kurt')
+ 3.50±0.01ms 4.13±0.7ms 1.18 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'mean')
+ 3.63±0.02ms 4.28±0.04ms 1.18 rolling.Methods.time_rolling('Series', 1000, 'int', 'std')
+ 303±4μs 357±5μs 1.18 join_merge.JoinNonUnique.time_join_non_unique_equal
+ 38.5±1μs 45.2±0.4μs 1.18 indexing.CategoricalIndexIndexing.time_getitem_slice('non_monotonic')
+ 5.97±0.02ms 7.02±0.04ms 1.17 indexing.MultiIndexing.time_index_slice
+ 8.42±0.2ms 9.87±0.7ms 1.17 rolling.Methods.time_rolling('Series', 1000, 'int', 'count')
+ 3.64±0.05ms 4.27±0.01ms 1.17 rolling.Methods.time_rolling('Series', 10, 'int', 'std')
+ 8.45±0.2ms 9.89±0.7ms 1.17 rolling.Methods.time_rolling('Series', 10, 'int', 'count')
+ 8.51±0.2ms 9.96±0.7ms 1.17 rolling.Methods.time_rolling('Series', 10, 'float', 'count')
+ 1.50±0.04μs 1.76±0.09μs 1.17 index_cached_properties.IndexCache.time_is_monotonic_decreasing('Int64Index')
+ 9.20±0.02ms 10.8±0.07ms 1.17 rolling.Pairwise.time_pairwise(None, 'corr', False)
+ 8.51±0.2ms 9.95±0.7ms 1.17 rolling.Methods.time_rolling('Series', 1000, 'float', 'count')
+ 1.28±0ms 1.49±0ms 1.16 series_methods.Map.time_map('dict', 'category')
+ 561±7μs 651±3μs 1.16 timeseries.ToDatetimeCacheSmallCount.time_unique_date_strings(False, 500)
+ 705±8ms 819±5ms 1.16 stat_ops.Correlation.time_corr_wide_nans('spearman')
+ 4.68±0.02ms 5.43±0.7ms 1.16 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'kurt')
+ 802±3μs 931±30μs 1.16 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'nonunique_monotonic_inc')
+ 190±5ms 221±4ms 1.16 io.json.ToJSONISO.time_iso_format('records')
+ 478±3μs 552±3μs 1.16 strings.Encode.time_encode_decode
+ 4.33±0.02ms 5.00±0.7ms 1.15 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'skew')
+ 225±0.5ms 260±2ms 1.15 io.json.ToJSONISO.time_iso_format('columns')
+ 974±5μs 1.12±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cumprod', 'transformation')
+ 1.20±0ms 1.39±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('datetime', 'rank', 'direct')
+ 7.71±0.01μs 8.89±0.02μs 1.15 dtypes.Dtypes.time_pandas_dtype('Int8')
+ 6.32±0.01ms 7.28±0.02ms 1.15 rolling.Pairwise.time_pairwise(None, 'cov', False)
+ 220±1μs 254±0.4μs 1.15 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('datetime', 'non_monotonic')
+ 21.2±0.1ms 24.4±0.1ms 1.15 reshape.Cut.time_qcut_datetime(10)
+ 143±0.4μs 164±0.4μs 1.15 series_methods.NanOps.time_func('std', 1000, 'int64')
+ 982±3μs 1.13±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cumsum', 'direct')
+ 1.06±0ms 1.22±0.01ms 1.15 groupby.GroupByMethods.time_dtype_as_group('datetime', 'cummin', 'transformation')
+ 35.8±0.3ms 41.1±0.7ms 1.15 io.hdf.HDFStoreDataFrame.time_read_store_mixed
+ 987±5μs 1.13±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cummax', 'direct')
+ 194±4μs 223±3μs 1.15 timeseries.SortIndex.time_get_slice(False)
+ 1.20±0ms 1.38±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('datetime', 'rank', 'transformation')
+ 981±3μs 1.12±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cumprod', 'direct')
+ 8.08±0.03ms 9.26±0.08ms 1.15 reshape.Cut.time_cut_datetime(4)
+ 19.8±0.2ms 22.7±0.07ms 1.15 reshape.Cut.time_qcut_datetime(4)
+ 990±1μs 1.13±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cummin', 'direct')
+ 1.24±0.04μs 1.43±0.04μs 1.15 index_cached_properties.IndexCache.time_is_monotonic('Int64Index')
+ 989±2μs 1.13±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cumsum', 'transformation')
+ 550±2ms 630±3ms 1.15 groupby.Groups.time_series_groups('int64_large')
+ 1.07±0ms 1.23±0ms 1.15 groupby.GroupByMethods.time_dtype_as_group('float', 'cumsum', 'transformation')
+ 989±3μs 1.13±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cummax', 'transformation')
+ 1.05±0ms 1.21±0.01ms 1.15 groupby.GroupByMethods.time_dtype_as_field('int', 'cummax', 'transformation')
+ 990±5μs 1.13±0ms 1.15 groupby.GroupByMethods.time_dtype_as_field('float', 'cummin', 'transformation')
+ 4.62±0.02ms 5.30±0.7ms 1.15 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'kurt')
+ 128±3ms 146±3ms 1.14 io.json.ToJSON.time_to_json('records', 'df_int_floats')
+ 1.07±0ms 1.23±0.01ms 1.14 groupby.GroupByMethods.time_dtype_as_group('float', 'cummax', 'direct')
+ 1.07±0ms 1.23±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('float', 'cummin', 'direct')
+ 196±0.5μs 224±1μs 1.14 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('datetime', 'nonunique_monotonic_inc')
+ 1.07±0ms 1.23±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('float', 'cummin', 'transformation')
+ 1.06±0ms 1.22±0.01ms 1.14 groupby.GroupByMethods.time_dtype_as_group('datetime', 'cummin', 'direct')
+ 4.67±0.02ms 5.34±0.7ms 1.14 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'kurt')
+ 2.61±0.01ms 2.98±0.03ms 1.14 groupby.RankWithTies.time_rank_ties('int64', 'max')
+ 2.80±0.01ms 3.21±0.01ms 1.14 ctors.SeriesConstructors.time_series_constructor(<class 'list'>, True, 'int')
+ 4.34±0.05ms 4.96±0.8ms 1.14 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'skew')
+ 143±0.2μs 163±0.2μs 1.14 series_methods.NanOps.time_func('std', 1000, 'int32')
+ 2.58±0.01ms 2.94±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float32', 'average')
+ 144±0.7μs 164±0.3μs 1.14 series_methods.NanOps.time_func('std', 1000, 'int8')
+ 1.08±0ms 1.23±0.01ms 1.14 groupby.GroupByMethods.time_dtype_as_group('float', 'cumsum', 'direct')
+ 2.55±0.01ms 2.92±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float64', 'average')
+ 2.55±0.01ms 2.92±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float64', 'max')
+ 128±0.7ms 146±0.5ms 1.14 io.json.ReadJSON.time_read_json('split', 'int')
+ 1.05±0ms 1.20±0ms 1.14 groupby.GroupByMethods.time_dtype_as_field('int', 'cummax', 'direct')
+ 37.6±0.1ms 42.9±0.1ms 1.14 strings.Methods.time_endswith
+ 2.57±0.01ms 2.94±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float32', 'first')
+ 1.08±0ms 1.23±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('float', 'cummax', 'transformation')
+ 2.59±0.02ms 2.95±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float32', 'dense')
+ 2.57±0ms 2.93±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float32', 'max')
+ 196±0.5μs 224±0.3μs 1.14 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('datetime', 'non_monotonic')
+ 8.07±0.02ms 9.20±0.06ms 1.14 sparse.Arithmetic.time_intersect(0.1, nan)
+ 1.04±0ms 1.19±0ms 1.14 groupby.GroupByMethods.time_dtype_as_field('int', 'cumsum', 'transformation')
+ 1.05±0ms 1.19±0ms 1.14 groupby.GroupByMethods.time_dtype_as_field('int', 'cumsum', 'direct')
+ 2.61±0.02ms 2.97±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('int64', 'min')
+ 2.55±0.01ms 2.91±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('float64', 'min')
+ 189±1ms 215±1ms 1.14 io.json.ToJSONLines.time_float_int_lines
+ 1.05±0ms 1.20±0ms 1.14 groupby.GroupByMethods.time_dtype_as_field('int', 'cummin', 'direct')
+ 2.77±0.01ms 3.15±0.01ms 1.14 ctors.SeriesConstructors.time_series_constructor(<class 'list'>, False, 'int')
+ 3.78±0.03ms 4.30±0.04ms 1.14 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f6536433620>, False, 'float')
+ 238±2μs 271±0.4μs 1.14 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('datetime', 'nonunique_monotonic_inc')
+ 9.28±0.03ms 10.6±0.02ms 1.14 rolling.Pairwise.time_pairwise(1000, 'corr', False)
+ 2.58±0.01ms 2.93±0.02ms 1.14 groupby.RankWithTies.time_rank_ties('float32', 'min')
+ 1.06±0ms 1.20±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int', 'cumsum', 'transformation')
+ 2.61±0.01ms 2.96±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('int64', 'average')
+ 1.17±0ms 1.33±0ms 1.14 series_methods.Map.time_map('dict', 'int')
+ 1.46±0ms 1.65±0.01ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int', 'sem', 'transformation')
+ 1.06±0ms 1.21±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int', 'cummin', 'transformation')
+ 1.06±0ms 1.20±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int', 'cumsum', 'direct')
+ 6.37±0.02ms 7.23±0.01ms 1.14 rolling.Pairwise.time_pairwise(1000, 'cov', False)
+ 2.59±0.01ms 2.94±0.01ms 1.14 groupby.RankWithTies.time_rank_ties('datetime64', 'min')
+ 1.06±0ms 1.21±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int', 'cummax', 'transformation')
+ 1.06±0ms 1.21±0ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int', 'cummin', 'direct')
+ 133±0.8ms 151±0.7ms 1.14 io.json.ReadJSON.time_read_json('split', 'datetime')
+ 1.06±0ms 1.21±0ms 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'cummax', 'direct')
+ 4.00±0.03ms 4.54±0.04ms 1.13 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f6536433620>, True, 'float')
+ 31.8±0.01ms 36.1±0.07ms 1.13 frame_methods.Equals.time_frame_nonunique_unequal
+ 2.59±0.01ms 2.93±0ms 1.13 groupby.RankWithTies.time_rank_ties('datetime64', 'max')
+ 9.24±0.02ms 10.5±0.02ms 1.13 rolling.Pairwise.time_pairwise(10, 'corr', False)
+ 2.59±0.01ms 2.93±0.01ms 1.13 groupby.RankWithTies.time_rank_ties('datetime64', 'dense')
+ 227±0.8μs 257±1μs 1.13 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('datetime', 'unique_monotonic_inc')
+ 2.33±0.01ms 2.64±0.01ms 1.13 io.csv.ReadCSVFloatPrecision.time_read_csv(';', '.', 'high')
+ 2.58±0.01ms 2.92±0.01ms 1.13 groupby.RankWithTies.time_rank_ties('float64', 'dense')
+ 1.36±0ms 1.54±0ms 1.13 groupby.GroupByMethods.time_dtype_as_field('float', 'rank', 'direct')
+ 31.8±0.06ms 36.0±0.03ms 1.13 frame_methods.Equals.time_frame_nonunique_equal
+ 226±7μs 256±1μs 1.13 timeseries.SortIndex.time_get_slice(True)
+ 2.59±0.01ms 2.93±0.02ms 1.13 groupby.RankWithTies.time_rank_ties('datetime64', 'average')
+ 1.06±0ms 1.20±0ms 1.13 groupby.GroupByMethods.time_dtype_as_field('int', 'cummin', 'transformation')
+ 1.40±0ms 1.58±0.01ms 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'rank', 'direct')
+ 2.62±0.01ms 2.96±0.01ms 1.13 groupby.RankWithTies.time_rank_ties('int64', 'dense')
+ 9.41±0.03ms 10.6±0.1ms 1.13 reshape.Cut.time_cut_datetime(10)
+ 2.62±0.01ms 2.96±0.01ms 1.13 groupby.RankWithTies.time_rank_ties('int64', 'first')
+ 1.40±0ms 1.58±0ms 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'rank', 'transformation')
+ 1.36±0ms 1.54±0ms 1.13 groupby.GroupByMethods.time_dtype_as_field('float', 'rank', 'transformation')
+ 6.93±0.1μs 7.82±0.2μs 1.13 index_cached_properties.IndexCache.time_engine('DatetimeIndex')
+ 2.33±0.01ms 2.63±0.01ms 1.13 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '.', 'high')
+ 1.41±0ms 1.59±0ms 1.13 groupby.GroupByMethods.time_dtype_as_group('float', 'rank', 'transformation')
+ 1.40±0ms 1.58±0.01ms 1.13 groupby.GroupByMethods.time_dtype_as_group('datetime', 'rank', 'transformation')
+ 1.40±0ms 1.58±0ms 1.13 groupby.GroupByMethods.time_dtype_as_group('datetime', 'rank', 'direct')
+ 2.42±0.02ms 2.73±0.01ms 1.13 io.csv.ReadCSVFloatPrecision.time_read_csv(';', '.', None)
+ 1.46±0.01ms 1.64±0.01ms 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'sem', 'direct')
+ 159±4ms 179±4ms 1.13 io.json.ToJSON.time_to_json('index', 'df_int_floats')
+ 183±0.5ms 207±2ms 1.13 io.json.ToJSONISO.time_iso_format('values')
+ 294±2μs 332±3μs 1.13 inference.NumericInferOps.time_multiply(<class 'numpy.int8'>)
+ 7.28±0.04ms 8.19±0.01ms 1.13 io.sas.SAS.time_read_sas('xport')
+ 2.42±0.01ms 2.73±0.01ms 1.13 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '.', None)
+ 1.39±0ms 1.56±0ms 1.13 groupby.GroupByMethods.time_dtype_as_field('int', 'rank', 'transformation')
+ 1.42±0ms 1.59±0ms 1.13 groupby.GroupByMethods.time_dtype_as_group('float', 'rank', 'direct')
+ 224±5ms 252±4ms 1.13 io.json.ToJSONISO.time_iso_format('split')
+ 692±10μs 779±20μs 1.13 inference.NumericInferOps.time_multiply(<class 'numpy.float32'>)
+ 2.13±0.01ms 2.39±0ms 1.12 series_methods.Map.time_map('dict', 'object')
+ 3.66±0.01ms 4.11±0.01ms 1.12 io.csv.ReadCSVParseDates.time_multiple_date
+ 1.39±0ms 1.56±0ms 1.12 groupby.GroupByMethods.time_dtype_as_field('int', 'rank', 'direct')
+ 86.7±1ms 97.3±2ms 1.12 frame_ctor.FromRecords.time_frame_from_records_generator(None)
+ 646±5ms 726±2ms 1.12 groupby.Groups.time_series_groups('object_large')
+ 126±3ms 141±3ms 1.12 io.json.ToJSON.time_to_json('records', 'df_int_float_str')
+ 3.01±0.01ms 3.38±0.02ms 1.12 io.csv.ReadCSVParseDates.time_baseline
+ 291±1μs 327±2μs 1.12 inference.NumericInferOps.time_add(<class 'numpy.int8'>)
+ 8.08±0.01ms 9.05±0.09ms 1.12 sparse.Arithmetic.time_intersect(0.01, nan)
+ 38.0±0.3ms 42.6±0.07ms 1.12 strings.Methods.time_startswith
+ 21.2±0.03ms 23.7±0.04ms 1.12 io.csv.ReadCSVConcatDatetimeBadDateValue.time_read_csv('nan')
+ 19.3±0.09ms 21.6±0.1ms 1.12 io.csv.ReadCSVConcatDatetimeBadDateValue.time_read_csv('')
+ 188±1ms 211±2ms 1.12 io.json.ToJSONLines.time_float_int_str_lines
+ 539±3μs 603±1μs 1.12 series_methods.Map.time_map('Series', 'category')
+ 288±1μs 323±2μs 1.12 inference.NumericInferOps.time_subtract(<class 'numpy.int8'>)
+ 291±0.8μs 325±2μs 1.12 inference.NumericInferOps.time_subtract(<class 'numpy.uint8'>)
+ 6.43±0.02ms 7.19±0.02ms 1.12 rolling.Pairwise.time_pairwise(10, 'cov', False)
+ 269±0.7μs 301±2μs 1.12 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('datetime', 'unique_monotonic_inc')
+ 292±1μs 326±1μs 1.12 inference.NumericInferOps.time_add(<class 'numpy.uint8'>)
+ 296±0.7μs 330±1μs 1.11 inference.NumericInferOps.time_multiply(<class 'numpy.uint8'>)
+ 8.85±0.3ms 9.86±0.5ms 1.11 timeseries.ResampleSeries.time_resample('datetime', '5min', 'ohlc')
+ 178±2ms 198±0.1ms 1.11 frame_ctor.FromDicts.time_nested_dict_int64
+ 13.5±0.04μs 15.1±0.4μs 1.11 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'nonunique_monotonic_inc')
+ 29.0±0.2ms 32.3±0.3ms 1.11 frame_ctor.FromLists.time_frame_from_lists
+ 3.09±0.05ms 3.43±0.03ms 1.11 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'sum')
+ 8.93±0.06μs 9.92±0.1μs 1.11 dtypes.Dtypes.time_pandas_dtype('Int16')
+ 398±3μs 442±3μs 1.11 inference.NumericInferOps.time_subtract(<class 'numpy.int16'>)
+ 244±6ms 270±5ms 1.11 io.json.ToJSONISO.time_iso_format('index')
+ 28.4±0.3ms 31.4±0.1ms 1.11 groupby.AggFunctions.time_different_python_functions_multicol
+ 5.50±0.03ms 6.08±0.04ms 1.11 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f6536433620>, False, 'int')
+ 11.2±0.03ms 12.4±0.05ms 1.11 io.hdf.HDFStoreDataFrame.time_query_store_table
+ 47.8±0.2μs 52.8±0.3μs 1.10 indexing.NonNumericSeriesIndexing.time_getitem_scalar('period', 'non_monotonic')
+ 227±0.7ms 251±1ms 1.10 strings.Slice.time_vector_slice
+ 2.78±0.02ms 3.08±0.03ms 1.10 io.csv.ReadCSVFloatPrecision.time_read_csv(';', '_', 'round_trip')
+ 399±3μs 441±9μs 1.10 inference.NumericInferOps.time_add(<class 'numpy.uint16'>)
+ 2.23±0s 2.46±0s 1.10 groupby.GroupByMethods.time_dtype_as_field('float', 'describe', 'transformation')
+ 192±2ms 212±2ms 1.10 io.stata.Stata.time_write_stata('tc')
+ 3.10±0.03ms 3.42±0.03ms 1.10 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'sum')
+ 5.74±0.03ms 6.32±0.04ms 1.10 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f6536433620>, True, 'int')
+ 2.23±0s 2.46±0.01s 1.10 groupby.GroupByMethods.time_dtype_as_field('float', 'describe', 'direct')
+ 105M 115M 1.10 rolling.PeakMemFixed.peakmem_fixed
+ 2.79±0.01ms 3.07±0.02ms 1.10 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '_', None)
+ 3.13±0s 3.44±0s 1.10 groupby.GroupByMethods.time_dtype_as_group('int', 'describe', 'direct')
+ 6.05±0.02ms 6.66±0.02ms 1.10 reshape.SimpleReshape.time_stack
+ 405±2μs 446±7μs 1.10 inference.NumericInferOps.time_multiply(<class 'numpy.int16'>)
+ 2.12±0s 2.33±0s 1.10 groupby.GroupByMethods.time_dtype_as_field('int', 'describe', 'direct')
+ 251±3ms 276±5ms 1.10 io.stata.StataMissing.time_write_stata('tc')
+ 18.4±0.2ms 20.2±0.06ms 1.10 reshape.Cut.time_qcut_timedelta(4)
+ 2.77±0.01ms 3.05±0.01ms 1.10 io.csv.ReadCSVFloatPrecision.time_read_csv(';', '_', None)
+ 3.13±0s 3.44±0s 1.10 groupby.GroupByMethods.time_dtype_as_group('int', 'describe', 'transformation')
- 1.10±0.01s 996±6ms 0.91 reshape.Unstack.time_without_last_row('category')
- 16.9±0.1ms 15.4±0.06ms 0.91 frame_methods.Apply.time_apply_lambda_mean
- 262±1μs 238±0.3μs 0.91 indexing.CategoricalIndexIndexing.time_getitem_bool_array('monotonic_decr')
- 3.97±0.01ms 3.59±0ms 0.91 offset.OffsetSeriesArithmetic.time_add_offset(<SemiMonthBegin: day_of_month=15>)
- 3.71±0.2μs 3.36±0.1μs 0.90 index_cached_properties.IndexCache.time_inferred_type('IntervalIndex')
- 16.7±0.9ms 15.0±0.07ms 0.90 stat_ops.Rank.time_average_old('DataFrame', False)
- 117±1ms 106±0.6ms 0.90 io.json.ToJSON.time_to_json('split', 'df_date_idx')
- 7.54±0.6μs 6.78±0.2μs 0.90 index_cached_properties.IndexCache.time_shape('TimedeltaIndex')
- 5.96±0.03ms 5.35±0.1ms 0.90 frame_methods.Interpolate.time_interpolate_some_good('infer')
- 4.43±0.05μs 3.98±0.01μs 0.90 series_methods.SeriesGetattr.time_series_datetimeindex_repr
- 186±6ms 167±1ms 0.90 categoricals.Rank.time_rank_string
- 78.7±0.3ms 70.3±0.3ms 0.89 rolling.Apply.time_rolling('Series', 3, 'int', <built-in function sum>, False)
- 84.0±0.6ms 74.9±0.5ms 0.89 binary_ops.Ops.time_frame_comparison(False, 1)
- 84.6±0.9ms 75.4±1ms 0.89 binary_ops.Ops.time_frame_comparison(False, 'default')
- 74.2±2ms 66.1±0.3ms 0.89 rolling.Apply.time_rolling('Series', 300, 'int', <built-in function sum>, False)
- 169±1μs 151±0.9μs 0.89 frame_methods.Dtypes.time_frame_dtypes
- 98.6±0.7μs 87.6±0.8μs 0.89 series_methods.NanOps.time_func('argmax', 1000, 'float64')
- 79.7±0.4ms 70.7±0.2ms 0.89 rolling.Apply.time_rolling('DataFrame', 3, 'int', <built-in function sum>, False)
- 79.5±0.4ms 70.5±0.3ms 0.89 rolling.Apply.time_rolling('DataFrame', 3, 'float', <built-in function sum>, False)
- 75.1±2ms 66.6±0.2ms 0.89 rolling.Apply.time_rolling('DataFrame', 300, 'float', <built-in function sum>, False)
- 12.5±0.5ms 11.1±0.3ms 0.88 categoricals.Rank.time_rank_string_cat
- 79.1±0.8ms 69.9±0.1ms 0.88 rolling.Apply.time_rolling('Series', 3, 'float', <built-in function sum>, False)
- 3.71±0.02μs 3.27±0.03μs 0.88 dtypes.DtypesInvalid.time_pandas_dtype_invalid('scalar-int')
- 74.5±2ms 65.6±0.2ms 0.88 rolling.Apply.time_rolling('Series', 300, 'float', <built-in function sum>, False)
- 52.6±0.2μs 46.3±0.1μs 0.88 timedelta.TimedeltaIndexing.time_series_loc
- 75.6±2ms 66.4±0.08ms 0.88 rolling.Apply.time_rolling('DataFrame', 300, 'int', <built-in function sum>, False)
- 3.50±0.02ms 3.06±0.01ms 0.88 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessDay>)
- 5.17±0.02ms 4.50±0.03ms 0.87 timeseries.ResampleSeries.time_resample('datetime', '1D', 'mean')
- 1.77±0.01ms 1.54±0ms 0.87 timeseries.ToDatetimeCacheSmallCount.time_unique_date_strings(True, 5000)
- 3.93±0.1μs 3.40±0.09μs 0.87 index_cached_properties.IndexCache.time_shape('PeriodIndex')
- 6.49±0.2μs 5.61±0.1μs 0.87 index_object.Indexing.time_get_loc('Int')
- 26.4±0.7μs 22.8±0.2μs 0.86 series_methods.SearchSorted.time_searchsorted('int32')
- 2.91±0.01ms 2.51±0.01ms 0.86 sparse.FromCoo.time_sparse_series_from_coo
- 6.52±0.03μs 5.62±0.04μs 0.86 index_object.Indexing.time_get_loc_sorted('Int')
- 920±2μs 793±1μs 0.86 frame_methods.Iteration.time_itertuples_raw_start
- 621±2μs 535±2μs 0.86 groupby.GroupByMethods.time_dtype_as_field('datetime', 'tail', 'direct')
- 26.5±0.7μs 22.9±0.4μs 0.86 series_methods.SearchSorted.time_searchsorted('int64')
- 274±2ms 235±2ms 0.86 io.json.ToJSON.time_to_json_wide('index', 'df_td_int_ts')
- 927±1μs 797±2μs 0.86 frame_methods.Iteration.time_itertuples_raw_read_first
- 26.1±0.3μs 22.4±0.2μs 0.86 series_methods.SearchSorted.time_searchsorted('uint8')
- 772±2μs 662±1μs 0.86 timeseries.ToDatetimeCacheSmallCount.time_unique_date_strings(True, 500)
- 597±2μs 512±2μs 0.86 groupby.GroupByMethods.time_dtype_as_field('datetime', 'head', 'direct')
- 622±2μs 532±1μs 0.86 groupby.GroupByMethods.time_dtype_as_field('datetime', 'tail', 'transformation')
- 600±2μs 513±2μs 0.85 groupby.GroupByMethods.time_dtype_as_field('datetime', 'head', 'transformation')
- 26.4±0.6μs 22.5±0.3μs 0.85 series_methods.SearchSorted.time_searchsorted('int8')
- 9.52±0.5μs 8.12±0.1μs 0.85 algorithms.DuplicatedUniqueIndex.time_duplicated_unique('float')
- 270±1ms 230±1ms 0.85 io.csv.ToCSV.time_frame('long')
- 273±2ms 233±2ms 0.85 io.json.ToJSON.time_to_json_wide('records', 'df_td_int_ts')
- 180±3ms 153±2ms 0.85 io.json.ToJSON.time_to_json('index', 'df_td_int_ts')
- 26.1±0.3μs 22.1±0.4μs 0.85 series_methods.SearchSorted.time_searchsorted('uint16')
- 26.8±0.3μs 22.7±0.1μs 0.85 series_methods.SearchSorted.time_searchsorted('int16')
- 152±1ms 128±2ms 0.85 io.json.ToJSON.time_to_json('records', 'df_td_int_ts')
- 9.50±0.03μs 8.04±0.06μs 0.85 algorithms.DuplicatedUniqueIndex.time_duplicated_unique('int')
- 26.5±0.3μs 22.3±0.09μs 0.84 series_methods.SearchSorted.time_searchsorted('uint32')
- 29.5±0.6μs 24.8±0.3μs 0.84 series_methods.SearchSorted.time_searchsorted('uint64')
- 4.61±0.04ms 3.84±0.02ms 0.83 timeseries.ResampleDatetetime64.time_resample
- 9.74±0.9μs 8.11±0.1μs 0.83 algorithms.DuplicatedUniqueIndex.time_duplicated_unique('string')
- 9.90±0.03ms 8.15±0.01ms 0.82 inference.DateInferOps.time_add_timedeltas
- 286±0.7ms 235±0.9ms 0.82 frame_methods.Apply.time_apply_user_func
- 70.4±3ms 57.9±1ms 0.82 plotting.SeriesPlotting.time_series_plot('line')
- 526±2ms 432±0.7ms 0.82 frame_methods.Nunique.time_frame_nunique
- 294±0.6ms 242±3ms 0.82 frame_methods.Duplicated.time_frame_duplicated_wide
- 256±2ms 210±0.4ms 0.82 io.json.ToJSON.time_to_json_wide('split', 'df_td_int_ts')
- 3.46±0.02ms 2.84±0.03ms 0.82 frame_methods.Interpolate.time_interpolate_some_good(None)
- 4.10±0.04ms 3.35±0.01ms 0.82 groupby.Datelike.time_sum('date_range')
- 256±1ms 209±2ms 0.82 io.json.ToJSON.time_to_json_wide('values', 'df_td_int_ts')
- 199±20ms 161±0.4ms 0.81 algorithms.Factorize.time_factorize(True, 'string')
- 10.3±0.2ms 8.36±0.02ms 0.81 inference.DateInferOps.time_subtract_datetimes
- 216±0.8μs 175±0.7μs 0.81 period.Indexing.time_unique
- 47.4±0.1μs 38.2±0.3μs 0.81 series_methods.NanOps.time_func('argmax', 1000, 'int64')
- 246±1ms 198±0.8ms 0.80 frame_methods.Interpolate.time_interpolate('infer')
- 7.62±0.01ms 6.10±0.05ms 0.80 io.hdf.HDFStoreDataFrame.time_store_info
- 34.0±0.08ms 27.2±0.05ms 0.80 io.csv.ToCSV.time_frame('mixed')
- 47.2±0.2μs 37.5±0.1μs 0.80 series_methods.NanOps.time_func('argmax', 1000, 'int8')
- 47.4±0.2μs 37.6±0.2μs 0.79 series_methods.NanOps.time_func('argmax', 1000, 'int32')
- 10.5±0.05ms 8.28±0.01ms 0.79 reindex.DropDuplicates.time_frame_drop_dups(True)
- 160±4ms 126±4ms 0.79 io.json.ToJSON.time_to_json('columns', 'df_td_int_ts')
- 188±2ms 148±2ms 0.79 frame_methods.Interpolate.time_interpolate(None)
- 21.1±0.4ms 16.6±1ms 0.78 algorithms.FactorizeUnique.time_factorize(False, 'string')
- 12.0±0.04ms 9.33±0.02ms 0.78 reindex.DropDuplicates.time_frame_drop_dups_na(True)
- 316±1μs 242±2μs 0.76 index_object.SetOperations.time_operation('datetime', 'union')
- 2.34±0.02ms 1.78±0.01ms 0.76 categoricals.CategoricalSlicing.time_getitem_bool_array('monotonic_incr')
- 2.36±0.01ms 1.79±0.01ms 0.76 categoricals.CategoricalSlicing.time_getitem_bool_array('monotonic_decr')
- 14.2±0.2μs 10.7±0.08μs 0.76 timeseries.AsOf.time_asof_single_early('Series')
- 15.1±0.1ms 11.4±0.1ms 0.76 io.csv.ToCSVDatetime.time_frame_date_formatting
- 15.3±0.2μs 11.5±0.2μs 0.75 timeseries.DatetimeIndex.time_get('tz_aware')
- 621±2ms 466±0.8ms 0.75 package.TimeImport.time_import
- 243±0.9μs 181±0.7μs 0.74 timeseries.DatetimeIndex.time_unique('dst')
- 2.68±0.01ms 1.98±0.01ms 0.74 timeseries.ResampleDataFrame.time_method('mean')
- 60.7±2ms 44.5±0.1ms 0.73 io.hdf.HDFStoreDataFrame.time_write_store_table_wide
- 919±5ns 667±20ns 0.73 timedelta.TimedeltaIndexing.time_shape
- 1.29±0.01ms 931±1μs 0.72 offset.OffsetSeriesArithmetic.time_add_offset(<DateOffset: days=2, months=2>)
- 9.40±0.1μs 6.70±0.3μs 0.71 timedelta.TimedeltaIndexing.time_get_loc
- 935±10ns 658±6ns 0.70 period.Indexing.time_shape
- 497±3ms 349±2ms 0.70 groupby.GroupByMethods.time_dtype_as_group('float', 'unique', 'direct')
- 502±5ms 351±3ms 0.70 groupby.GroupByMethods.time_dtype_as_group('float', 'unique', 'transformation')
- 224±3ms 156±0.9ms 0.70 groupby.GroupByMethods.time_dtype_as_field('float', 'unique', 'transformation')
- 218±2ms 151±1ms 0.69 groupby.GroupByMethods.time_dtype_as_field('int', 'unique', 'direct')
- 505±4ms 350±2ms 0.69 groupby.GroupByMethods.time_dtype_as_group('datetime', 'unique', 'direct')
- 11.2±0.08μs 7.76±0.05μs 0.69 timedelta.TimedeltaIndexing.time_shallow_copy
- 219±2ms 151±0.6ms 0.69 groupby.GroupByMethods.time_dtype_as_field('int', 'unique', 'transformation')
- 506±2ms 350±2ms 0.69 groupby.GroupByMethods.time_dtype_as_group('datetime', 'unique', 'transformation')
- 227±9ms 157±0.7ms 0.69 groupby.GroupByMethods.time_dtype_as_field('float', 'unique', 'direct')
- 325±3ms 223±0.6ms 0.69 groupby.GroupByMethods.time_dtype_as_group('int', 'unique', 'direct')
- 139±0.8ms 95.2±0.6ms 0.68 io.json.ToJSON.time_to_json('values', 'df_td_int_ts')
- 30.9±1ms 21.1±0.6ms 0.68 algorithms.Duplicated.time_duplicated(False, 'string')
- 31.5±0.2ms 21.5±0.06ms 0.68 stat_ops.Correlation.time_corrwith_cols('pearson')
- 331±6ms 225±1ms 0.68 groupby.GroupByMethods.time_dtype_as_group('int', 'unique', 'transformation')
- 12.0±4μs 8.08±0.05μs 0.68 algorithms.DuplicatedUniqueIndex.time_duplicated_unique('uint')
- 1.06±0.01ms 709±3μs 0.67 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessMonthEnd>)
- 1.07±0ms 709±5μs 0.67 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessYearEnd: month=12>)
- 1.06±0ms 702±3μs 0.66 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessQuarterEnd: startingMonth=3>)
- 45.9±4ms 30.4±0.1ms 0.66 algorithms.Factorize.time_factorize(False, 'string')
- 1.03±0.01ms 681±2μs 0.66 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessQuarterBegin: startingMonth=3>)
- 1.04±0ms 687±2μs 0.66 offset.OffsetSeriesArithmetic.time_add_offset(<YearEnd: month=12>)
- 163±1ms 107±1ms 0.66 io.json.ToJSON.time_to_json('split', 'df_td_int_ts')
- 1.03±0ms 678±1μs 0.66 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessYearBegin: month=1>)
- 1.03±0ms 676±3μs 0.65 offset.OffsetSeriesArithmetic.time_add_offset(<QuarterEnd: startingMonth=3>)
- 1.03±0ms 670±1μs 0.65 offset.OffsetSeriesArithmetic.time_add_offset(<BusinessMonthBegin>)
- 1.03±0ms 671±4μs 0.65 offset.OffsetSeriesArithmetic.time_add_offset(<MonthEnd>)
- 255±1ms 167±0.6ms 0.65 groupby.GroupByMethods.time_dtype_as_field('object', 'unique', 'direct')
- 1.02±0ms 662±0.7μs 0.65 offset.OffsetSeriesArithmetic.time_add_offset(<QuarterBegin: startingMonth=3>)
- 1.01±0ms 659±5μs 0.65 offset.OffsetSeriesArithmetic.time_add_offset(<YearBegin: month=1>)
- 1.01±0.01ms 652±1μs 0.65 offset.OffsetSeriesArithmetic.time_add_offset(<MonthBegin>)
- 258±2ms 166±1ms 0.64 groupby.GroupByMethods.time_dtype_as_field('object', 'unique', 'transformation')
- 252±2ms 163±1ms 0.64 eval.Eval.time_and('python', 'all')
- 206M 133M 0.64 reshape.Cut.peakmem_cut_interval(10)
- 206M 133M 0.64 reshape.Cut.peakmem_cut_interval(4)
- 207M 133M 0.64 reshape.Cut.peakmem_cut_interval(1000)
- 4.76±0.02ms 3.03±0.01ms 0.64 timeseries.ResampleDataFrame.time_method('min')
- 983±2ms 618±1ms 0.63 io.json.ReadJSON.time_read_json('index', 'datetime')
- 1.02±0ms 640±2μs 0.63 offset.OffsetSeriesArithmetic.time_add_offset(<Day>)
- 3.87±0ms 2.41±0.01ms 0.62 index_object.SetOperations.time_operation('datetime', 'intersection')
- 150±4ms 92.7±4ms 0.62 binary_ops.Ops.time_frame_multi_and(False, 'default')
- 151±4ms 92.9±3ms 0.62 binary_ops.Ops.time_frame_multi_and(False, 1)
- 263±2ms 162±1ms 0.62 eval.Eval.time_and('python', 1)
- 1.92±0.05ms 1.18±0.06ms 0.62 reindex.LevelAlign.time_align_level
- 8.72±0.08μs 5.35±0.03μs 0.61 timeseries.DatetimeIndex.time_get('repeated')
- 191±0.6μs 117±0.5μs 0.61 timedelta.TimedeltaIndexing.time_unique
- 22.7±0.2ms 13.8±0.06ms 0.61 algorithms.Duplicated.time_duplicated('last', 'string')
- 1.12±0.01s 679±1ms 0.60 io.json.ReadJSON.time_read_json('index', 'int')
- 8.52±0.07μs 5.14±0.02μs 0.60 timeseries.DatetimeIndex.time_get('tz_naive')
- 4.75±0.01ms 2.86±0ms 0.60 timeseries.ResampleDataFrame.time_method('max')
- 8.49±0.05μs 5.12±0.02μs 0.60 timeseries.DatetimeIndex.time_get('dst')
- 22.8±0.3ms 13.7±0.02ms 0.60 algorithms.Duplicated.time_duplicated('first', 'string')
- 149±4ms 87.2±3ms 0.59 binary_ops.Ops.time_frame_multi_and(True, 'default')
- 160±4ms 93.6±3ms 0.59 binary_ops.Ops.time_frame_multi_and(True, 1)
- 1.95±0ms 1.12±0ms 0.57 groupby.GroupByMethods.time_dtype_as_group('object', 'unique', 'direct')
- 1.95±0.01ms 1.11±0ms 0.57 groupby.GroupByMethods.time_dtype_as_group('object', 'unique', 'transformation')
- 2.10±0.06ms 1.20±0.06ms 0.57 reindex.LevelAlign.time_reindex_level
- 652±1ms 348±1ms 0.53 stat_ops.Correlation.time_corrwith_rows('pearson')
- 1.83±0.03ms 949±8μs 0.52 replace.FillNa.time_replace(True)
- 10.0±0.5ms 5.06±0.8ms 0.50 binary_ops.Timeseries.time_timestamp_ops_diff('US/Eastern')
- 184±10ms 89.7±1ms 0.49 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function pow>)
- 128±1ms 61.4±0.5ms 0.48 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function floordiv>)
- 197±20ms 93.4±4ms 0.47 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function pow>)
- 124±2ms 58.6±0.5ms 0.47 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function floordiv>)
- 9.59±0.4ms 4.51±0.1ms 0.47 rolling.EWMMethods.time_ewm('Series', 10, 'int', 'mean')
- 125±1ms 58.7±0.5ms 0.47 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function floordiv>)
- 126±2ms 59.0±0.5ms 0.47 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function floordiv>)
- 133±1ms 61.2±0.7ms 0.46 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function floordiv>)
- 202±10ms 92.7±4ms 0.46 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function pow>)
- 132±1ms 60.3±0.5ms 0.46 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function floordiv>)
- 9.37±0.4ms 4.26±0.1ms 0.45 rolling.EWMMethods.time_ewm('Series', 10, 'float', 'mean')
- 9.59±0.4ms 4.35±0.1ms 0.45 rolling.EWMMethods.time_ewm('Series', 1000, 'int', 'mean')
- 9.43±0.3ms 4.25±0.1ms 0.45 rolling.EWMMethods.time_ewm('Series', 1000, 'float', 'mean')
- 127±1ms 55.9±0.4ms 0.44 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function floordiv>)
- 128±1ms 56.1±0.5ms 0.44 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function floordiv>)
- 126±0.9μs 53.9±0.09μs 0.43 categoricals.CategoricalOps.time_categorical_op('__eq__')
- 127±0.6μs 54.3±0.2μs 0.43 categoricals.CategoricalOps.time_categorical_op('__gt__')
- 127±0.9μs 54.3±0.3μs 0.43 categoricals.CategoricalOps.time_categorical_op('__ge__')
- 75.5±0.5ms 27.1±0.6ms 0.36 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function mod>)
- 7.66±0.01ms 2.74±0.06ms 0.36 rolling.EWMMethods.time_ewm('DataFrame', 10, 'int', 'mean')
- 114±0.4ms 40.6±0.02ms 0.36 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function mod>)
- 5.33±0.07ms 1.87±0ms 0.35 series_methods.Dir.time_dir_strings
- 77.0±0.6ms 27.0±0.7ms 0.35 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function mod>)
- 7.67±0.03ms 2.69±0.02ms 0.35 rolling.EWMMethods.time_ewm('DataFrame', 1000, 'int', 'mean')
- 114±1ms 39.7±0.03ms 0.35 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function mod>)
- 93.1±0.9ms 32.0±0.06ms 0.34 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function mod>)
- 86.7±0.7ms 29.5±0.03ms 0.34 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function mod>)
- 86.9±0.9ms 29.5±0.04ms 0.34 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function mod>)
- 7.52±0.02ms 2.55±0.01ms 0.34 rolling.EWMMethods.time_ewm('DataFrame', 10, 'float', 'mean')
- 7.53±0.02ms 2.54±0.01ms 0.34 rolling.EWMMethods.time_ewm('DataFrame', 1000, 'float', 'mean')
- 88.8±0.7ms 29.7±0.01ms 0.33 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function mod>)
- 3.40±0.02s 1.08±0.01s 0.32 reshape.Cut.time_cut_interval(1000)
- 105±4ms 32.9±0.5ms 0.31 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function pow>)
- 333±4ms 102±0.2ms 0.31 binary_ops.Ops2.time_frame_float_div_by_zero
- 336±0.9ms 103±0.4ms 0.31 binary_ops.Ops2.time_frame_int_div_by_zero
- 97.8±1ms 29.5±0.4ms 0.30 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function pow>)
- 97.5±1ms 29.4±0.3ms 0.30 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function pow>)
- 2.91±0.01s 792±10ms 0.27 reshape.Cut.time_cut_interval(4)
- 2.98±0.03s 803±7ms 0.27 reshape.Cut.time_cut_interval(10)
- 96.2±0.8ms 25.3±0.7ms 0.26 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function pow>)
- 19.4±0.7ms 4.87±0.3ms 0.25 rolling.EWMMethods.time_ewm('Series', 10, 'int', 'std')
- 19.3±0.7ms 4.71±0.3ms 0.24 rolling.EWMMethods.time_ewm('Series', 1000, 'int', 'std')
- 2.34±0.02μs 557±10ns 0.24 multiindex_object.Integer.time_is_monotonic
- 19.5±0.3ms 4.61±0.2ms 0.24 rolling.EWMMethods.time_ewm('Series', 10, 'float', 'std')
- 19.5±0.3ms 4.61±0.2ms 0.24 rolling.EWMMethods.time_ewm('Series', 1000, 'float', 'std')
- 19.5±0.07ms 3.66±0.02ms 0.19 rolling.EWMMethods.time_ewm('DataFrame', 1000, 'int', 'std')
- 19.6±0.07ms 3.66±0.02ms 0.19 rolling.EWMMethods.time_ewm('DataFrame', 10, 'int', 'std')
- 19.4±0.08ms 3.50±0.01ms 0.18 rolling.EWMMethods.time_ewm('DataFrame', 1000, 'float', 'std')
- 19.4±0.05ms 3.49±0.01ms 0.18 rolling.EWMMethods.time_ewm('DataFrame', 10, 'float', 'std')
- 18.7±0.2ms 2.98±0.01ms 0.16 stat_ops.Correlation.time_corr('spearman')
- 476±9ms 45.6±0.8ms 0.10 binary_ops.Ops2.time_frame_float_floor_by_zero
- 8.78±0.5ms 746±3μs 0.09 period.Algorithms.time_drop_duplicates('series')
- 757±10ms 60.1±0.2ms 0.08 stat_ops.Correlation.time_corr_wide('spearman')
- 18.8±0.03ms 1.32±0ms 0.07 frame_methods.SelectDtypes.time_select_dtypes(100)
- 66.8±1ms 4.41±0.2ms 0.07 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function truediv>)
- 64.0±1ms 3.90±0.6ms 0.06 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function add>)
- 17.7±0.2ms 1.07±0ms 0.06 index_object.IntervalIndexMethod.time_intersection_both_duplicate(1000)
- 65.8±2ms 3.73±0.1ms 0.06 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function truediv>)
- 64.1±1ms 3.57±0.3ms 0.06 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function sub>)
- 64.6±0.9ms 3.58±0.09ms 0.06 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function mul>)
- 64.5±0.3ms 3.57±0.3ms 0.06 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function sub>)
- 72.3±0.9ms 4.00±0.3ms 0.06 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function truediv>)
- 64.2±0.7ms 3.49±0.2ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function mul>)
- 71.2±1ms 3.85±0.2ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function truediv>)
- 64.7±0.7ms 3.44±0.1ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function add>)
- 65.2±0.7ms 3.40±0.3ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function truediv>)
- 66.4±0.9ms 3.36±0.1ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function truediv>)
- 70.3±0.7ms 3.51±0.2ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function truediv>)
- 58.1±0.9ms 2.74±0.02ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function eq>)
- 58.3±0.8ms 2.73±0.01ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function ge>)
- 58.0±0.8ms 2.70±0.01ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function lt>)
- 58.4±0.8ms 2.71±0.01ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function gt>)
- 58.3±0.6ms 2.70±0ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function le>)
- 58.3±0.7ms 2.69±0.01ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function ne>)
- 59.0±0.9ms 2.71±0.01ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function ge>)
- 74.2±3ms 3.41±0.3ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function truediv>)
- 59.3±0.9ms 2.72±0.02ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function lt>)
- 59.0±0.8ms 2.71±0ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function gt>)
- 58.8±0.5ms 2.69±0.02ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function eq>)
- 63.4±0.6ms 2.88±0.2ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function sub>)
- 64.1±0.9ms 2.91±0.2ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function add>)
- 69.1±1ms 3.13±0.2ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function add>)
- 59.3±0.7ms 2.68±0.01ms 0.05 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function ne>)
- 59.8±1ms 2.68±0.01ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function le>)
- 63.7±1ms 2.85±0.09ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function mul>)
- 64.2±0.8ms 2.86±0.08ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function mul>)
- 64.1±0.8ms 2.83±0.1ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function sub>)
- 63.2±0.4ms 2.78±0.1ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function add>)
- 67.3±0.5ms 2.94±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function mul>)
- 69.3±1ms 2.99±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function add>)
- 22.4±0.04ms 948±10μs 0.04 index_cached_properties.IndexCache.time_is_monotonic_decreasing('MultiIndex')
- 69.9±1ms 2.94±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function sub>)
- 70.8±2ms 2.93±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function sub>)
- 72.2±2ms 2.95±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function mul>)
- 71.5±1ms 2.91±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function sub>)
- 70.4±2ms 2.84±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 3.0, <built-in function mul>)
- 72.2±1ms 2.87±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function add>)
- 71.6±0.7ms 2.73±0.1ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function sub>)
- 71.4±0.6ms 2.69±0.1ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function add>)
- 72.8±1ms 2.67±0.2ms 0.04 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function mul>)
- 22.1±0.06ms 717±10μs 0.03 index_cached_properties.IndexCache.time_is_monotonic_increasing('MultiIndex')
- 22.1±0.05ms 715±10μs 0.03 index_cached_properties.IndexCache.time_is_monotonic('MultiIndex')
- 56.4±0.5ms 1.48±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function lt>)
- 57.2±0.7ms 1.48±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function le>)
- 56.5±0.4ms 1.46±0ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function ge>)
- 57.1±0.6ms 1.47±0ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function le>)
- 57.0±0.6ms 1.47±0ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function lt>)
- 56.8±0.8ms 1.46±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function gt>)
- 57.0±0.5ms 1.47±0ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function ge>)
- 56.7±0.6ms 1.45±0ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function gt>)
- 56.4±0.3ms 1.42±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function lt>)
- 56.4±0.4ms 1.42±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function le>)
- 56.3±0.3ms 1.41±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function ge>)
- 56.8±0.3ms 1.42±0.01ms 0.03 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function lt>)
- 56.7±0.3ms 1.42±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function ne>)
- 57.0±0.2ms 1.42±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function ge>)
- 56.4±0.7ms 1.40±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function gt>)
- 57.0±0.2ms 1.42±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function le>)
- 57.1±0.4ms 1.42±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function le>)
- 57.1±0.4ms 1.42±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function le>)
- 57.3±0.4ms 1.42±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function gt>)
- 57.2±0.4ms 1.42±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function lt>)
- 57.0±0.8ms 1.41±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function ge>)
- 57.7±0.3ms 1.42±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function ne>)
- 57.4±0.4ms 1.41±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function lt>)
- 57.3±0.4ms 1.41±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function ge>)
- 57.3±4ms 1.41±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function gt>)
- 56.9±0.5ms 1.40±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 5.0, <built-in function eq>)
- 57.8±0.5ms 1.42±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function ne>)
- 57.4±0.5ms 1.40±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function gt>)
- 57.9±5ms 1.42±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function ne>)
- 57.4±0.4ms 1.40±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 4, <built-in function eq>)
- 56.7±0.7ms 1.39±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function ne>)
- 56.9±0.7ms 1.38±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function ne>)
- 57.4±0.3ms 1.40±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 3.0, <built-in function eq>)
- 57.9±0.05ms 1.40±0ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.float64'>, 2, <built-in function eq>)
- 56.6±0.5ms 1.37±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function eq>)
- 57.0±0.5ms 1.37±0.01ms 0.02 binary_ops.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 2, <built-in function eq>)
- 7.38±0.01s 115±1ms 0.02 index_object.IntervalIndexMethod.time_intersection_both_duplicate(100000)
- 276±2ms 2.27±0.1ms 0.01 frame_ctor.FromRange.time_frame_from_range
- 201±0.5ms 1.40±0ms 0.01 frame_methods.SelectDtypes.time_select_dtypes(1000)
- 27.1±0.04s 151±0.4ms 0.01 replace.ReplaceList.time_replace_list_one_match(False)
- 24.8±0.04s 93.4±0.4ms 0.00 replace.ReplaceList.time_replace_list(False)
- 25.3±0.02s 59.0±0.08ms 0.00 replace.ReplaceList.time_replace_list_one_match(True)
- 13.7±0.5ms 5.18±0.4μs 0.00 dtypes.InferDtypes.time_infer_skipna('np-int')
- 14.6±0.4ms 4.97±0.2μs 0.00 dtypes.InferDtypes.time_infer_skipna('np-null')
- 14.9±0.4ms 5.01±0.1μs 0.00 dtypes.InferDtypes.time_infer_skipna('np-floating')
- 331±1ms 6.55±0.03μs 0.00 index_object.IndexEquals.time_non_object_equals_multiindex
- 331±3ms 2.74±0.03μs 0.00 multiindex_object.Equals.time_equals_non_object_index
- 22.9±0.06s 115±1μs 0.00 replace.ReplaceList.time_replace_list(True)
SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY.
I already commented on a few PRs, for the rest would need to take a further look. Help is certainly welcome to check certain cases.
One recurrent theme seems to be a rather consistent slowdown of a bunch of groupby methods. This can also be seen on the benchmark machine (eg https://pandas.pydata.org/speed/pandas/index.html#groupby.GroupByMethods.time_dtype_as_group?p-dtype='int'&p-method='all'&p-method='any'&odfpy=)