Closed
Description
I did a full benchmark run on a dedicated machine comparing v1.2.0rc0 with v1.1.5.
The top results:
[b5958ee1] [7688d3cf]
<v1.1.5^0> <v1.2.0rc0^0>
+ 4.25±0.05μs 366±9ms 86187.42 index_object.IndexEquals.time_non_object_equals_multiindex
+ 50.2±4μs 104±5ms 2075.23 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 120±8μs 102±5ms 848.38 indexing.NumericSeriesIndexing.time_loc_scalar(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 268±20μs 103±5ms 383.87 indexing.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 289±40μs 111±8ms 382.15 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 1000000)
+ 273±20μs 102±5ms 374.69 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 1.75±0.1ms 103±5ms 58.77 indexing.NumericSeriesIndexing.time_loc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 2.11±0.1ms 103±5ms 48.69 indexing.NumericSeriesIndexing.time_getitem_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 7.38±0.7ms 109±7ms 14.80 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 1000000)
+ 3.66±0.2μs 13.4±0.4μs 3.66 index_cached_properties.IndexCache.time_is_all_dates('Float64Index')
+ 336±2ms 1.22±0s 3.65 groupby.TransformEngine.time_series_numba(True)
+ 287±2ms 1.02±0s 3.55 groupby.AggEngine.time_series_numba(True)
+ 289±2ms 1.02±0s 3.52 groupby.AggEngine.time_dataframe_numba(True)
+ 3.64±0.2μs 12.8±0.5μs 3.52 index_cached_properties.IndexCache.time_is_all_dates('IntervalIndex')
+ 1.89±0.09μs 6.49±0.1μs 3.44 index_cached_properties.IndexCache.time_is_all_dates('PeriodIndex')
+ 3.80±0.2μs 12.7±0.4μs 3.35 index_cached_properties.IndexCache.time_is_all_dates('UInt64Index')
+ 3.27±0.1μs 10.9±0.2μs 3.33 index_cached_properties.IndexCache.time_is_all_dates('MultiIndex')
+ 728±30ns 2.39±0.06μs 3.28 index_cached_properties.IndexCache.time_is_all_dates('RangeIndex')
+ 2.02±0.09μs 6.49±0.1μs 3.21 index_cached_properties.IndexCache.time_is_all_dates('DatetimeIndex')
+ 719±30ns 2.27±0.06μs 3.15 index_cached_properties.IndexCache.time_is_all_dates('Int64Index')
+ 4.11±0.2μs 12.4±0.3μs 3.02 index_cached_properties.IndexCache.time_is_all_dates('TimedeltaIndex')
+ 430±3ms 1.23±0s 2.85 groupby.TransformEngine.time_dataframe_numba(True)
+ 7.44±0.08ms 17.1±2ms 2.29 hash_functions.UniqueAndFactorizeArange.time_unique(6)
+ 75.3±1ms 172±1ms 2.28 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.float64'>, 1000000)
+ 7.64±0.04ms 17.1±2ms 2.24 hash_functions.UniqueAndFactorizeArange.time_unique(5)
+ 1.62±0.04ms 3.51±0.02ms 2.16 arithmetic.Timeseries.time_series_timestamp_compare(None)
+ 1.60±0.03ms 3.45±0.04ms 2.16 arithmetic.Timeseries.time_timestamp_series_compare(None)
+ 1.62±0.03ms 3.49±0.09ms 2.16 arithmetic.Timeseries.time_timestamp_series_compare('US/Eastern')
+ 10.9±0.7ms 23.2±1ms 2.14 hash_functions.UniqueAndFactorizeArange.time_factorize(6)
+ 11.1±0.5ms 23.2±1ms 2.10 hash_functions.UniqueAndFactorizeArange.time_factorize(5)
+ 1.63±0.04ms 3.41±0.03ms 2.09 arithmetic.Timeseries.time_series_timestamp_compare('US/Eastern')
+ 4.11±0.1ms 8.52±0.09ms 2.08 index_object.SetDisjoint.time_datetime_difference_disjoint
+ 74.5±0.3ms 153±1ms 2.05 replace.ReplaceList.time_replace_list_one_match(True)
+ 124±0.9ms 248±0.4ms 2.00 gil.ParallelDatetimeFields.time_datetime_to_period
The first, biggest regression in the IndexEquals benchmark is probably already fixed in #38560
Full results:
before after ratio
[b5958ee1] [7688d3cf]
<v1.1.5^0> <v1.2.0rc0^0>
+ 4.25±0.05μs 366±9ms 86187.42 index_object.IndexEquals.time_non_object_equals_multiindex
+ 50.2±4μs 104±5ms 2075.23 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 120±8μs 102±5ms 848.38 indexing.NumericSeriesIndexing.time_loc_scalar(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 268±20μs 103±5ms 383.87 indexing.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 289±40μs 111±8ms 382.15 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 1000000)
+ 273±20μs 102±5ms 374.69 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 1.75±0.1ms 103±5ms 58.77 indexing.NumericSeriesIndexing.time_loc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 2.11±0.1ms 103±5ms 48.69 indexing.NumericSeriesIndexing.time_getitem_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 7.38±0.7ms 109±7ms 14.80 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 1000000)
+ 3.66±0.2μs 13.4±0.4μs 3.66 index_cached_properties.IndexCache.time_is_all_dates('Float64Index')
+ 336±2ms 1.22±0s 3.65 groupby.TransformEngine.time_series_numba(True)
+ 287±2ms 1.02±0s 3.55 groupby.AggEngine.time_series_numba(True)
+ 289±2ms 1.02±0s 3.52 groupby.AggEngine.time_dataframe_numba(True)
+ 3.64±0.2μs 12.8±0.5μs 3.52 index_cached_properties.IndexCache.time_is_all_dates('IntervalIndex')
+ 1.89±0.09μs 6.49±0.1μs 3.44 index_cached_properties.IndexCache.time_is_all_dates('PeriodIndex')
+ 3.80±0.2μs 12.7±0.4μs 3.35 index_cached_properties.IndexCache.time_is_all_dates('UInt64Index')
+ 3.27±0.1μs 10.9±0.2μs 3.33 index_cached_properties.IndexCache.time_is_all_dates('MultiIndex')
+ 728±30ns 2.39±0.06μs 3.28 index_cached_properties.IndexCache.time_is_all_dates('RangeIndex')
+ 2.02±0.09μs 6.49±0.1μs 3.21 index_cached_properties.IndexCache.time_is_all_dates('DatetimeIndex')
+ 719±30ns 2.27±0.06μs 3.15 index_cached_properties.IndexCache.time_is_all_dates('Int64Index')
+ 4.11±0.2μs 12.4±0.3μs 3.02 index_cached_properties.IndexCache.time_is_all_dates('TimedeltaIndex')
+ 430±3ms 1.23±0s 2.85 groupby.TransformEngine.time_dataframe_numba(True)
+ 7.44±0.08ms 17.1±2ms 2.29 hash_functions.UniqueAndFactorizeArange.time_unique(6)
+ 75.3±1ms 172±1ms 2.28 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.float64'>, 1000000)
+ 7.64±0.04ms 17.1±2ms 2.24 hash_functions.UniqueAndFactorizeArange.time_unique(5)
+ 1.62±0.04ms 3.51±0.02ms 2.16 arithmetic.Timeseries.time_series_timestamp_compare(None)
+ 1.60±0.03ms 3.45±0.04ms 2.16 arithmetic.Timeseries.time_timestamp_series_compare(None)
+ 1.62±0.03ms 3.49±0.09ms 2.16 arithmetic.Timeseries.time_timestamp_series_compare('US/Eastern')
+ 10.9±0.7ms 23.2±1ms 2.14 hash_functions.UniqueAndFactorizeArange.time_factorize(6)
+ 11.1±0.5ms 23.2±1ms 2.10 hash_functions.UniqueAndFactorizeArange.time_factorize(5)
+ 1.63±0.04ms 3.41±0.03ms 2.09 arithmetic.Timeseries.time_series_timestamp_compare('US/Eastern')
+ 4.11±0.1ms 8.52±0.09ms 2.08 index_object.SetDisjoint.time_datetime_difference_disjoint
+ 74.5±0.3ms 153±1ms 2.05 replace.ReplaceList.time_replace_list_one_match(True)
+ 124±0.9ms 248±0.4ms 2.00 gil.ParallelDatetimeFields.time_datetime_to_period
+ 950±30μs 1.83±0.05ms 1.92 reindex.LevelAlign.time_reindex_level
+ 2.84±0ms 5.46±0.02ms 1.92 tslibs.normalize.Normalize.time_is_date_array_normalized(1000000, datetime.timezone(datetime.timedelta(seconds=3600)))
+ 283±2ms 535±1ms 1.89 groupby.AggEngine.time_series_numba(False)
+ 284±2ms 534±2ms 1.88 groupby.AggEngine.time_dataframe_numba(False)
+ 11.8±0.3ms 21.4±0.4ms 1.81 io.csv.ToCSVDatetime.time_frame_date_formatting
+ 331±3ms 599±2ms 1.81 groupby.TransformEngine.time_series_numba(False)
+ 9.45±0.5ms 17.1±2ms 1.81 hash_functions.UniqueAndFactorizeArange.time_unique(4)
+ 16.8±0.1ms 30.3±0.8ms 1.80 gil.ParallelDatetimeFields.time_datetime_field_normalize
+ 65.8±2ms 113±2ms 1.71 series_methods.IsInFloat64.time_isin_many_different
+ 192±20μs 326±20μs 1.70 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 500000)
+ 37.2±0.1μs 62.3±0.09μs 1.68 tslibs.normalize.Normalize.time_is_date_array_normalized(10000, datetime.timezone(datetime.timedelta(seconds=3600)))
+ 13.9±0.4ms 23.2±1ms 1.67 hash_functions.UniqueAndFactorizeArange.time_factorize(4)
+ 508±2ms 837±5ms 1.65 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'skew')
+ 11.7±0.1ms 18.5±0.2ms 1.58 period.PeriodIndexConstructor.time_from_ints('D', False)
+ 11.8±0.1ms 18.5±0.5ms 1.57 period.PeriodIndexConstructor.time_from_ints('D', True)
+ 4.24±0.03ms 6.58±0.03ms 1.55 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.float64'>, 100000)
+ 438±1ms 680±2ms 1.55 series_methods.IsInLongSeriesValuesDominate.time_isin('float64', 'monotone')
+ 94.0±0.2ms 143±0.8ms 1.52 groupby.GroupByMethods.time_dtype_as_field('datetime', 'unique', 'transformation')
+ 94.2±0.1ms 143±0.5ms 1.52 groupby.GroupByMethods.time_dtype_as_field('datetime', 'unique', 'direct')
+ 616±3μs 937±8μs 1.52 stat_ops.FrameOps.time_op('sum', 'int', 0)
+ 21.3±0.8ms 32.4±0.7ms 1.52 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 19)
+ 41.1±0.3ms 62.2±20ms 1.51 rolling.Apply.time_rolling('Series', 300, 'int', <built-in function sum>, False)
+ 1.87±0.02ms 2.80±0ms 1.49 series_methods.IsIn.time_isin('uint64')
+ 27.7±0.2μs 41.1±0.1μs 1.48 tslibs.normalize.Normalize.time_is_date_array_normalized(10000, None)
+ 1.32±0s 1.95±0.01s 1.48 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'mad')
+ 2.97±0.01ms 4.40±0.7ms 1.48 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'count')
+ 2.93±0.02ms 4.32±0.6ms 1.47 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'count')
+ 1.46±0ms 2.14±0.04ms 1.47 groupby.FillNA.time_srs_ffill
+ 1.47±0.01ms 2.14±0.01ms 1.46 groupby.FillNA.time_srs_bfill
+ 96.7±0.1ms 141±2ms 1.46 rolling.Groupby.time_rolling_int('min')
+ 28.0±0.2μs 40.8±0.2μs 1.46 tslibs.normalize.Normalize.time_is_date_array_normalized(10000, datetime.timezone.utc)
+ 2.82±0.01ms 4.11±0.01ms 1.46 tslibs.normalize.Normalize.time_is_date_array_normalized(1000000, None)
+ 97.4±0.6ms 142±1ms 1.46 rolling.Groupby.time_rolling_int('kurt')
+ 18.5±0.1ms 27.0±0.2ms 1.46 frame_methods.Iteration.time_items
+ 2.81±0.1ms 4.09±0.01ms 1.46 tslibs.normalize.Normalize.time_is_date_array_normalized(1000000, datetime.timezone.utc)
+ 97.5±0.5ms 142±0.9ms 1.45 rolling.Groupby.time_rolling_int('mean')
+ 97.4±0.9ms 141±1ms 1.45 rolling.Groupby.time_rolling_int('max')
+ 751±4μs 1.09±0.01ms 1.45 stat_ops.FrameOps.time_op('mean', 'int', 0)
+ 99.9±0.7ms 144±1ms 1.44 rolling.Groupby.time_rolling_int('median')
+ 97.0±1ms 140±0.9ms 1.44 rolling.Groupby.time_rolling_int('sum')
+ 11.9±2ms 17.1±2ms 1.44 hash_functions.UniqueAndFactorizeArange.time_unique(15)
+ 2.98±0.02ms 4.27±0.7ms 1.43 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'count')
+ 9.98±0.4ms 14.3±0.5ms 1.43 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 18)
+ 8.77±0.02ms 12.5±0.03ms 1.43 frame_methods.ToString.time_to_string_floats
+ 4.25±0.03s 6.03±0.01s 1.42 replace.ReplaceDict.time_replace_series(False)
+ 786±10μs 1.11±0ms 1.41 stat_ops.FrameOps.time_op('prod', 'int', 0)
+ 122±0.5ms 173±0.8ms 1.41 frame_methods.Iteration.time_iteritems_indexing
+ 157±0.8ms 221±2ms 1.41 stat_ops.FrameMultiIndexOps.time_op(1, 'mad')
+ 134±0.8ms 188±20ms 1.41 gil.ParallelGroupbyMethods.time_loop(8, 'count')
+ 427±1ms 599±1ms 1.40 groupby.TransformEngine.time_dataframe_numba(False)
+ 284±3ms 398±8ms 1.40 frame_methods.GetDtypeCounts.time_info
+ 33.5±0.2ms 46.6±5ms 1.39 gil.ParallelGroupbyMethods.time_loop(2, 'count')
+ 74.5±0.4ms 103±0.9ms 1.38 stat_ops.FrameMultiIndexOps.time_op(1, 'skew')
+ 60.9±3ms 84.0±3ms 1.38 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 20)
+ 6.97±0.05ms 9.60±0.06ms 1.38 groupby.Apply.time_scalar_function_single_col
+ 223±5ms 304±4ms 1.36 groupby.MultiColumn.time_lambda_sum
+ 11.7±0.01ms 15.8±0.03ms 1.35 stat_ops.Correlation.time_corr_wide('pearson')
+ 25.4±0.4μs 34.2±0.2μs 1.35 indexing.NumericSeriesIndexing.time_iloc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 12.2±0.06μs 16.4±0.1μs 1.34 categoricals.CategoricalSlicing.time_getitem_slice('monotonic_decr')
+ 3.98±0.2ms 5.33±0.04ms 1.34 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'kurt')
+ 229±10ms 306±10ms 1.34 replace.ReplaceList.time_replace_list_one_match(False)
+ 26.1±0.4μs 34.9±0.7μs 1.34 indexing.NumericSeriesIndexing.time_iloc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc')
+ 14.4±0.06ms 19.2±0.7ms 1.33 strings.Cat.time_cat(0, None, None, 0.0)
+ 122±3ms 162±2ms 1.33 groupby.MultiColumn.time_col_select_lambda_sum
+ 12.3±0.05μs 16.4±0.3μs 1.33 categoricals.CategoricalSlicing.time_getitem_slice('non_monotonic')
+ 12.3±0.08μs 16.3±0.3μs 1.32 categoricals.CategoricalSlicing.time_getitem_slice('monotonic_incr')
+ 25.9±0.4μs 34.3±0.4μs 1.32 indexing.NumericSeriesIndexing.time_iloc_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc')
+ 58.0±0.2μs 76.3±1μs 1.32 indexing.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc')
+ 67.3±0.3ms 88.6±9ms 1.32 gil.ParallelGroupbyMethods.time_loop(4, 'count')
+ 2.53±0.03ms 3.33±0.02ms 1.32 categoricals.Indexing.time_sort_values
+ 26.3±0.4μs 34.6±0.2μs 1.31 indexing.NumericSeriesIndexing.time_iloc_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
+ 20.7±0.03ms 27.1±0.03ms 1.31 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 8000, -2)
+ 25.9±0.1μs 33.9±0.2μs 1.31 indexing.NumericSeriesIndexing.time_iloc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 2.38±0.02ms 3.12±0.03ms 1.31 groupby.FillNA.time_df_ffill
+ 4.33±0.01ms 5.66±0.02ms 1.31 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 1000, -2)
+ 60.3±0.4μs 78.8±0.8μs 1.31 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 100000)
+ 3.92±0.02ms 5.12±0.2ms 1.31 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'kurt')
+ 90.4±2ms 118±0.7ms 1.30 timeseries.Iteration.time_iter_preexit(<function timedelta_range at 0x7f2782aecaf0>)
+ 3.94±0.01ms 5.12±0.02ms 1.30 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'kurt')
+ 31.0±0.2μs 40.2±0.2μs 1.30 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc')
+ 3.09±0.3ms 4.00±0.06ms 1.30 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'kurt')
+ 2.42±0.01ms 3.13±0.02ms 1.29 groupby.FillNA.time_df_bfill
+ 8.73±0.3ms 11.3±0.05ms 1.29 timeseries.ResampleSeries.time_resample('period', '5min', 'ohlc')
+ 105±1ms 135±0.6ms 1.29 groupby.Groups.time_series_groups('int64_large')
+ 29.4±0.2ms 37.8±0.2ms 1.29 rolling.Apply.time_rolling('Series', 3, 'int', <built-in function sum>, False)
+ 455±1ms 584±0.7ms 1.28 series_methods.IsInLongSeriesValuesDominate.time_isin('float32', 'monotone')
+ 8.95±0.03ms 11.5±0.1ms 1.28 index_object.IntervalIndexMethod.time_intersection(100000)
+ 2.60±0.02ms 3.33±0.09ms 1.28 stat_ops.SeriesMultiIndexOps.time_op(1, 'prod')
+ 3.20±0.02ms 4.10±0.03ms 1.28 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'kurt')
+ 29.9±0.2ms 38.2±0.2ms 1.28 rolling.Apply.time_rolling('Series', 3, 'float', <built-in function sum>, False)
+ 29.9±0.3μs 38.2±0.1μs 1.28 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'non_monotonic')
+ 18.3±1ms 23.2±1ms 1.27 hash_functions.UniqueAndFactorizeArange.time_factorize(14)
+ 30.2±0.6μs 38.4±0.4μs 1.27 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'unique_monotonic_inc')
+ 31.3±0.4μs 39.8±0.3μs 1.27 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
+ 16.1±0.09ms 20.5±0.2ms 1.27 groupby.AggFunctions.time_different_str_functions
+ 30.3±0.5μs 38.3±0.4μs 1.27 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'nonunique_monotonic_inc')
+ 30.2±0.2ms 38.2±0.4ms 1.27 rolling.Apply.time_rolling('DataFrame', 3, 'float', <built-in function sum>, False)
+ 2.62±0.02ms 3.32±0.1ms 1.27 stat_ops.SeriesMultiIndexOps.time_op(1, 'sum')
+ 3.07±0.02ms 3.89±0.02ms 1.26 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'kurt')
+ 3.90±0.01ms 4.91±0.02ms 1.26 series_methods.IsInDatetime64.time_isin_cat_values
+ 115±0.5μs 145±1μs 1.26 tslibs.normalize.Normalize.time_is_date_array_normalized(10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
+ 2.61±0.03ms 3.30±0.1ms 1.26 stat_ops.SeriesMultiIndexOps.time_op(0, 'sum')
+ 14.6±0.6ms 18.3±1ms 1.26 tslibs.normalize.Normalize.time_is_date_array_normalized(1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
+ 21.1±0.04ms 26.4±0.07ms 1.25 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 8000, 2)
+ 4.50±0.03μs 5.64±0.05μs 1.25 categoricals.CategoricalSlicing.time_getitem_scalar('non_monotonic')
+ 16.1±0.08ms 20.2±0.09ms 1.25 groupby.AggFunctions.time_different_numpy_functions
+ 30.2±0.3ms 37.9±0.1ms 1.25 rolling.Apply.time_rolling('DataFrame', 3, 'int', <built-in function sum>, False)
+ 359±0.5ms 450±4ms 1.25 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 5, 'monotone_misses')
+ 37.2±0.5μs 46.4±0.4μs 1.25 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'non_monotonic')
+ 142±0.4ms 177±0.3ms 1.24 hash_functions.IsinWithArange.time_isin(<class 'object'>, 2000, 2)
+ 21.7±0.1ms 26.9±0.1ms 1.24 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 8000, -2)
+ 271±2μs 335±3μs 1.24 reindex.Fillna.time_float_32('backfill')
+ 6.95±0.04ms 8.58±0.1ms 1.23 stat_ops.Correlation.time_corrwith_cols('pearson')
+ 48.1±0.4μs 59.3±0.6μs 1.23 frame_methods.GetNumericData.time_frame_get_numeric_data
+ 45.7±0.2μs 56.4±0.8μs 1.23 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 10000)
+ 6.06±0.4ms 7.47±0.4ms 1.23 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'sum')
+ 6.22±0.07μs 7.67±0.04μs 1.23 dtypes.Dtypes.time_pandas_dtype('Int8')
+ 108±0.2ms 133±0.2ms 1.23 hash_functions.IsinWithArange.time_isin(<class 'object'>, 2000, -2)
+ 9.49±0.08μs 11.7±0.1μs 1.23 indexing.CategoricalIndexIndexing.time_getitem_scalar('monotonic_incr')
+ 4.53±0.04μs 5.57±0.04μs 1.23 categoricals.CategoricalSlicing.time_getitem_scalar('monotonic_decr')
+ 4.13±0.1ms 5.07±0.2ms 1.23 tslibs.normalize.Normalize.time_normalize_i8_timestamps(1000000, None)
+ 4.54±0.04μs 5.57±0.03μs 1.23 categoricals.CategoricalSlicing.time_getitem_scalar('monotonic_incr')
+ 137±1μs 168±2μs 1.23 hash_functions.IsinWithArangeSorted.time_isin(<class 'object'>, 1000)
+ 56.4±0.3μs 68.9±1μs 1.22 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 1.54±0.02ms 1.88±0.03ms 1.22 reindex.ReindexMethod.time_reindex_method('pad', <function period_range at 0x7f2782af4700>)
+ 3.76±0.2ms 4.59±0.03ms 1.22 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'skew')
+ 25.7±0.3ms 31.4±0.4ms 1.22 groupby.ApplyDictReturn.time_groupby_apply_dict_return
+ 1.19±0.02μs 1.45±0.01μs 1.21 tslibs.normalize.Normalize.time_is_date_array_normalized(100, None)
+ 56.6±0.6μs 68.8±1μs 1.21 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 62.8±0.1μs 76.0±1μs 1.21 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 100000)
+ 4.14±0.01ms 5.00±0.02ms 1.21 tslibs.normalize.Normalize.time_normalize_i8_timestamps(1000000, datetime.timezone.utc)
+ 325±20ms 392±10ms 1.21 indexing.NumericSeriesIndexing.time_getitem_lists(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 28.4±0.2ms 34.3±0.2ms 1.21 groupby.AggFunctions.time_different_python_functions_multicol
+ 134±2μs 161±0.9μs 1.21 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'object'>, 10)
+ 58.9±2ms 71.2±3ms 1.21 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 20)
+ 5.19±0.04ms 6.27±0.04ms 1.21 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 17)
+ 9.55±0.1μs 11.5±0.09μs 1.20 indexing.CategoricalIndexIndexing.time_getitem_scalar('monotonic_decr')
+ 513±0.7μs 617±3μs 1.20 stat_ops.Correlation.time_corr('pearson')
+ 891±10μs 1.07±0.01ms 1.20 reindex.ReindexMethod.time_reindex_method('pad', <function date_range at 0x7f2782b204c0>)
+ 321±20ms 385±10ms 1.20 indexing.NumericSeriesIndexing.time_loc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 2.62±0.02ms 3.15±0.07ms 1.20 stat_ops.SeriesMultiIndexOps.time_op(0, 'prod')
+ 323±20ms 388±10ms 1.20 indexing.NumericSeriesIndexing.time_loc_array(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 86.7±0.6ms 104±0.5ms 1.20 frame_methods.ToHTML.time_to_html_mixed
+ 8.31±0.07ms 9.97±0.05ms 1.20 frame_methods.Apply.time_apply_pass_thru
+ 44.7±0.3μs 53.6±0.08μs 1.20 tslibs.normalize.Normalize.time_normalize_i8_timestamps(10000, None)
+ 182±0.4μs 218±2μs 1.20 hash_functions.IsinWithArangeSorted.time_isin(<class 'object'>, 2000)
+ 4.64±0.02ms 5.56±0.05ms 1.20 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'kurt')
+ 5.25±0.03ms 6.28±0.1ms 1.20 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 2000, 0)
+ 653±2μs 782±4μs 1.20 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 8000)
+ 7.09±0.06μs 8.48±0.03μs 1.20 dtypes.Dtypes.time_pandas_dtype('Int16')
+ 609±4ms 728±2ms 1.20 frame_methods.Nunique.time_frame_nunique
+ 324±20ms 387±10ms 1.20 indexing.NumericSeriesIndexing.time_getitem_array(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 22.0±0.07ms 26.3±0.04ms 1.20 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 8000, 2)
+ 50.4±0.2μs 60.2±0.3μs 1.20 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'nonunique_monotonic_inc')
+ 130±2μs 155±0.7μs 1.19 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('datetime', 'unique_monotonic_inc')
+ 595±2ms 710±1ms 1.19 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 5000000)
+ 44.9±0.08μs 53.5±0.1μs 1.19 tslibs.normalize.Normalize.time_normalize_i8_timestamps(10000, datetime.timezone.utc)
+ 122±0.9μs 146±3μs 1.19 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('datetime', 'non_monotonic')
+ 603±5μs 719±4μs 1.19 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 7000)
+ 82.4±0.8μs 98.2±0.3μs 1.19 indexing.DataFrameNumericIndexing.time_iloc
+ 16.0±0.1ms 19.1±0.05ms 1.19 categoricals.Isin.time_isin_categorical('object')
+ 90.3±0.6μs 107±2μs 1.19 indexing.NumericSeriesIndexing.time_iloc_array(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc')
+ 196±0.6ms 233±2ms 1.19 groupby.Groups.time_series_groups('object_large')
+ 47.3±0.2μs 56.2±0.7μs 1.19 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 10000)
+ 9.68±0.07μs 11.5±0.09μs 1.19 indexing.CategoricalIndexIndexing.time_getitem_scalar('non_monotonic')
+ 1.06±0ms 1.25±0ms 1.19 timeseries.DatetimeIndex.time_unique('repeated')
+ 4.66±0.02ms 5.52±0.02ms 1.18 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'kurt')
+ 4.54±0.03ms 5.38±0.05ms 1.18 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'kurt')
+ 2.59±0.01ms 3.07±0.01ms 1.18 series_methods.IsInForObjects.time_isin_long_series_short_values
+ 5.40±0.02ms 6.39±0.06ms 1.18 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 8000, 0)
+ 136±1ms 161±0.5ms 1.18 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 900000)
+ 326±20ms 385±20ms 1.18 indexing.NumericSeriesIndexing.time_getitem_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 66.1±1μs 78.1±0.4μs 1.18 indexing.DataFrameNumericIndexing.time_loc
+ 3.86±0.2ms 4.55±0.01ms 1.18 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'midpoint')
+ 667±10μs 785±5μs 1.18 groupby.GroupManyLabels.time_sum(1)
+ 3.38±0.04ms 3.98±0.08ms 1.18 stat_ops.SeriesMultiIndexOps.time_op(1, 'var')
+ 7.51±0.03μs 8.84±0.2μs 1.18 dtypes.Dtypes.time_pandas_dtype('interval')
+ 2.88±0.02ms 3.39±0.06ms 1.18 stat_ops.FrameMultiIndexOps.time_op(0, 'sum')
+ 2.84±0.04ms 3.34±0.05ms 1.18 stat_ops.FrameMultiIndexOps.time_op(0, 'mean')
+ 26.8±0.1ms 31.5±0.06ms 1.18 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 2000, -2)
+ 3.86±0.2ms 4.54±0.02ms 1.18 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'lower')
+ 145±1μs 170±0.8μs 1.18 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'object'>, 10)
+ 9.33±0.05μs 11.0±0.04μs 1.18 dtypes.Dtypes.time_pandas_dtype('UInt8')
+ 2.89±0.02ms 3.39±0.03ms 1.17 stat_ops.FrameMultiIndexOps.time_op(1, 'prod')
+ 5.21±0.02ms 6.12±0.01ms 1.17 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 1000, 0)
+ 2.24±0.03ms 2.63±0.04ms 1.17 stat_ops.FrameOps.time_op('var', 'int', 0)
+ 7.86±0.03μs 9.22±0.03μs 1.17 dtypes.Dtypes.time_pandas_dtype('Int32')
+ 5.03±0.03ms 5.90±0.03ms 1.17 tslibs.normalize.Normalize.time_normalize_i8_timestamps(1000000, datetime.timezone(datetime.timedelta(seconds=3600)))
+ 26.4±0.03ms 30.9±0.04ms 1.17 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 2000, 2)
+ 4.72±0.06ms 5.53±0.06ms 1.17 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 80000)
+ 909±4μs 1.06±0.05ms 1.17 dtypes.SelectDtypes.time_select_dtype_int_include(<class 'float'>)
+ 2.86±0.04ms 3.35±0.02ms 1.17 stat_ops.FrameMultiIndexOps.time_op(1, 'mean')
+ 8.63±0.05μs 10.1±0.5μs 1.17 dtypes.Dtypes.time_pandas_dtype('Int64')
+ 90.9±0.8μs 106±1μs 1.17 indexing.NumericSeriesIndexing.time_iloc_array(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc')
+ 199±0.3ms 232±1ms 1.17 frame_methods.Apply.time_apply_axis_1
+ 3.89±0.2ms 4.54±0.01ms 1.17 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'nearest')
+ 76.3±1ms 89.0±0.6ms 1.17 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 750000)
+ 739±5μs 862±2μs 1.17 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 8000)
+ 4.64±0.03ms 5.41±0.03ms 1.17 index_object.Indexing.time_get_loc_non_unique('Float')
+ 3.39±0.03ms 3.96±0.05ms 1.17 stat_ops.SeriesMultiIndexOps.time_op(0, 'var')
+ 997±40ns 1.16±0.04μs 1.17 index_cached_properties.IndexCache.time_is_monotonic_increasing('Int64Index')
+ 3.04±0.02ms 3.55±0.04ms 1.17 stat_ops.FrameMultiIndexOps.time_op(0, 'prod')
+ 2.94±0.02ms 3.42±0.05ms 1.17 groupby.TransformBools.time_transform_mean
+ 3.88±0.1ms 4.52±0.02ms 1.16 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'higher')
+ 2.22±0.06ms 2.58±0.02ms 1.16 frame_methods.Lookup.time_frame_fancy_lookup
+ 11.3±0.04ms 13.1±0.3ms 1.16 index_object.IntervalIndexMethod.time_intersection_one_duplicate(100000)
+ 1.41±0ms 1.63±0ms 1.16 timeseries.DatetimeIndex.time_normalize('tz_naive')
+ 81.8±0.2ms 95.0±0.2ms 1.16 series_methods.IsInFloat64.time_isin_nan_values
+ 3.90±0.2ms 4.53±0.03ms 1.16 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'lower')
+ 3.90±0.2ms 4.53±0.02ms 1.16 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'nearest')
+ 90.6±1μs 105±1μs 1.16 indexing.NumericSeriesIndexing.time_iloc_array(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc')
+ 41.0±0.3ms 47.6±0.1ms 1.16 rolling.Apply.time_rolling('Series', 300, 'float', <built-in function sum>, False)
+ 3.91±0.2ms 4.53±0.02ms 1.16 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'linear')
+ 95.6±0.2ms 111±0.9ms 1.16 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 1000, 'random_misses')
+ 662±3μs 768±2μs 1.16 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 7000)
+ 90.6±1μs 105±2μs 1.16 indexing.NumericSeriesIndexing.time_iloc_array(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 2.31±0.02ms 2.67±0.03ms 1.16 stat_ops.FrameOps.time_op('std', 'int', 0)
+ 78.7±0.4ms 91.1±1ms 1.16 period.PeriodIndexConstructor.time_from_ints_daily('D', True)
+ 3.91±0.1ms 4.53±0.01ms 1.16 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'midpoint')
+ 366±2μs 424±4μs 1.16 groupby.GroupByMethods.time_dtype_as_field('datetime', 'shift', 'direct')
+ 129±1ms 149±1ms 1.16 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 900000)
+ 894±7ns 1.03±0.02μs 1.16 tslibs.normalize.Normalize.time_is_date_array_normalized(0, None)
+ 440±5μs 509±3μs 1.16 hash_functions.IsinWithArangeSorted.time_isin(<class 'object'>, 8000)
+ 3.75±0.04ms 4.33±0.04ms 1.16 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 70000)
+ 91.0±0.4μs 105±2μs 1.15 indexing.NumericSeriesIndexing.time_iloc_array(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 10.7±0.2ms 12.4±0.4ms 1.15 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'median')
+ 40.5±0.8ms 46.7±1ms 1.15 stat_ops.FrameMultiIndexOps.time_op(0, 'mad')
+ 25.4±0.08ms 29.3±0.09ms 1.15 hash_functions.IsinWithArange.time_isin(<class 'numpy.int64'>, 1000, 2)
+ 91.4±1μs 105±0.9μs 1.15 indexing.NumericSeriesIndexing.time_iloc_array(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
+ 1.42±0.01ms 1.63±0.01ms 1.15 timeseries.DatetimeIndex.time_normalize('repeated')
+ 177±1μs 204±0.9μs 1.15 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'object'>, 11)
+ 15.8±0.03ms 18.2±0.3ms 1.15 eval.Query.time_query_datetime_index
+ 10.1±0.04μs 11.6±0.03μs 1.15 dtypes.Dtypes.time_pandas_dtype('UInt16')
+ 41.6±0.2ms 47.9±0.3ms 1.15 rolling.Apply.time_rolling('DataFrame', 300, 'int', <built-in function sum>, False)
+ 6.71±0.3μs 7.72±0.3μs 1.15 index_cached_properties.IndexCache.time_shape('IntervalIndex')
+ 79.0±0.2ms 90.9±0.9ms 1.15 period.PeriodIndexConstructor.time_from_ints_daily('D', False)
+ 532±9ns 612±10ns 1.15 multiindex_object.Integer.time_is_monotonic
+ 141±3μs 162±0.4μs 1.15 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('datetime', 'nonunique_monotonic_inc')
+ 481±0.9ms 554±4ms 1.15 frame_methods.Iteration.time_iterrows
+ 27.4±0.3μs 31.5±0.8μs 1.15 indexing.CategoricalIndexIndexing.time_getitem_slice('monotonic_decr')
+ 3.72±0.01ms 4.28±0.01ms 1.15 series_methods.IsInDatetime64.time_isin
+ 1.74±0ms 2.00±0.01ms 1.15 timeseries.DatetimeAccessor.time_dt_accessor_normalize(tzutc())
+ 453±3μs 520±2μs 1.15 reindex.DropDuplicates.time_series_drop_dups_int(False)
+ 31.8±0.6ms 36.5±0.8ms 1.15 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 19)
+ 2.94±0.04ms 3.38±0.02ms 1.15 stat_ops.FrameMultiIndexOps.time_op(1, 'sum')
+ 409±2μs 469±3μs 1.15 reindex.DropDuplicates.time_series_drop_dups_string(True)
+ 5.21±0.03ms 5.97±0.3ms 1.15 stat_ops.SeriesMultiIndexOps.time_op(1, 'median')
+ 3.94±0.2ms 4.52±0.02ms 1.15 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 0, 'linear')
+ 895±10ns 1.03±0.01μs 1.15 tslibs.normalize.Normalize.time_is_date_array_normalized(1, None)
+ 27.6±0.3μs 31.6±0.5μs 1.15 indexing.CategoricalIndexIndexing.time_getitem_slice('monotonic_incr')
+ 47.7±0.4ms 54.7±0.7ms 1.15 gil.ParallelGroupbyMethods.time_parallel(4, 'max')
+ 73.3±0.4μs 84.0±0.9μs 1.15 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 10000)
+ 154±1μs 177±2μs 1.15 groupby.GroupByMethods.time_dtype_as_group('int', 'size', 'direct')
+ 258±0.4μs 295±1μs 1.14 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 2000)
+ 369±2μs 422±4μs 1.14 groupby.GroupByMethods.time_dtype_as_field('datetime', 'shift', 'transformation')
+ 1.72±0ms 1.96±0.02ms 1.14 timeseries.DatetimeAccessor.time_dt_accessor_normalize(None)
+ 1.78±0.02ms 2.04±0.01ms 1.14 series_methods.IsIn.time_isin('int64')
+ 3.42±0.03ms 3.91±0.1ms 1.14 stat_ops.SeriesMultiIndexOps.time_op(0, 'std')
+ 74.6±0.7μs 85.2±0.4μs 1.14 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 10000)
+ 41.7±0.2ms 47.6±0.2ms 1.14 rolling.Apply.time_rolling('DataFrame', 300, 'float', <built-in function sum>, False)
+ 54.2±0.4μs 61.8±0.4μs 1.14 inference.ToNumeric.time_from_float('coerce')
+ 15.2±0.2ms 17.3±0.2ms 1.14 eval.Query.time_query_datetime_column
+ 279±2μs 318±0.8μs 1.14 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 2000)
+ 54.2±0.9μs 61.8±0.5μs 1.14 inference.ToNumeric.time_from_float('ignore')
+ 3.23±0.02ms 3.69±0.02ms 1.14 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 70000)
+ 2.16±0.01μs 2.46±0.06μs 1.14 attrs_caching.SeriesArrayAttribute.time_array('object')
+ 1.74±0.01ms 1.98±0.01ms 1.14 timeseries.DatetimeAccessor.time_dt_accessor_normalize('UTC')
+ 2.16±0.02μs 2.45±0.05μs 1.14 attrs_caching.SeriesArrayAttribute.time_array('numeric')
+ 441±3μs 501±4μs 1.14 strings.Encode.time_encode_decode
+ 2.70±0.01ms 3.07±0.01ms 1.14 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 16)
+ 26.7±0.2ms 30.3±0.3ms 1.14 groupby.Groups.time_series_groups('int64_small')
+ 63.0±0.2μs 71.5±0.3μs 1.13 tslibs.normalize.Normalize.time_normalize_i8_timestamps(10000, datetime.timezone(datetime.timedelta(seconds=3600)))
+ 252±2μs 286±3μs 1.13 arithmetic.NumericInferOps.time_subtract(<class 'numpy.int8'>)
+ 254±2μs 288±2μs 1.13 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'object'>, 12)
+ 214±0.7ms 242±0.4ms 1.13 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 1000, 'monotone_hits')
+ 74.6±1ms 84.6±0.6ms 1.13 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 750000)
+ 27.6±0.3μs 31.3±0.5μs 1.13 indexing.CategoricalIndexIndexing.time_getitem_slice('non_monotonic')
+ 323±2μs 366±2μs 1.13 index_object.IntervalIndexMethod.time_intersection(1000)
+ 152±1μs 173±1μs 1.13 groupby.GroupByMethods.time_dtype_as_field('datetime', 'size', 'transformation')
+ 27.4±0.03ms 31.0±0.06ms 1.13 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 8000, 2)
+ 14.3±0.2μs 16.2±0.1μs 1.13 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'non_monotonic')
+ 65.5±0.7μs 74.1±0.3μs 1.13 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 79.4±0.09ms 89.9±0.2ms 1.13 hash_functions.IsinWithArange.time_isin(<class 'object'>, 1000, -2)
+ 4.01±0.2ms 4.53±0.02ms 1.13 rolling.Quantile.time_quantile('DataFrame', 1000, 'float', 1, 'higher')
+ 127±0.1ms 144±0.3ms 1.13 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 5, 'monotone_hits')
+ 915±5μs 1.03±0.01ms 1.13 dtypes.SelectDtypes.time_select_dtype_string_include('Int8')
+ 21.6±0.4μs 24.4±0.08μs 1.13 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'nonunique_monotonic_inc')
+ 64.5±0.4μs 72.9±0.4μs 1.13 indexing.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
+ 4.15±0.04ms 4.69±0.06ms 1.13 hash_functions.IsinWithRandomFloat.time_isin(<class 'numpy.float64'>, 80000)
+ 907±4μs 1.02±0.01ms 1.13 dtypes.SelectDtypes.time_select_dtype_string_include(<class 'int'>)
+ 534±1μs 603±7μs 1.13 frame_methods.Iteration.time_itertuples_raw_start
+ 156±0.9ms 176±1ms 1.13 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 5, 'random_hits')
+ 81.4±1ms 92.0±0.7ms 1.13 arithmetic.BinaryOpsMultiIndex.time_binary_op_multiindex('add')
+ 535±5μs 604±6μs 1.13 frame_methods.Iteration.time_itertuples_raw_read_first
+ 943±7μs 1.06±0.02ms 1.13 dtypes.SelectDtypes.time_select_dtype_string_include('m8[ns]')
+ 154±1μs 174±0.8μs 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'size', 'transformation')
+ 152±0.8μs 172±1μs 1.13 groupby.GroupByMethods.time_dtype_as_group('object', 'size', 'transformation')
+ 27.8±0.2ms 31.3±0.05ms 1.13 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 2000, -2)
+ 121±2μs 136±2μs 1.13 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.int64'>, 10)
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+ 153±1μs 172±2μs 1.13 groupby.GroupByMethods.time_dtype_as_field('datetime', 'size', 'direct')
+ 11.0±0.06μs 12.4±0.07μs 1.13 dtypes.Dtypes.time_pandas_dtype('UInt32')
+ 1.00±0.01ms 1.13±0.01ms 1.13 dtypes.SelectDtypes.time_select_dtype_int_exclude('Int64')
+ 920±4μs 1.04±0.01ms 1.13 dtypes.SelectDtypes.time_select_dtype_string_include('Int64')
+ 924±3μs 1.04±0.01ms 1.13 dtypes.SelectDtypes.time_select_dtype_int_include('Int32')
+ 946±10μs 1.06±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_float_include('float32')
+ 152±1μs 171±2μs 1.12 groupby.GroupByMethods.time_dtype_as_field('int', 'size', 'transformation')
+ 987±3μs 1.11±0ms 1.12 dtypes.SelectDtypes.time_select_dtype_int_exclude(<class 'int'>)
+ 205±0.6μs 230±0.9μs 1.12 tslibs.normalize.Normalize.time_is_date_array_normalized(10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
+ 938±5μs 1.05±0.02ms 1.12 dtypes.SelectDtypes.time_select_dtype_string_include('bool')
+ 79.2±0.4μs 89.0±0.6μs 1.12 hash_functions.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 10000)
+ 1.00±0.01ms 1.13±0.01ms 1.12 frame_methods.SelectDtypes.time_select_dtypes(1000)
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+ 903±3μs 1.01±0ms 1.12 dtypes.SelectDtypes.time_select_dtype_int_include(<class 'bool'>)
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+ 938±5μs 1.05±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_bool_include('uint16')
+ 44.9±0.5μs 50.4±0.1μs 1.12 arithmetic.Ops2.time_series_dot
+ 935±1μs 1.05±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_bool_include('M8[ns]')
+ 917±2μs 1.03±0.02ms 1.12 dtypes.SelectDtypes.time_select_dtype_int_include('Int16')
+ 937±5μs 1.05±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_string_include('float64')
+ 158±0.9μs 177±0.9μs 1.12 groupby.GroupByMethods.time_dtype_as_group('float', 'size', 'transformation')
+ 14.8±0.08μs 16.6±0.1μs 1.12 dtypes.Dtypes.time_pandas_dtype('float32')
+ 3.71±0.02ms 4.16±0.04ms 1.12 hash_functions.IsinWithArangeSorted.time_isin(<class 'object'>, 100000)
+ 152±2μs 171±0.9μs 1.12 groupby.GroupByMethods.time_dtype_as_group('object', 'size', 'direct')
+ 226±7ms 254±5ms 1.12 indexing.NumericSeriesIndexing.time_loc_array(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
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+ 11.7±0.06μs 13.1±0.03μs 1.12 dtypes.Dtypes.time_pandas_dtype('UInt64')
+ 930±6μs 1.04±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_float_include('UInt16')
+ 922±4μs 1.03±0ms 1.12 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt8')
+ 152±1μs 171±0.9μs 1.12 groupby.GroupByMethods.time_dtype_as_field('object', 'size', 'transformation')
+ 913±6μs 1.02±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_float_include(<class 'bool'>)
+ 3.76±0.05ms 4.21±0.05ms 1.12 stat_ops.FrameMultiIndexOps.time_op(1, 'var')
+ 5.85±0.02ms 6.55±0.01ms 1.12 frame_methods.Repr.time_html_repr_trunc_si
+ 923±6μs 1.03±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_int_include('UInt16')
+ 944±9μs 1.06±0.02ms 1.12 dtypes.SelectDtypes.time_select_dtype_string_include('timedelta64[ns]')
+ 1.61±0.02ms 1.81±0.02ms 1.12 reindex.ReindexMethod.time_reindex_method('backfill', <function period_range at 0x7f2782af4700>)
+ 927±2μs 1.04±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_float_include('UInt32')
+ 880±8μs 984±9μs 1.12 groupby.GroupByMethods.time_dtype_as_group('float', 'sem', 'direct')
+ 24.3±0.4ms 27.2±0.8ms 1.12 timeseries.ToDatetimeFormat.time_no_exact
+ 939±4μs 1.05±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_string_include('uint16')
+ 27.4±0.1ms 30.7±0.07ms 1.12 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 2000, 2)
+ 937±0.6μs 1.05±0ms 1.12 dtypes.SelectDtypes.time_select_dtype_float_include('m8[ns]')
+ 112±3ms 125±0.9ms 1.12 io.json.ToJSON.time_to_json('split', 'df_date_idx')
+ 937±2μs 1.05±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_bool_include('float64')
+ 109±1ms 122±2ms 1.12 io.json.ToJSON.time_to_json('records', 'df')
+ 3.26±0.01ms 3.65±0.02ms 1.12 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'skew')
+ 25.6±0.06ms 28.6±0.2ms 1.12 groupby.Apply.time_scalar_function_multi_col
+ 90.7±2ms 101±3ms 1.12 gil.ParallelGroupbyMethods.time_parallel(8, 'min')
+ 905±3μs 1.01±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_bool_include(<class 'float'>)
+ 1.02±0ms 1.14±0ms 1.12 dtypes.SelectDtypes.time_select_dtype_int_exclude('int64')
+ 943±4μs 1.05±0ms 1.12 dtypes.SelectDtypes.time_select_dtype_float_include('uint32')
+ 4.68±0.04ms 5.22±0.07ms 1.12 stat_ops.SeriesMultiIndexOps.time_op(1, 'sem')
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+ 932±4μs 1.04±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_string_include('UInt32')
+ 937±3μs 1.04±0.01ms 1.12 dtypes.SelectDtypes.time_select_dtype_string_include('uint8')
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+ 938±2μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_bool_include('int8')
+ 3.74±0.05ms 4.17±0.02ms 1.11 stat_ops.FrameMultiIndexOps.time_op(0, 'var')
+ 948±3μs 1.06±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_int_include('complex128')
+ 2.47±0.01ms 2.76±0.09ms 1.11 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '_', None)
+ 14.8±0.05μs 16.5±0.2μs 1.11 dtypes.Dtypes.time_pandas_dtype('int8')
+ 991±4μs 1.10±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_bool_exclude(<class 'bool'>)
+ 945±8μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_bool_include('complex64')
+ 945±7μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_float_include('datetime64[ns]')
+ 911±5μs 1.01±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include(<class 'bool'>)
+ 944±9μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_bool_include('float32')
+ 846±6μs 941±3μs 1.11 groupby.GroupByMethods.time_dtype_as_field('float', 'sem', 'direct')
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+ 945±7μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_float_include('timedelta64[ns]')
+ 82.5±3ms 91.7±1ms 1.11 arithmetic.BinaryOpsMultiIndex.time_binary_op_multiindex('div')
+ 943±5μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_bool_include('int16')
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+ 1.95±0.02ms 2.17±0.01ms 1.11 groupby.Datelike.time_sum('date_range')
+ 929±3μs 1.03±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('UInt64')
+ 2.92±0.02ms 3.24±0.02ms 1.11 reindex.DropDuplicates.time_frame_drop_dups_bool(False)
+ 940±7μs 1.04±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('datetime64[ns]')
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+ 525±3μs 583±5μs 1.11 groupby.GroupByMethods.time_dtype_as_field('datetime', 'ffill', 'direct')
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+ 10.1±0.4ms 11.3±0.2ms 1.11 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'sem')
+ 68.4±0.3ms 76.0±0.5ms 1.11 groupby.GroupByMethods.time_dtype_as_field('int', 'unique', 'direct')
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+ 938±6μs 1.04±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_bool_include('int64')
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+ 945±6μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('uint64')
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+ 945±8μs 1.05±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('int16')
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+ 252±4μs 280±2μs 1.11 arithmetic.NumericInferOps.time_subtract(<class 'numpy.uint8'>)
+ 3.58±0.04ms 3.97±0.05ms 1.11 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '.', 'round_trip')
+ 909±4μs 1.01±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_float_include(<class 'complex'>)
+ 4.35±0.02ms 4.83±0.03ms 1.11 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'skew')
+ 948±10μs 1.05±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('complex128')
+ 1.02±0ms 1.14±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_float_exclude('float64')
+ 69.2±0.7μs 76.7±1μs 1.11 ctors.SeriesConstructors.time_series_constructor(<function no_change at 0x7f277fe8ac10>, False, 'float')
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+ 932±0.9μs 1.03±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('UInt16')
+ 868±3μs 963±9μs 1.11 groupby.GroupByMethods.time_dtype_as_group('int', 'sem', 'transformation')
+ 850±5μs 943±9μs 1.11 groupby.GroupByMethods.time_dtype_as_field('int', 'sem', 'direct')
+ 86.0±0.3μs 95.3±1μs 1.11 frame_methods.XS.time_frame_xs(0)
+ 3.73±0.02ms 4.13±0.04ms 1.11 series_methods.IsInForObjects.time_isin_long_series_long_values
+ 14.9±0.06μs 16.5±0.1μs 1.11 dtypes.Dtypes.time_pandas_dtype('int64')
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+ 880±7μs 975±5μs 1.11 groupby.GroupByMethods.time_dtype_as_group('float', 'sem', 'transformation')
+ 526±5μs 583±5μs 1.11 groupby.GroupByMethods.time_dtype_as_field('datetime', 'bfill', 'transformation')
+ 6.01±0.1μs 6.66±0.1μs 1.11 index_object.Indexing.time_get_loc('Int')
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+ 926±3μs 1.02±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_int_include('Int8')
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+ 46.2±1ms 51.1±0.4ms 1.11 gil.ParallelGroupbyMethods.time_parallel(4, 'last')
+ 87.1±1μs 96.4±2μs 1.11 ctors.SeriesConstructors.time_series_constructor(<function no_change at 0x7f277fe8ac10>, True, 'float')
+ 14.9±0.05μs 16.5±0.04μs 1.11 dtypes.Dtypes.time_pandas_dtype('float64')
+ 939±6μs 1.04±0ms 1.11 dtypes.SelectDtypes.time_select_dtype_int_include('uint32')
+ 290±2μs 321±2μs 1.11 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'object'>, 12)
+ 109±2ms 121±1ms 1.11 io.json.ToJSON.time_to_json('records', 'df_date_idx')
+ 25.8±0.1ms 28.5±0.09ms 1.11 hash_functions.IsinWithArange.time_isin(<class 'object'>, 1000, 0)
+ 14.9±0.07μs 16.5±0.09μs 1.11 dtypes.Dtypes.time_pandas_dtype('uint32')
+ 738±2ms 817±2ms 1.11 groupby.GroupByMethods.time_dtype_as_group('int', 'mad', 'direct')
+ 87.9±0.5μs 97.2±0.6μs 1.11 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('datetime', 'nonunique_monotonic_inc')
+ 14.9±0.06μs 16.5±0.06μs 1.11 dtypes.Dtypes.time_pandas_dtype('uint8')
+ 932±2μs 1.03±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_string_include('Int32')
+ 167±1μs 185±2μs 1.11 groupby.GroupByMethods.time_dtype_as_field('datetime', 'count', 'transformation')
+ 9.24±0.07ms 10.2±0.04ms 1.11 frame_methods.Repr.time_html_repr_trunc_mi
+ 191±0.5ms 211±2ms 1.11 io.style.RenderApply.time_render(24, 120)
+ 159±1μs 176±1μs 1.11 groupby.GroupByMethods.time_dtype_as_group('float', 'size', 'direct')
+ 945±10μs 1.04±0.01ms 1.11 dtypes.SelectDtypes.time_select_dtype_float_include('bool')
+ 15.0±0.03μs 16.6±0.04μs 1.11 dtypes.Dtypes.time_pandas_dtype('datetime64')
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+ 940±6μs 1.04±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_string_include('M8[ns]')
+ 867±3μs 958±4μs 1.10 groupby.GroupByMethods.time_dtype_as_group('int', 'sem', 'direct')
+ 932±7μs 1.03±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt64')
+ 944±5μs 1.04±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_int_include('M8[ns]')
+ 228±5ms 252±7ms 1.10 indexing.NumericSeriesIndexing.time_getitem_array(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc')
+ 155±0.8μs 171±0.7μs 1.10 groupby.GroupByMethods.time_dtype_as_field('object', 'size', 'direct')
+ 1.15±0s 1.27±0s 1.10 groupby.GroupByMethods.time_dtype_as_group('float', 'mad', 'transformation')
+ 150±0.3μs 166±1μs 1.10 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.int64'>, 2000)
+ 852±10μs 940±4μs 1.10 groupby.GroupByMethods.time_dtype_as_field('float', 'sem', 'transformation')
+ 933±9μs 1.03±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt16')
+ 954±3μs 1.05±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_bool_include('m8[ns]')
+ 1.03±0.01ms 1.13±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_bool_exclude('bool')
+ 128±2μs 141±2μs 1.10 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.int64'>, 10)
+ 2.92±0.03ms 3.22±0.1ms 1.10 stat_ops.SeriesMultiIndexOps.time_op(1, 'mean')
+ 928±2μs 1.02±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_float_include('Int16')
+ 412±3μs 454±2μs 1.10 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.int64'>, 14)
+ 1.20±0.02μs 1.32±0.01μs 1.10 tslibs.normalize.Normalize.time_is_date_array_normalized(100, datetime.timezone.utc)
+ 3.16±0.08μs 3.48±0.1μs 1.10 attrs_caching.SeriesArrayAttribute.time_extract_array('object')
+ 265±2μs 292±2μs 1.10 arithmetic.NumericInferOps.time_multiply(<class 'numpy.int8'>)
+ 947±4μs 1.04±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_string_include('uint32')
+ 26.4±0.2ms 29.1±0.05ms 1.10 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 1000, 2)
+ 88.3±0.6μs 97.4±0.5μs 1.10 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('datetime', 'non_monotonic')
+ 720±4μs 794±4μs 1.10 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.int64'>, 15)
+ 259±3μs 285±2μs 1.10 arithmetic.NumericInferOps.time_add(<class 'numpy.int8'>)
+ 1.87±0.1μs 2.06±0.09μs 1.10 index_cached_properties.IndexCache.time_inferred_type('PeriodIndex')
+ 191±1μs 211±0.7μs 1.10 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'numpy.float64'>, 1300)
+ 100±2ms 110±1ms 1.10 io.json.ToJSON.time_to_json('values', 'df_date_idx')
+ 952±10μs 1.05±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_int_include('datetime64[ns]')
+ 2.46±0.01ms 2.71±0.01ms 1.10 reindex.DropDuplicates.time_frame_drop_dups_bool(True)
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+ 528±8μs 581±2μs 1.10 groupby.GroupByMethods.time_dtype_as_field('datetime', 'ffill', 'transformation')
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+ 4.33±0.01ms 4.76±0.01ms 1.10 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'skew')
+ 942±8μs 1.04±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_int_include('uint16')
+ 503±0.4ms 554±1ms 1.10 groupby.GroupByMethods.time_dtype_as_field('int', 'mad', 'direct')
+ 503±0.9ms 553±0.9ms 1.10 groupby.GroupByMethods.time_dtype_as_field('int', 'mad', 'transformation')
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+ 927±4μs 1.02±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_bool_include('Int64')
+ 20.5±0.2μs 22.5±0.2μs 1.10 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'unique_monotonic_inc')
+ 832±10μs 915±20μs 1.10 series_methods.Clip.time_clip(50)
+ 279±1ms 307±0.8ms 1.10 io.style.RenderApply.time_render(36, 120)
+ 101±0.2ms 111±1ms 1.10 groupby.GroupByMethods.time_dtype_as_group('int', 'unique', 'direct')
+ 104±0.7ms 115±0.8ms 1.10 hash_functions.IsinWithArange.time_isin(<class 'object'>, 8000, -2)
+ 171±0.9μs 188±2μs 1.10 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 100000)
+ 1.16±0.01s 1.27±0s 1.10 groupby.GroupByMethods.time_dtype_as_group('float', 'mad', 'direct')
+ 929±4μs 1.02±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_string_include('UInt8')
+ 264±0.9μs 290±1μs 1.10 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.int64'>, 13)
+ 936±9μs 1.03±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_int_include('UInt8')
+ 257±2ms 282±0.9ms 1.10 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 1000, 'random_hits')
+ 3.59±0.03ms 3.94±0.06ms 1.10 io.csv.ReadCSVFloatPrecision.time_read_csv(';', '.', 'round_trip')
+ 943±6μs 1.03±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_float_include('uint8')
+ 296±2μs 324±2μs 1.10 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.int64'>, 8000)
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+ 2.46±0.02ms 2.69±0.03ms 1.10 io.csv.ReadCSVFloatPrecision.time_read_csv(',', '_', 'high')
+ 954±10μs 1.05±0ms 1.10 dtypes.SelectDtypes.time_select_dtype_string_include('complex64')
+ 14.8±0.04μs 16.3±0.04μs 1.10 dtypes.Dtypes.time_pandas_dtype('object')
+ 936±3μs 1.03±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_int_include('UInt64')
+ 14.9±0.03μs 16.3±0.07μs 1.10 dtypes.DtypesInvalid.time_pandas_dtype_invalid('scalar-string')
+ 130±1ms 142±2ms 1.10 io.json.ToJSON.time_to_json('index', 'df')
+ 68.9±0.4ms 75.4±0.5ms 1.10 groupby.GroupByMethods.time_dtype_as_field('int', 'unique', 'transformation')
+ 138±2ms 151±2ms 1.10 io.json.ToJSON.time_to_json('index', 'df_date_idx')
+ 947±3μs 1.04±0.01ms 1.10 dtypes.SelectDtypes.time_select_dtype_float_include('M8[ns]')
+ 448±3μs 491±3μs 1.09 period.Algorithms.time_drop_duplicates('series')
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+ 201±5ms 220±0.6ms 1.09 io.stata.StataMissing.time_read_stata('td')
+ 934±10μs 1.02±0.01ms 1.09 dtypes.SelectDtypes.time_select_dtype_bool_include('Int32')
+ 108±2ms 118±2ms 1.09 io.stata.Stata.time_read_stata('tq')
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+ 1.46±0.01ms 1.60±0.01ms 1.09 dtypes.SelectDtypes.time_select_dtype_int_include('Int64')
+ 94.7±0.7ms 103±0.7ms 1.09 frame_methods.Repr.time_frame_repr_wide
+ 168±5ms 183±2ms 1.09 io.json.ToJSONLines.time_floats_with_int_idex_lines
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+ 1.49±0ms 1.62±0.02ms 1.09 frame_methods.Iteration.time_items_cached
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+ 22.0±0.05ms 23.9±0.07ms 1.09 groupby.MultiColumn.time_cython_sum
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+ 126±2μs 137±2μs 1.09 timeseries.AsOf.time_asof_single_early('DataFrame')
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+ 210±2ms 228±0.5ms 1.08 io.json.ToJSONLines.time_float_int_str_lines
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+ 699±40ns 757±30ns 1.08 index_cached_properties.IndexCache.time_inferred_type('RangeIndex')
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+ 21.9±0.1μs 23.5±0.2μs 1.07 boolean.TimeLogicalOps.time_xor_array
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+ 1.42±0.08μs 1.52±0.05μs 1.07 index_cached_properties.IndexCache.time_is_monotonic_decreasing('Int64Index')
+ 16.3±0.2ms 17.5±0.05ms 1.07 frame_methods.Repr.time_repr_tall
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+ 646±3μs 667±0.9μs 1.03 groupby.GroupByMethods.time_dtype_as_group('int', 'nunique', 'transformation')
+ 47.3±0.4ms 48.8±0.4ms 1.03 io.sql.WriteSQLDtypes.time_to_sql_dataframe_column('sqlite', 'datetime')
+ 572±6ns 590±2ns 1.03 dtypes.Dtypes.time_pandas_dtype(dtype('uint32'))
+ 714±2μs 736±2μs 1.03 groupby.GroupByMethods.time_dtype_as_field('datetime', 'nunique', 'direct')
+ 8.94±0.04ms 9.22±0.09ms 1.03 frame_ctor.FromArrays.time_frame_from_arrays_sparse
+ 34.7±0.2ms 35.8±0.07ms 1.03 sparse.ToCoo.time_sparse_series_to_coo
+ 33.5±0.1ms 34.5±0.1ms 1.03 groupby.AggEngine.time_series_cython(True)
+ 646±4μs 665±4μs 1.03 groupby.GroupByMethods.time_dtype_as_group('float', 'nunique', 'direct')
+ 7.18±0.08ms 7.40±0.1ms 1.03 ctors.SeriesConstructors.time_series_constructor(<function gen_of_tuples at 0x7f277fe8a280>, False, 'int')
+ 333±1μs 342±1μs 1.03 groupby.GroupByMethods.time_dtype_as_field('datetime', 'cumcount', 'direct')
+ 574±7ns 592±2ns 1.03 dtypes.Dtypes.time_pandas_dtype(dtype('int8'))
+ 2.55±0.01ms 2.63±0.01ms 1.03 timeseries.ResampleDataFrame.time_method('max')
+ 1.00±0.01μs 1.03±0.01μs 1.03 dtypes.Dtypes.time_pandas_dtype(<class 'pandas.core.arrays.integer.UInt8Dtype'>)
+ 1.29±0ms 1.32±0.06ms 1.03 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 1011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
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+ 67.1±0.5ms 69.1±0.3ms 1.03 gil.ParallelFactorize.time_loop(4)
+ 1.18±0.01s 1.21±0s 1.03 join_merge.MergeAsof.time_multiby('nearest', 5)
+ 762±1ms 784±1ms 1.03 join_merge.MergeCategoricals.time_merge_object
+ 625±3μs 643±2μs 1.03 groupby.GroupByMethods.time_dtype_as_field('int', 'nunique', 'transformation')
+ 268±1μs 275±2μs 1.03 groupby.GroupByMethods.time_dtype_as_group('int', 'all', 'direct')
+ 623±5ns 640±8ns 1.03 dtypes.Dtypes.time_pandas_dtype(datetime64[ns, UTC])
+ 91.1±0.3ms 93.6±0.4ms 1.03 plotting.SeriesPlotting.time_series_plot('bar')
+ 5.65±0.03ms 5.81±0.03ms 1.03 groupby.CountMultiDtype.time_multi_count
+ 1.06±0.01ms 1.09±0ms 1.03 groupby.GroupByMethods.time_dtype_as_group('object', 'value_counts', 'direct')
+ 524±4μs 538±2μs 1.03 groupby.GroupByMethods.time_dtype_as_group('float', 'bfill', 'direct')
+ 656±2μs 674±2μs 1.03 categoricals.Repr.time_rendering
+ 14.7±0.03μs 15.1±0.05μs 1.03 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(100, 8000)
+ 526±2μs 539±4μs 1.03 groupby.GroupByMethods.time_dtype_as_field('int', 'ffill', 'transformation')
+ 451±3ms 462±0.7ms 1.02 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 5000000)
+ 683±2μs 700±4μs 1.02 groupby.GroupByMethods.time_dtype_as_field('object', 'bfill', 'transformation')
+ 1.07±0s 1.09±0.01s 1.02 join_merge.MergeAsof.time_multiby('forward', 5)
+ 714±4μs 731±2μs 1.02 groupby.GroupByMethods.time_dtype_as_field('datetime', 'nunique', 'transformation')
+ 92.2±0.4ms 94.5±0.8ms 1.02 plotting.TimeseriesPlotting.time_plot_regular
+ 5.25±0.02ms 5.38±0.03ms 1.02 dtypes.InferDtypes.time_infer('bytes')
+ 33.5±0.1ms 34.3±0.1ms 1.02 groupby.AggEngine.time_series_cython(False)
+ 1.06±0s 1.09±0s 1.02 join_merge.MergeAsof.time_multiby('forward', None)
+ 830±2μs 850±2μs 1.02 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 9000)
+ 256±0.3ms 262±6ms 1.02 io.stata.StataMissing.time_write_stata('th')
+ 272±0.9μs 278±1μs 1.02 groupby.GroupByMethods.time_dtype_as_group('float', 'any', 'transformation')
+ 11.9±0.1ms 12.1±0.03ms 1.02 timedelta.ToTimedelta.time_convert_string_seconds
+ 1.21±0.01ms 1.24±0ms 1.02 index_object.SetOperations.time_operation('int', 'union')
+ 1.68±0ms 1.72±0.01ms 1.02 arithmetic.OffsetArrayArithmetic.time_add_series_offset(<MonthEnd>)
+ 529±2μs 540±2μs 1.02 groupby.GroupByMethods.time_dtype_as_group('int', 'ffill', 'direct')
+ 15.8±0.04ms 16.1±0.02ms 1.02 timeseries.SortIndex.time_sort_index(False)
+ 5.65±0.07ms 5.77±0.07ms 1.02 index_cached_properties.IndexCache.time_is_all_dates('CategoricalIndex')
+ 109±0.09ms 111±0.6ms 1.02 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 2000, datetime.timezone(datetime.timedelta(seconds=3600)))
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+ 1.38±0.01ms 1.41±0.01ms 1.02 frame_ctor.FromRecords.time_frame_from_records_generator(1000)
+ 105±0.3ms 108±0.3ms 1.02 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 1011, datetime.timezone(datetime.timedelta(seconds=3600)))
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+ 577±2μs 588±2μs 1.02 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 7000)
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+ 697±40μs 709±30μs 1.02 index_cached_properties.IndexCache.time_is_monotonic('MultiIndex')
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+ 458±3ms 466±1ms 1.02 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 5000000)
+ 530±2μs 539±3μs 1.02 groupby.GroupByMethods.time_dtype_as_group('int', 'ffill', 'transformation')
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+ 4.28±0.03ms 4.35±0.04ms 1.02 ctors.SeriesConstructors.time_series_constructor(<function list_of_tuples_with_none at 0x7f277fe8a3a0>, False, 'float')
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+ 1.09±0ms 1.11±0ms 1.02 tslibs.resolution.TimeResolution.time_get_resolution('us', 10000, datetime.timezone(datetime.timedelta(seconds=3600)))
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+ 298±0.6ms 303±0.4ms 1.02 index_object.Indexing.time_get_loc_non_unique_sorted('String')
+ 7.59±0.02ms 7.71±0.01ms 1.02 dtypes.InferDtypes.time_infer_skipna('np-object')
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- 118M 116M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '50s', 'int', 'min')
- 118M 116M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '50s', 'int', 'max')
- 117M 115M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '1h', 'float', 'mean')
- 118M 116M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '1h', 'int', 'min')
- 118M 115M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '1d', 'float', 'max')
- 118M 116M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '1d', 'int', 'max')
- 117M 115M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '50s', 'float', 'max')
- 117M 115M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '50s', 'float', 'min')
- 118M 116M 0.98 rolling.VariableWindowMethods.peakmem_rolling('Series', '1h', 'int', 'max')
- 203M 199M 0.98 io.json.ToJSON.peakmem_to_json_wide('columns', 'df_int_float_str')
- 16.4±0.1ms 16.1±0.08ms 0.98 join_merge.Concat.time_concat_small_frames(1)
- 6.43±0.03ms 6.28±0.05ms 0.98 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 8000, 0)
- 18.2±0.1ms 17.8±0.03ms 0.98 join_merge.MergeAsof.time_on_uint64('forward', 5)
- 197M 193M 0.98 io.json.ToJSON.peakmem_to_json_wide('columns', 'df_td_int_ts')
- 318M 311M 0.98 frame_methods.Iteration.peakmem_itertuples_start
- 318M 311M 0.98 frame_methods.Iteration.peakmem_itertuples
- 870±3ns 850±3ns 0.98 tslibs.timestamp.TimestampOps.time_to_pydatetime(<UTC>)
- 169±0.5ms 165±0.9ms 0.98 index_cached_properties.IndexCache.time_is_monotonic('IntervalIndex')
- 9.48±0.05ms 9.26±0.02ms 0.98 stat_ops.Correlation.time_corrwith_cols('kendall')
- 55.9±0.4ms 54.5±0.1ms 0.98 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0.5, 'nearest')
- 193M 189M 0.98 io.json.ToJSON.peakmem_to_json_wide('index', 'df_int_float_str')
- 193M 189M 0.98 io.json.ToJSON.peakmem_to_json_wide('records', 'df_int_float_str')
- 169±0.7ms 165±0.7ms 0.98 index_cached_properties.IndexCache.time_is_monotonic_increasing('IntervalIndex')
- 16.8±0.06ms 16.4±0.09ms 0.98 join_merge.MergeAsof.time_on_uint64('backward', 5)
- 187M 183M 0.98 io.json.ToJSON.peakmem_to_json_wide('records', 'df_td_int_ts')
- 187M 183M 0.98 io.json.ToJSON.peakmem_to_json_wide('index', 'df_td_int_ts')
- 140±1μs 137±1μs 0.97 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<CustomBusinessMonthEnd>)
- 193±0.5ms 188±0.4ms 0.97 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 2000)
- 434±4ns 423±0.7ns 0.97 tslibs.timestamp.TimestampProperties.time_dayofyear(tzfile('/usr/share/zoneinfo/US/Central'), 'B')
- 55.7±0.3ms 54.2±0.2ms 0.97 strings.Methods.time_match
- 181M 176M 0.97 io.json.ToJSON.peakmem_to_json_wide('split', 'df_int_float_str')
- 6.28±0.08ms 6.12±0.02ms 0.97 hash_functions.IsinWithArange.time_isin(<class 'numpy.uint64'>, 2000, 0)
- 196M 191M 0.97 io.json.ToJSON.peakmem_to_json_wide('columns', 'df_date_idx')
- 116M 113M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'int', 'median')
- 181M 176M 0.97 io.json.ToJSON.peakmem_to_json_wide('values', 'df_int_float_str')
- 188M 183M 0.97 io.json.ToJSON.peakmem_to_json_wide('index', 'df')
- 188M 183M 0.97 io.json.ToJSON.peakmem_to_json_wide('records', 'df')
- 188M 183M 0.97 io.json.ToJSON.peakmem_to_json_wide('index', 'df_date_idx')
- 188M 183M 0.97 io.json.ToJSON.peakmem_to_json_wide('records', 'df_date_idx')
- 187M 181M 0.97 io.json.ToJSON.peakmem_to_json_wide('columns', 'df')
- 175M 170M 0.97 io.json.ToJSON.peakmem_to_json_wide('split', 'df_td_int_ts')
- 175M 170M 0.97 io.json.ToJSON.peakmem_to_json_wide('values', 'df_td_int_ts')
- 22.3±0.09ms 21.7±0.1ms 0.97 join_merge.MergeAsof.time_on_uint64('nearest', None)
- 115M 112M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'float', 'median')
- 4.60±0.05μs 4.47±0.02μs 0.97 categoricals.Contains.time_categorical_index_contains
- 380±3ns 370±2ns 0.97 tslibs.timestamp.TimestampOps.time_tz_localize(tzutc())
- 194±0.9ms 188±0.1ms 0.97 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 2011)
- 6.08±0.02ms 5.89±0.03ms 0.97 tslibs.offsets.OnOffset.time_on_offset(<CustomBusinessMonthBegin>)
- 66.3±0.5ms 64.3±0.1ms 0.97 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0.5, 'midpoint')
- 15.2±0.2μs 14.8±0.2μs 0.97 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BYearBegin: month=1>)
- 178±0.8μs 172±0.6μs 0.97 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<CustomBusinessMonthBegin>)
- 177M 172M 0.97 io.json.ToJSON.peakmem_to_json_wide('split', 'df')
- 177M 172M 0.97 io.json.ToJSON.peakmem_to_json_wide('values', 'df')
- 177M 172M 0.97 io.json.ToJSON.peakmem_to_json_wide('split', 'df_date_idx')
- 1.79±0.01s 1.73±0.01s 0.97 groupby.GroupByMethods.time_dtype_as_field('float', 'describe', 'direct')
- 177M 172M 0.97 io.json.ToJSON.peakmem_to_json_wide('values', 'df_date_idx')
- 4.75±0.02ms 4.61±0.02ms 0.97 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(';', '_', 'high')
- 310±4ms 301±1ms 0.97 arithmetic.OffsetArrayArithmetic.time_add_dti_offset(<CustomBusinessDay>)
- 317±4ms 307±2ms 0.97 arithmetic.OffsetArrayArithmetic.time_add_series_offset(<CustomBusinessDay>)
- 196±2μs 189±0.9μs 0.97 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<CustomBusinessMonthBegin>)
- 5.05±0.7ms 4.89±0.03ms 0.97 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'skew')
- 20.7±0.08μs 20.0±0.06μs 0.97 tslibs.resolution.TimeResolution.time_get_resolution('h', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 115M 111M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'float', 'median')
- 3.31±0.01ms 3.20±0.02ms 0.97 arithmetic.ApplyIndex.time_apply_index(<BusinessDay>)
- 98.8±0.5ms 95.6±0.6ms 0.97 rolling.Quantile.time_quantile('Series', 1000, 'float', 0.5, 'linear')
- 56.2±0.5ms 54.4±0.1ms 0.97 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0.5, 'lower')
- 4.78±0.02ms 4.62±0.02ms 0.97 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(';', '_', None)
- 138±0.4ms 133±0.4ms 0.97 hash_functions.IsinWithArange.time_isin(<class 'object'>, 8000, 2)
- 10.2±0.2μs 9.82±0.1μs 0.97 tslibs.timestamp.TimestampProperties.time_weekday_name(datetime.timezone(datetime.timedelta(seconds=3600)), None)
- 91.6±0.4ms 88.5±0.4ms 0.97 rolling.Quantile.time_quantile('Series', 1000, 'float', 0.5, 'nearest')
- 117M 113M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'kurt')
- 116M 112M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'int', 'kurt')
- 204M 197M 0.97 io.json.ToJSON.peakmem_to_json_wide('columns', 'df_int_floats')
- 117M 113M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'median')
- 115M 111M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'int', 'max')
- 115M 111M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'int', 'min')
- 116M 112M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'int', 'mean')
- 116M 112M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'int', 'sum')
- 116M 112M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'skew')
- 116M 112M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'sum')
- 116M 112M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'int', 'median')
- 1.79±0.04s 1.73±0s 0.97 groupby.GroupByMethods.time_dtype_as_field('float', 'describe', 'transformation')
- 117M 113M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'skew')
- 372±0.7ms 359±2ms 0.97 series_methods.IsInLongSeriesValuesDominate.time_isin('int64', 'monotone')
- 115M 111M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'float', 'kurt')
- 2.01±0.01μs 1.94±0.02μs 0.97 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1, None)
- 11.1±0.5μs 10.7±0.3μs 0.97 index_cached_properties.IndexCache.time_engine('Float64Index')
- 117M 113M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'std')
- 115M 111M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'float', 'mean')
- 114M 110M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'float', 'max')
- 94.6±0.3ms 91.3±0.3ms 0.97 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'median')
- 29.2±0.1ms 28.2±0.2ms 0.97 io.csv.ToCSV.time_frame('mixed')
- 118M 114M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'median')
- 114M 110M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'float', 'min')
- 116M 112M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'kurt')
- 116M 112M 0.97 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'mean')
- 115M 111M 0.97 rolling.ForwardWindowMethods.peakmem_rolling('Series', 10, 'float', 'sum')
- 117M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'mean')
- 194M 187M 0.96 io.json.ToJSON.peakmem_to_json_wide('records', 'df_int_floats')
- 194M 187M 0.96 io.json.ToJSON.peakmem_to_json_wide('index', 'df_int_floats')
- 118M 114M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'std')
- 5.78±0.03μs 5.58±0.03μs 0.96 dtypes.InferDtypes.time_infer('np-floating')
- 11.4±0.1μs 11.0±0.08μs 0.96 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 0, datetime.timezone(datetime.timedelta(seconds=3600)))
- 4.80±0.02ms 4.63±0.01ms 0.96 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(',', '_', 'high')
- 117M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'sum')
- 72.3±0.4ms 69.7±0.5ms 0.96 io.csv.ToCSVDatetimeBig.time_frame(10000)
- 2.06±0.01s 1.99±0.01s 0.96 frame_methods.Iteration.time_itertuples_to_list
- 15.4±0.1μs 14.8±0.05μs 0.96 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<YearBegin: month=1>)
- 117M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'min')
- 43.1±0.3ms 41.5±0.3ms 0.96 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'median')
- 98.7±0.3ms 95.0±0.5ms 0.96 rolling.Quantile.time_quantile('Series', 1000, 'float', 0.5, 'midpoint')
- 161±1μs 155±1μs 0.96 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<CustomBusinessMonthBegin>)
- 117M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'max')
- 3.80±0.2μs 3.66±0.2μs 0.96 index_cached_properties.IndexCache.time_inferred_type('UInt64Index')
- 407±3ms 392±0.3ms 0.96 index_object.Indexing.time_get_loc('String')
- 129±2ms 124±0.6ms 0.96 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'median')
- 91.9±0.1ms 88.4±0.4ms 0.96 rolling.Quantile.time_quantile('Series', 1000, 'float', 0.5, 'lower')
- 2.96±0.8ms 2.85±0.02ms 0.96 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'linear')
- 44.6±0.2ms 42.9±0.5ms 0.96 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'median')
- 138M 132M 0.96 io.pickle.Pickle.peakmem_write_pickle
- 182M 175M 0.96 io.json.ToJSON.peakmem_to_json_wide('split', 'df_int_floats')
- 116M 112M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'max')
- 116M 112M 0.96 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'min')
- 182M 175M 0.96 io.json.ToJSON.peakmem_to_json_wide('values', 'df_int_floats')
- 116M 111M 0.96 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'int', 'kurt')
- 56.6±0.4ms 54.4±0.5ms 0.96 reshape.Cut.time_cut_int(1000)
- 92.2±0.3ms 88.5±0.2ms 0.96 rolling.Quantile.time_quantile('Series', 1000, 'float', 0.5, 'higher')
- 15.2±0.06μs 14.6±0.3μs 0.96 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BusinessDay>)
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'median')
- 7.48±0.04μs 7.18±0.1μs 0.96 tslibs.normalize.Normalize.time_is_date_array_normalized(0, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 179±1μs 171±1μs 0.96 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<CustomBusinessMonthBegin>)
- 9.99±0.04μs 9.58±0.09μs 0.96 tslibs.timestamp.TimestampProperties.time_month_name(<UTC>, None)
- 116±0.3μs 111±0.9μs 0.96 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<CustomBusinessMonthEnd>)
- 10.2±0.1μs 9.81±0.08μs 0.96 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 6000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 2.96±0.8ms 2.84±0.01ms 0.96 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'nearest')
- 1.61±0.01s 1.55±0.02s 0.96 frame_methods.Iteration.time_itertuples
- 186±1μs 179±1μs 0.96 stat_ops.SeriesOps.time_op('mean', 'int')
- 9.93±0.08μs 9.53±0.03μs 0.96 tslibs.timestamp.TimestampProperties.time_month_name(None, 'B')
- 10.3±0.1μs 9.86±0.08μs 0.96 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 145M 139M 0.96 io.pickle.Pickle.peakmem_read_pickle
- 117M 112M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'skew')
- 117M 112M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'sum')
- 3.70±0.2μs 3.55±0.2μs 0.96 index_cached_properties.IndexCache.time_values('UInt64Index')
- 166±0.4μs 159±0.4μs 0.96 series_methods.NanOps.time_func('median', 1000, 'Int64')
- 4.21±0.01ms 4.04±0.02ms 0.96 io.csv.ReadCSVCachedParseDates.time_read_csv_cached(True, 'python')
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'std')
- 117M 112M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'mean')
- 117M 112M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'kurt')
- 164±0.8μs 157±0.7μs 0.96 period.DataFramePeriodColumn.time_setitem_period_column
- 119M 114M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'std')
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'kurt')
- 114M 109M 0.96 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'float', 'max')
- 185±3μs 177±1μs 0.96 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<CustomBusinessMonthEnd>)
- 250±2μs 239±1μs 0.96 series_methods.NanOps.time_func('sem', 1000, 'int32')
- 115M 110M 0.96 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'int', 'min')
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'skew')
- 115M 110M 0.96 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'int', 'max')
- 114M 109M 0.96 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'float', 'min')
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'mean')
- 252±1μs 241±3μs 0.96 series_methods.NanOps.time_func('sem', 1000, 'int8')
- 119M 114M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'median')
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'sum')
- 10.3±0.08μs 9.81±0.1μs 0.96 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'min')
- 10.2±0.06μs 9.77±0.1μs 0.96 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 118M 113M 0.96 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'max')
- 10.2±0.08μs 9.76±0.2μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 73.9±0.2ms 70.6±0.3ms 0.95 index_object.SetOperations.time_operation('strings', 'intersection')
- 10.2±0.2μs 9.73±0.04μs 0.95 tslibs.timestamp.TimestampProperties.time_weekday_name(tzlocal(), None)
- 3.78±0.06μs 3.61±0.03μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, None)
- 4.95±0.04μs 4.72±0.03μs 0.95 tslibs.timedelta.TimedeltaConstructor.time_from_np_timedelta
- 10.5±0.06μs 10.0±0.09μs 0.95 tslibs.timestamp.TimestampProperties.time_month_name(tzfile('/usr/share/zoneinfo/US/Central'), 'B')
- 10.2±0.1μs 9.75±0.1μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 115M 110M 0.95 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'float', 'kurt')
- 3.49±0.02μs 3.32±0.09μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, datetime.timezone.utc)
- 91.0±0.6ms 86.8±0.4ms 0.95 replace.Convert.time_replace('Series', 'Timedelta')
- 116M 110M 0.95 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'int', 'mean')
- 443±10ns 422±2ns 0.95 tslibs.timestamp.TimestampProperties.time_dayofyear(tzfile('/usr/share/zoneinfo/US/Central'), None)
- 116M 110M 0.95 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'int', 'sum')
- 115M 109M 0.95 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'float', 'mean')
- 101±0.6ms 95.9±0.3ms 0.95 rolling.Methods.time_rolling('Series', 1000, 'float', 'median')
- 10.2±0.1μs 9.76±0.05μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 5.71±0.05ms 5.44±0.03ms 0.95 rolling.Engine.time_rolling_apply('Series', 'float', <function sum at 0x7f2790e97430>, 'cython')
- 115M 109M 0.95 rolling.ForwardWindowMethods.peakmem_rolling('Series', 1000, 'float', 'sum')
- 3.00±0.8ms 2.86±0.02ms 0.95 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 0, 'midpoint')
- 95.6±0.3ms 91.0±0.2ms 0.95 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'median')
- 3.02±0.8ms 2.87±0.03ms 0.95 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'nearest')
- 2.03±0.03μs 1.93±0.02μs 0.95 tslibs.resolution.TimeResolution.time_get_resolution('h', 1, None)
- 10.9±0.1μs 10.3±0.1μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 10.2±0.07μs 9.75±0.1μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 120M 114M 0.95 rolling.Methods.peakmem_rolling('Series', 1000, 'float', 'count')
- 117M 111M 0.95 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'max')
- 8.15±0.02ms 7.75±0.03ms 0.95 io.csv.ToCSVDatetimeBig.time_frame(1000)
- 117M 111M 0.95 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'min')
- 10.1±0.08μs 9.60±0.04μs 0.95 tslibs.timestamp.TimestampProperties.time_weekday_name(tzfile('/usr/share/zoneinfo/US/Central'), 'B')
- 16.7±0.4ms 15.9±0.8ms 0.95 stat_ops.FrameOps.time_op('std', 'float', 1)
- 15.3±0.1μs 14.5±0.3μs 0.95 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BusinessMonthBegin>)
- 11.6±0.2μs 11.0±0.1μs 0.95 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 5.69±0.04ms 5.41±0.03ms 0.95 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(',', '.', None)
- 1.59±0.01ms 1.51±0.01ms 0.95 io.parsers.ConcatDateCols.time_check_concat(1234567890, 1)
- 38.4±0.3ms 36.5±0.5ms 0.95 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'median')
- 10.7±0.04μs 10.2±0.3μs 0.95 tslibs.resolution.TimeResolution.time_get_resolution('us', 1, datetime.timezone(datetime.timedelta(seconds=3600)))
- 10.5±0.04μs 9.96±0.09μs 0.95 tslibs.timestamp.TimestampProperties.time_month_name(datetime.timezone(datetime.timedelta(seconds=3600)), 'B')
- 287±3μs 273±4μs 0.95 series_methods.NanOps.time_func('sem', 1000, 'boolean')
- 125±0.9μs 119±2μs 0.95 series_methods.NanOps.time_func('skew', 1000, 'float64')
- 8.96±0.05μs 8.50±0.2μs 0.95 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 1.69±0.02μs 1.61±0.01μs 0.95 attrs_caching.SeriesArrayAttribute.time_array('datetime64')
- 4.32±0.01ms 4.10±0.06ms 0.95 rolling.Apply.time_rolling('Series', 300, 'int', <function sum at 0x7f2790e97430>, True)
- 2.43±0.01ms 2.31±0.02ms 0.95 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'mean')
- 3.03±0.8ms 2.88±0.01ms 0.95 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'lower')
- 11.0±0.05μs 10.4±0.1μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 69.6±0.1ms 66.0±0.3ms 0.95 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'median')
- 5.73±0.07ms 5.44±0.04ms 0.95 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(';', '.', None)
- 5.73±0.04ms 5.44±0.03ms 0.95 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(',', '.', 'high')
- 10.3±0.1μs 9.77±0.1μs 0.95 tslibs.normalize.Normalize.time_normalize_i8_timestamps(1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 33.2±0.2μs 31.4±0.2μs 0.95 indexing.NumericSeriesIndexing.time_loc_scalar(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
- 10.8±0.1μs 10.2±0.06μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 5.73±0.04ms 5.43±0.02ms 0.95 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(';', '.', 'high')
- 8.19±0.04μs 7.76±0.07μs 0.95 series_methods.SearchSorted.time_searchsorted('float64')
- 2.60±0.02ms 2.46±0.1ms 0.95 rolling.Apply.time_rolling('Series', 3, 'float', <built-in function sum>, True)
- 95.1±0.7μs 90.0±0.6μs 0.95 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
- 44.0±0.3ms 41.7±0.2ms 0.95 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0.5, 'linear')
- 736±9ms 697±4ms 0.95 io.csv.ToCSVDatetimeBig.time_frame(100000)
- 15.2±0.3μs 14.4±0.3μs 0.95 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessMonthEnd>)
- 120M 114M 0.95 rolling.Methods.peakmem_rolling('Series', 1000, 'int', 'count')
- 99.3±0.3ms 94.0±0.6ms 0.95 rolling.Methods.time_rolling('Series', 1000, 'int', 'median')
- 119±2μs 112±0.5μs 0.95 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<CustomBusinessMonthEnd>)
- 10.3±0.09μs 9.72±0.1μs 0.95 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 2.03±0.02μs 1.92±0.02μs 0.95 tslibs.resolution.TimeResolution.time_get_resolution('m', 1, None)
- 9.54±0.09μs 9.02±0.1μs 0.95 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 138±0.8μs 131±0.6μs 0.95 stat_ops.SeriesOps.time_op('sum', 'int')
- 9.73±0.2μs 9.20±0.2μs 0.95 tslibs.timestamp.TimestampProperties.time_weekday_name(<UTC>, None)
- 187±0.5μs 177±1μs 0.95 series_methods.NanOps.time_func('median', 1000, 'float64')
- 3.03±0.8ms 2.86±0.02ms 0.94 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'midpoint')
- 10.2±0.07μs 9.63±0.07μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 2.04±0.02μs 1.93±0.02μs 0.94 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, None)
- 9.69±0.1μs 9.15±0.05μs 0.94 tslibs.timestamp.TimestampProperties.time_weekday_name(<UTC>, 'B')
- 3.02±0.8ms 2.86±0.02ms 0.94 rolling.Quantile.time_quantile('DataFrame', 1000, 'int', 1, 'higher')
- 43.4±0.6ms 41.0±0.3ms 0.94 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'median')
- 121M 114M 0.94 rolling.Methods.peakmem_rolling('Series', 10, 'float', 'count')
- 10.9±0.06μs 10.3±0.09μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 5.05±0.7ms 4.77±0.02ms 0.94 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'skew')
- 37.9±0.3ms 35.7±0.3ms 0.94 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0.5, 'linear')
- 15.5±0.2μs 14.6±0.3μs 0.94 tslibs.offsets.OffestDatetimeArithmetic.time_add(<MonthEnd>)
- 15.1±0.2μs 14.2±0.1μs 0.94 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<MonthBegin>)
- 40.8±0.4ms 38.5±0.3ms 0.94 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0.5, 'nearest')
- 10.3±0.04μs 9.68±0.2μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 10.9±0.08μs 10.3±0.05μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 121M 114M 0.94 rolling.Methods.peakmem_rolling('Series', 10, 'int', 'count')
- 10.2±0.06μs 9.62±0.07μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 6.10±0.03ms 5.74±0.03ms 0.94 rolling.Engine.time_expanding_apply('Series', 'int', <function sum at 0x7f2790e97430>, 'cython')
- 9.64±0.06μs 9.08±0.2μs 0.94 tslibs.timestamp.TimestampProperties.time_weekday_name(None, None)
- 6.74±0.06ms 6.35±0.03ms 0.94 rolling.Engine.time_rolling_apply('Series', 'float', <function Engine.<lambda> at 0x7f277d8de310>, 'cython')
- 44.3±0.4ms 41.7±0.2ms 0.94 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0.5, 'midpoint')
- 5.76±0.1ms 5.42±0.02ms 0.94 io.csv.ReadCSVFloatPrecision.time_read_csv_python_engine(',', '.', 'round_trip')
- 3.26±0.02ms 3.07±0.02ms 0.94 io.csv.ReadCSVParseDates.time_multiple_date('python')
- 6.10±0.04ms 5.74±0.06ms 0.94 rolling.Engine.time_expanding_apply('Series', 'float', <function sum at 0x7f2790e97430>, 'cython')
- 38.0±0.4ms 35.8±1ms 0.94 stat_ops.FrameOps.time_op('median', 'float', 1)
- 21.1±0.3μs 19.9±0.3μs 0.94 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc')
- 5.10±0.06ms 4.80±0.09ms 0.94 ctors.SeriesConstructors.time_series_constructor(<function gen_of_str at 0x7f277fe8a310>, False, 'int')
- 117±0.9μs 110±1μs 0.94 series_methods.NanOps.time_func('var', 1000, 'float64')
- 1.84±0.05ms 1.73±0.01ms 0.94 reshape.Explode.time_explode(1000, 3)
- 3.86±0.02ms 3.63±0.03ms 0.94 index_cached_properties.IndexCache.time_is_unique('DatetimeIndex')
- 3.15±0.04μs 2.96±0.03μs 0.94 tslibs.timestamp.TimestampConstruction.time_parse_now
- 71.3±1ms 67.0±1ms 0.94 io.csv.ReadCSVCategorical.time_convert_post('c')
- 41.0±0.4ms 38.4±0.2ms 0.94 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0.5, 'lower')
- 1.36±0.02ms 1.28±0.01ms 0.94 arithmetic.NumericInferOps.time_divide(<class 'numpy.uint8'>)
- 110±0.6μs 103±0.9μs 0.94 indexing.NumericSeriesIndexing.time_loc_scalar(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc')
- 10.9±0.03μs 10.2±0.09μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 9.91±0.1μs 9.29±0.1μs 0.94 tslibs.timestamp.TimestampProperties.time_weekday_name(tzutc(), 'B')
- 9.88±0.1μs 9.26±0.2μs 0.94 tslibs.timestamp.TimestampProperties.time_weekday_name(tzutc(), None)
- 3.85±0.06μs 3.61±0.01μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, None)
- 2.57±0.04ms 2.41±0.1ms 0.94 rolling.Apply.time_rolling('Series', 3, 'int', <built-in function sum>, True)
- 11.0±0.05μs 10.3±0.2μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 41.6±0.5ms 38.9±0.3ms 0.94 rolling.Quantile.time_quantile('DataFrame', 10, 'float', 0.5, 'higher')
- 143±0.7ms 134±0.2ms 0.94 rolling.Apply.time_rolling('Series', 3, 'float', <function sum at 0x7f2790e97430>, False)
- 10.4±0.2μs 9.69±0.03μs 0.94 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 10.3±0.1μs 9.61±0.2μs 0.93 tslibs.timestamp.TimestampProperties.time_weekday_name(datetime.timezone(datetime.timedelta(seconds=3600)), 'B')
- 10.8±0.2μs 10.1±0.2μs 0.93 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 16.5±0.4ms 15.4±0.1ms 0.93 reshape.PivotTable.time_pivot_table_categorical
- 143±0.8ms 134±0.7ms 0.93 rolling.Apply.time_rolling('Series', 3, 'int', <function sum at 0x7f2790e97430>, False)
- 1.37±0.01ms 1.28±0.02ms 0.93 arithmetic.NumericInferOps.time_divide(<class 'numpy.int8'>)
- 146±0.6ms 136±1ms 0.93 rolling.Apply.time_rolling('DataFrame', 3, 'float', <function Apply.<lambda> at 0x7f277d8de160>, False)
- 146±0.8ms 136±0.9ms 0.93 rolling.Apply.time_rolling('DataFrame', 3, 'int', <function Apply.<lambda> at 0x7f277d8de160>, False)
- 145±0.3ms 135±1ms 0.93 rolling.Apply.time_rolling('Series', 3, 'int', <function Apply.<lambda> at 0x7f277d8de160>, False)
- 1.62±0.01ms 1.51±0.01ms 0.93 series_methods.ValueCounts.time_value_counts('int')
- 10.8±0.1μs 10.1±0.2μs 0.93 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, datetime.timezone(datetime.timedelta(seconds=3600)))
- 37.9±0.6ms 35.4±0.2ms 0.93 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0.5, 'midpoint')
- 184±3ms 172±1ms 0.93 io.json.ToJSON.time_to_json('index', 'df_int_floats')
- 1.81±0.01ms 1.69±0.03ms 0.93 frame_methods.GetDtypeCounts.time_frame_get_dtype_counts
- 9.19±0.2μs 8.57±0.09μs 0.93 tslibs.normalize.Normalize.time_is_date_array_normalized(1, datetime.timezone(datetime.timedelta(seconds=3600)))
- 29.2±0.3μs 27.2±0.3μs 0.93 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<CustomBusinessDay>)
- 44.3±0.1ms 41.3±0.2ms 0.93 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'median')
- 10.9±0.2μs 10.2±0.09μs 0.93 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 6000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 150±0.8ms 140±1ms 0.93 groupby.TransformEngine.time_dataframe_cython(True)
- 21.5±0.3μs 20.1±0.6μs 0.93 series_methods.SearchSorted.time_searchsorted('uint16')
- 16.4±0.1ms 15.2±0.3ms 0.93 reshape.Explode.time_explode(10000, 3)
- 9.54±0.05μs 8.89±0.1μs 0.93 tslibs.resolution.TimeResolution.time_get_resolution('D', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 10.1±0.07μs 9.41±0.2μs 0.93 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 11.0±0.09μs 10.2±0.2μs 0.93 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 9.04±0.09μs 8.41±0.1μs 0.93 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 7.06±0.2ms 6.56±0.03ms 0.93 stat_ops.FrameOps.time_op('median', 'Int64', 0)
- 8.97±0.07μs 8.34±0.2μs 0.93 tslibs.resolution.TimeResolution.time_get_resolution('us', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 3.15±0.02μs 2.93±0.08μs 0.93 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(100, datetime.timezone.utc)
- 5.34±0.05ms 4.96±0.08ms 0.93 ctors.SeriesConstructors.time_series_constructor(<function gen_of_str at 0x7f277fe8a310>, False, 'float')
- 103±1ms 96.0±0.5ms 0.93 rolling.Apply.time_rolling('Series', 300, 'int', <function Apply.<lambda> at 0x7f277d8de160>, False)
- 35.4±0.2ms 32.9±0.2ms 0.93 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0.5, 'higher')
- 9.97±0.1ms 9.25±0.04ms 0.93 series_methods.NanOps.time_func('std', 1000000, 'Int64')
- 4.19±0.6ms 3.88±0.02ms 0.93 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'min')
- 11.0±0.09μs 10.2±0.2μs 0.93 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 21.4±0.2μs 19.8±0.4μs 0.93 series_methods.SearchSorted.time_searchsorted('uint8')
- 10.4±0.1μs 9.67±0.1μs 0.93 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 58.3±0.2ms 54.0±0.3ms 0.93 rolling.Quantile.time_quantile('Series', 1000, 'int', 0.5, 'higher')
- 2.24±0.01ms 2.08±0.01ms 0.93 series_methods.NSort.time_nlargest('last')
- 11.0±0.2μs 10.2±0.1μs 0.93 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 349±3μs 323±2μs 0.93 join_merge.Concat.time_concat_empty_left(0)
- 6.83±0.06ms 6.32±0.05ms 0.93 rolling.Apply.time_rolling('Series', 3, 'float', <function Apply.<lambda> at 0x7f277d8de160>, True)
- 1.62±0.01ms 1.50±0.01ms 0.93 series_methods.NSort.time_nsmallest('last')
- 10.6±0.1μs 9.78±0.1μs 0.93 tslibs.timestamp.TimestampOps.time_tz_convert(tzfile('/usr/share/zoneinfo/US/Central'))
- 105±0.5ms 96.7±1ms 0.93 rolling.Apply.time_rolling('DataFrame', 300, 'float', <function Apply.<lambda> at 0x7f277d8de160>, False)
- 143±0.3ms 133±1ms 0.92 rolling.Apply.time_rolling('DataFrame', 3, 'int', <function sum at 0x7f2790e97430>, False)
- 25.4±0.09ms 23.4±0.1ms 0.92 io.csv.ReadCSVSkipRows.time_skipprows(None, 'c')
- 10.4±0.1μs 9.60±0.2μs 0.92 index_object.Indexing.time_get_loc_sorted('Float')
- 10.5±0.3μs 9.72±0.1μs 0.92 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 4.39±0.2ms 4.06±0.03ms 0.92 index_cached_properties.IndexCache.time_is_unique('IntervalIndex')
- 68.5±0.3ms 63.3±0.4ms 0.92 rolling.Quantile.time_quantile('Series', 1000, 'int', 0.5, 'linear')
- 150±0.8ms 138±1ms 0.92 groupby.TransformEngine.time_dataframe_cython(False)
- 50.2±0.4μs 46.3±0.5μs 0.92 array.IntegerArray.time_from_integer_array
- 103±0.6ms 95.1±1ms 0.92 rolling.Apply.time_rolling('DataFrame', 300, 'int', <function sum at 0x7f2790e97430>, False)
- 68.8±0.5ms 63.4±0.3ms 0.92 rolling.Quantile.time_quantile('Series', 1000, 'int', 0.5, 'midpoint')
- 97.8±0.8μs 90.2±1μs 0.92 series_methods.Any.time_any(1000000, 'slow', 'bool')
- 58.4±0.2ms 53.8±0.3ms 0.92 rolling.Quantile.time_quantile('Series', 1000, 'int', 0.5, 'nearest')
- 6.63±0.1μs 6.11±0.1μs 0.92 tslibs.timedelta.TimedeltaConstructor.time_from_datetime_timedelta
- 10.5±0.07μs 9.70±0.1μs 0.92 index_object.Indexing.time_get_loc('Float')
- 757±5μs 697±3μs 0.92 io.parsers.ConcatDateCols.time_check_concat('AAAA', 1)
- 15.4±0.4μs 14.2±0.1μs 0.92 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessMonthBegin>)
- 44.3±0.5ms 40.7±0.2ms 0.92 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'median')
- 168±0.9ms 155±2ms 0.92 io.json.ToJSON.time_to_json_wide('columns', 'df_date_idx')
- 58.4±0.2ms 53.7±0.2ms 0.92 rolling.Quantile.time_quantile('Series', 1000, 'int', 0.5, 'lower')
- 49.7±2ms 45.6±1ms 0.92 stat_ops.FrameOps.time_op('mean', 'Int64', 1)
- 144±0.7ms 132±0.5ms 0.92 rolling.Apply.time_rolling('DataFrame', 3, 'float', <function sum at 0x7f2790e97430>, False)
- 9.29±0.1μs 8.52±0.05μs 0.92 tslibs.normalize.Normalize.time_is_date_array_normalized(0, datetime.timezone(datetime.timedelta(seconds=3600)))
- 56.0±0.1ms 51.3±0.4ms 0.92 frame_methods.Dropna.time_dropna_axis_mixed_dtypes('all', 1)
- 1.96±0.02μs 1.80±0.01μs 0.92 timedelta.TimedeltaIndexing.time_shallow_copy
- 3.13±0.01ms 2.86±0.04ms 0.92 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'mean')
- 3.11±0.05μs 2.85±0.1μs 0.91 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1, datetime.timezone.utc)
- 21.0±0.3ms 19.2±0.3ms 0.91 timeseries.Iteration.time_iter_preexit(<function period_range at 0x7f2782af4700>)
- 10.9±0.2μs 9.96±0.2μs 0.91 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 170±0.5μs 155±0.9μs 0.91 period.Algorithms.time_drop_duplicates('index')
- 44.3±0.4ms 40.4±0.3ms 0.91 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'median')
- 106±0.8ms 96.2±0.4ms 0.91 rolling.Apply.time_rolling('DataFrame', 300, 'int', <function Apply.<lambda> at 0x7f277d8de160>, False)
- 353±2μs 321±0.9μs 0.91 join_merge.Concat.time_concat_empty_right(0)
- 1.92±0.01ms 1.75±0.02ms 0.91 series_methods.NSort.time_nsmallest('first')
- 20.5±0.06ms 18.7±0.07ms 0.91 groupby.MultiColumn.time_col_select_numpy_sum
- 202±4ms 183±3ms 0.91 io.json.ToJSON.time_to_json_wide('records', 'df_int_floats')
- 90.2±0.3ms 82.0±0.1ms 0.91 hash_functions.IsinWithArange.time_isin(<class 'object'>, 1000, 2)
- 22.0±0.2ms 19.9±0.1ms 0.91 rolling.Pairwise.time_pairwise(10, 'corr', True)
- 58.2±0.5μs 52.8±0.7μs 0.91 series_methods.NanOps.time_func('prod', 1000, 'float64')
- 2.98±0.01ms 2.71±0.02ms 0.91 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'mean')
- 57.5±0.08μs 52.1±0.6μs 0.91 array.BooleanArray.time_from_integer_array
- 15.2±0.2ms 13.8±0.1ms 0.91 frame_methods.Apply.time_apply_lambda_mean
- 45.9±0.4ms 41.6±0.3ms 0.91 rolling.Quantile.time_quantile('Series', 10, 'float', 0.5, 'linear')
- 45.1±0.2ms 40.8±0.3ms 0.91 rolling.Methods.time_rolling('Series', 10, 'float', 'median')
- 4.28±0.6ms 3.87±0.02ms 0.90 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'max')
- 52.6±0.1ms 47.6±0.1ms 0.90 strings.Methods.time_title
- 7.28±0.1ms 6.59±0.1ms 0.90 rolling.Apply.time_rolling('DataFrame', 3, 'float', <function Apply.<lambda> at 0x7f277d8de160>, True)
- 45.5±0.3ms 41.1±0.5ms 0.90 rolling.Methods.time_rolling('Series', 10, 'int', 'median')
- 2.17±0.01ms 1.96±0ms 0.90 series_methods.NSort.time_nlargest('first')
- 7.21±0.1ms 6.51±0.07ms 0.90 rolling.Engine.time_rolling_apply('DataFrame', 'float', <function Engine.<lambda> at 0x7f277d8de310>, 'cython')
- 16.7±0.2ms 15.1±0.2ms 0.90 frame_methods.Apply.time_apply_np_mean
- 151±2ms 137±3ms 0.90 io.json.ToJSON.time_to_json_wide('values', 'df')
- 3.00±0.02ms 2.71±0.01ms 0.90 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'mean')
- 387±0.7μs 349±2μs 0.90 timedelta.TimedeltaIndexing.time_intersection
- 3.03±0.08ms 2.74±0.03ms 0.90 arithmetic.FrameWithFrameWide.time_op_different_blocks(<built-in function add>)
- 7.56±0.06ms 6.82±0.03ms 0.90 rolling.Engine.time_expanding_apply('DataFrame', 'int', <function Engine.<lambda> at 0x7f277d8de310>, 'cython')
- 37.6±0.06ms 33.9±0.3ms 0.90 strings.Methods.time_lower
- 6.62±0.05ms 5.96±0.05ms 0.90 rolling.Engine.time_expanding_apply('DataFrame', 'float', <function sum at 0x7f2790e97430>, 'cython')
- 1.81±0.02ms 1.63±0.01ms 0.90 rolling.Engine.time_expanding_apply('Series', 'float', <function Engine.<lambda> at 0x7f277d8de310>, 'numba')
- 49.6±0.5ms 44.6±0.2ms 0.90 rolling.GroupbyLargeGroups.time_rolling_multiindex_creation
- 43.2±0.07ms 38.8±0.3ms 0.90 rolling.Quantile.time_quantile('Series', 10, 'float', 0.5, 'higher')
- 1.97±0.01s 1.77±0s 0.90 timeseries.Iteration.time_iter(<function period_range at 0x7f2782af4700>)
- 218±10μs 196±1μs 0.90 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>)
- 42.6±0.2ms 38.3±0.3ms 0.90 rolling.Quantile.time_quantile('Series', 10, 'float', 0.5, 'nearest')
- 6.59±0.04ms 5.91±0.05ms 0.90 rolling.Engine.time_expanding_apply('DataFrame', 'int', <function sum at 0x7f2790e97430>, 'cython')
- 6.24±0.05ms 5.59±0.03ms 0.90 rolling.Engine.time_rolling_apply('DataFrame', 'float', <function sum at 0x7f2790e97430>, 'cython')
- 46.2±0.05ms 41.4±0.3ms 0.90 rolling.Quantile.time_quantile('Series', 10, 'float', 0.5, 'midpoint')
- 7.60±0.07ms 6.80±0.03ms 0.90 rolling.Engine.time_expanding_apply('DataFrame', 'float', <function Engine.<lambda> at 0x7f277d8de310>, 'cython')
- 2.82±0.01ms 2.52±0.01ms 0.89 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'sum')
- 42.7±0.1ms 38.1±0.3ms 0.89 rolling.Quantile.time_quantile('Series', 10, 'float', 0.5, 'lower')
- 6.24±0.1ms 5.57±0.05ms 0.89 rolling.Apply.time_rolling('DataFrame', 3, 'float', <function sum at 0x7f2790e97430>, True)
- 11.3±0.4μs 10.1±0.2μs 0.89 timeseries.TzLocalize.time_infer_dst('UTC')
- 7.69±0.08ms 6.84±0.02ms 0.89 rolling.Pairwise.time_pairwise(10, 'corr', False)
- 7.66±0.04ms 6.81±0.03ms 0.89 rolling.Pairwise.time_pairwise(1000, 'corr', False)
- 154±0.7μs 137±0.8μs 0.89 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo'))
- 2.69±0.01ms 2.39±0.01ms 0.89 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'sum')
- 2.68±0.02ms 2.38±0.01ms 0.89 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'sum')
- 25.3±0.2ms 22.5±0.2ms 0.89 frame_methods.ToNumpy.time_to_numpy_mixed_tall
- 14.7±0.07ms 13.1±0.2ms 0.89 groupby.Categories.time_groupby_nosort
- 204±5ms 181±4ms 0.89 io.json.ToJSON.time_to_json_wide('index', 'df_int_floats')
- 177±3ms 157±1ms 0.89 io.csv.ToCSV.time_frame('wide')
- 39.7±0.2ms 35.2±0.4ms 0.89 rolling.Quantile.time_quantile('Series', 10, 'int', 0.5, 'linear')
- 3.29±0.01ms 2.91±0.05ms 0.89 rolling.EWMMethods.time_ewm('DataFrame', 1000, 'float', 'std')
- 1.83±0.05ms 1.62±0.04ms 0.89 rolling.Engine.time_expanding_apply('Series', 'float', <function sum at 0x7f2790e97430>, 'numba')
- 22.1±0.09ms 19.6±0.06ms 0.89 rolling.Pairwise.time_pairwise(None, 'corr', True)
- 39.8±0.3ms 35.2±0.2ms 0.88 rolling.Quantile.time_quantile('Series', 10, 'int', 0.5, 'midpoint')
- 79.3±0.8μs 70.2±0.4μs 0.88 series_methods.NanOps.time_func('mean', 1000, 'int64')
- 227±2ms 201±4ms 0.88 io.json.ToJSON.time_to_json_wide('index', 'df_int_float_str')
- 7.33±0.08ms 6.48±0.03ms 0.88 rolling.Engine.time_rolling_apply('DataFrame', 'int', <function Engine.<lambda> at 0x7f277d8de310>, 'cython')
- 4.86±0.01ms 4.29±0.04ms 0.88 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'min')
- 525±6μs 464±10μs 0.88 join_merge.Append.time_append_homogenous
- 170±1ms 150±1ms 0.88 io.json.ToJSON.time_to_json_wide('columns', 'df')
- 3.71±0.01ms 3.27±0.01ms 0.88 series_methods.NanOps.time_func('mean', 1000000, 'boolean')
- 181±3ms 160±2ms 0.88 io.json.ToJSON.time_to_json_wide('split', 'df_int_floats')
- 19.5±0.07ms 17.2±0.1ms 0.88 rolling.Pairwise.time_pairwise(None, 'cov', True)
- 125±0.3ms 111±0.2ms 0.88 gil.ParallelKth.time_kth_smallest
- 24.1±0.4ms 21.2±0.2ms 0.88 categoricals.Indexing.time_reindex
- 1.85±0.01ms 1.63±0.03ms 0.88 rolling.Engine.time_expanding_apply('Series', 'int', <function sum at 0x7f2790e97430>, 'numba')
- 79.3±0.9μs 69.8±0.7μs 0.88 series_methods.NanOps.time_func('mean', 1000, 'int32')
- 7.38±0.1ms 6.49±0.04ms 0.88 rolling.Apply.time_rolling('DataFrame', 3, 'int', <function Apply.<lambda> at 0x7f277d8de160>, True)
- 972±3μs 855±4μs 0.88 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 14)
- 4.77±0.05ms 4.20±0.05ms 0.88 rolling.Apply.time_rolling('DataFrame', 300, 'float', <function sum at 0x7f2790e97430>, True)
- 182±2ms 160±3ms 0.88 io.json.ToJSON.time_to_json_wide('values', 'df_int_floats')
- 36.7±0.4ms 32.2±0.2ms 0.88 rolling.Quantile.time_quantile('Series', 10, 'int', 0.5, 'nearest')
- 36.6±0.3ms 32.2±0.2ms 0.88 rolling.Quantile.time_quantile('Series', 10, 'int', 0.5, 'lower')
- 78.9±0.5μs 69.2±0.6μs 0.88 series_methods.NanOps.time_func('mean', 1000, 'int8')
- 556±3μs 487±3μs 0.88 join_merge.Concat.time_concat_mixed_ndims(0)
- 4.94±0.01ms 4.33±0.02ms 0.88 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'min')
- 37.0±0.2ms 32.4±0.2ms 0.88 rolling.Quantile.time_quantile('Series', 10, 'int', 0.5, 'higher')
- 120±0.6ms 105±0.1ms 0.88 replace.Convert.time_replace('DataFrame', 'Timedelta')
- 120±1ms 105±0.7ms 0.87 replace.Convert.time_replace('DataFrame', 'Timestamp')
- 5.50±0.05ms 4.81±0.02ms 0.87 rolling.Apply.time_rolling('DataFrame', 300, 'float', <function Apply.<lambda> at 0x7f277d8de160>, True)
- 19.6±0.06ms 17.1±0.1ms 0.87 rolling.Pairwise.time_pairwise(1000, 'cov', True)
- 66.5±0.2μs 58.1±0.6μs 0.87 series_methods.NanOps.time_func('min', 1000, 'int32')
- 6.29±0.1ms 5.48±0.04ms 0.87 rolling.Engine.time_rolling_apply('DataFrame', 'int', <function sum at 0x7f2790e97430>, 'cython')
- 230±6ms 200±3ms 0.87 io.json.ToJSON.time_to_json_wide('records', 'df_int_float_str')
- 208±4ms 181±2ms 0.87 io.json.ToJSON.time_to_json_wide('values', 'df_int_float_str')
- 113±0.7ms 97.9±1ms 0.87 index_object.IndexAppend.time_append_obj_list
- 5.03±0.01ms 4.36±0.01ms 0.87 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'max')
- 815±1ms 706±3ms 0.87 hash_functions.NumericSeriesIndexingShuffled.time_loc_slice(<class 'pandas.core.indexes.numeric.Float64Index'>, 5000000)
- 5.53±0.06ms 4.78±0.02ms 0.87 rolling.Apply.time_rolling('DataFrame', 300, 'int', <function Apply.<lambda> at 0x7f277d8de160>, True)
- 573±8μs 495±3μs 0.86 period.Indexing.time_intersection
- 5.49±0.04ms 4.75±0.03ms 0.86 stat_ops.FrameOps.time_op('std', 'Int64', 0)
- 4.81±0.07ms 4.15±0.04ms 0.86 rolling.Apply.time_rolling('DataFrame', 300, 'int', <function sum at 0x7f2790e97430>, True)
- 210±0.5ms 181±5ms 0.86 io.json.ToJSON.time_to_json_wide('columns', 'df_int_floats')
- 26.3±0.08ms 22.7±0.05ms 0.86 join_merge.Concat.time_concat_series(0)
- 66.6±0.4μs 57.3±0.4μs 0.86 series_methods.NanOps.time_func('min', 1000, 'int64')
- 5.98±0.7ms 5.14±0.03ms 0.86 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'kurt')
- 66.8±0.1μs 57.5±0.6μs 0.86 series_methods.NanOps.time_func('min', 1000, 'int8')
- 3.09±0.2ms 2.65±0.01ms 0.86 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'std')
- 5.03±0.02ms 4.31±0.03ms 0.86 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'max')
- 68.0±0.7μs 58.1±0.2μs 0.85 replace.ReplaceList.time_replace_list(True)
- 55.4±0.5μs 47.3±0.3μs 0.85 series_methods.NanOps.time_func('sum', 1000, 'int64')
- 10.6±0.2μs 9.05±0.04μs 0.85 timeseries.TzLocalize.time_infer_dst(tzutc())
- 38.1±0.5ms 32.5±0.1ms 0.85 frame_methods.Dropna.time_dropna_axis_mixed_dtypes('any', 1)
- 188±6ms 160±5ms 0.85 indexing.CategoricalIndexIndexing.time_get_indexer_list('monotonic_incr')
- 6.01±0.7ms 5.12±0.04ms 0.85 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'kurt')
- 3.50±0.02ms 2.98±0.02ms 0.85 series_methods.IsIn.time_isin('object')
- 2.61±0.02ms 2.22±0.02ms 0.85 stat_ops.FrameOps.time_op('mean', 'Int64', 0)
- 734±30μs 623±4μs 0.85 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'non_monotonic')
- 6.20±0.06ms 5.26±0.03ms 0.85 gil.ParallelRolling.time_rolling('std')
- 5.57±0.04ms 4.71±0.01ms 0.85 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'min')
- 5.62±0.02ms 4.75±0.02ms 0.85 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'min')
- 218±0.4ms 184±2ms 0.84 io.json.ToJSON.time_to_json_wide('records', 'df_td_int_ts')
- 5.57±0.01ms 4.70±0.02ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'min')
- 204±2ms 172±4ms 0.84 io.json.ToJSON.time_to_json_wide('columns', 'df_td_int_ts')
- 218±1ms 183±2ms 0.84 io.json.ToJSON.time_to_json_wide('index', 'df_td_int_ts')
- 5.89±0.7ms 4.96±0ms 0.84 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'kurt')
- 3.74±0.05ms 3.15±0.02ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'mean')
- 187±1ms 157±1ms 0.84 io.json.ToJSON.time_to_json_wide('values', 'df_td_int_ts')
- 5.76±0.09ms 4.84±0.01ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'min')
- 210±2ms 177±0.8ms 0.84 io.json.ToJSON.time_to_json_wide('split', 'df_int_float_str')
- 5.67±0.09ms 4.76±0.01ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'min')
- 5.82±0.05ms 4.89±0.01ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'max')
- 5.47±0.02ms 4.60±0.01ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'min')
- 3.70±0.03ms 3.10±0.01ms 0.84 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'mean')
- 227±2ms 190±4ms 0.84 io.json.ToJSON.time_to_json_wide('columns', 'df_int_float_str')
- 22.3±0.08ms 18.6±0.07ms 0.84 join_merge.Merge.time_merge_dataframe_integer_2key(True)
- 3.95±0.02ms 3.29±0.02ms 0.83 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 16)
- 6.32±0.7ms 5.26±0.03ms 0.83 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'kurt')
- 750±60μs 625±6μs 0.83 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'unique_monotonic_inc')
- 5.73±0.06ms 4.78±0.02ms 0.83 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'max')
- 188±3ms 157±1ms 0.83 io.json.ToJSON.time_to_json_wide('split', 'df_td_int_ts')
- 3.66±0.01ms 3.05±0.01ms 0.83 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'mean')
- 144±1μs 120±1μs 0.83 series_methods.NanOps.time_func('std', 1000, 'int32')
- 21.4±0.04ms 17.8±0.06ms 0.83 stat_ops.Correlation.time_corr_wide_nans('pearson')
- 3.35±0.02ms 2.78±0.01ms 0.83 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'sum')
- 145±0.9μs 119±1μs 0.83 series_methods.NanOps.time_func('std', 1000, 'int8')
- 5.74±0.03ms 4.74±0.06ms 0.83 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'min')
- 7.73±0.07ms 6.39±0.05ms 0.83 gil.ParallelRolling.time_rolling('kurt')
- 3.38±0.02ms 2.79±0.01ms 0.82 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'sum')
- 194±7ms 160±5ms 0.82 indexing.CategoricalIndexIndexing.time_get_indexer_list('monotonic_decr')
- 146±1μs 121±1μs 0.82 series_methods.NanOps.time_func('std', 1000, 'int64')
- 95.4±1μs 78.4±1μs 0.82 series_methods.NanOps.time_func('mean', 1000, 'boolean')
- 1.96±0.04ms 1.61±0.02ms 0.82 arithmetic.FrameWithFrameWide.time_op_same_blocks(<built-in function add>)
- 82.9±1μs 68.1±0.6μs 0.82 series_methods.NanOps.time_func('mean', 1000, 'Int64')
- 5.77±0.03ms 4.74±0.01ms 0.82 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'max')
- 58.8±0.5μs 48.3±0.6μs 0.82 series_methods.NanOps.time_func('sum', 1000, 'int8')
- 3.41±0.01ms 2.79±0.02ms 0.82 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'sum')
- 5.74±0.03ms 4.70±0.01ms 0.82 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'max')
- 5.71±0.01ms 4.66±0ms 0.82 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'max')
- 6.73±0.08ms 5.48±0.06ms 0.82 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f277fe8a160>, True, 'int')
- 7.95±0.05ms 6.48±0.03ms 0.82 rolling.Pairwise.time_pairwise(None, 'corr', False)
- 5.79±0.03ms 4.72±0.01ms 0.82 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'max')
- 6.54±0.07ms 5.32±0.07ms 0.81 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f277fe8a160>, False, 'int')
- 5.27±0.02ms 4.29±0.03ms 0.81 rolling.Pairwise.time_pairwise(10, 'cov', False)
- 48.9±3μs 39.7±0.7μs 0.81 series_methods.Any.time_any(1000000, 'fast', 'bool')
- 68.5±0.6ms 55.6±0.4ms 0.81 groupby.TransformEngine.time_series_cython(False)
- 192±4ms 156±6ms 0.81 indexing.CategoricalIndexIndexing.time_get_indexer_list('non_monotonic')
- 6.27±0.8ms 5.09±0.03ms 0.81 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'kurt')
- 68.7±0.6ms 55.7±0.4ms 0.81 groupby.TransformEngine.time_series_cython(True)
- 5.32±0.08ms 4.31±0.08ms 0.81 rolling.Pairwise.time_pairwise(1000, 'cov', False)
- 3.12±0.04ms 2.52±0.1ms 0.81 rolling.Apply.time_rolling('DataFrame', 3, 'int', <built-in function sum>, True)
- 5.65±0.03ms 4.57±0.01ms 0.81 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'max')
- 10.1±0.1ms 8.15±0.03ms 0.81 stat_ops.FrameOps.time_op('median', 'float', 0)
- 3.12±0.06ms 2.52±0.1ms 0.81 rolling.Apply.time_rolling('DataFrame', 3, 'float', <built-in function sum>, True)
- 6.21±0.01ms 5.01±0.01ms 0.81 rolling.Methods.time_rolling('Series', 1000, 'float', 'kurt')
- 410±5μs 330±3μs 0.80 stat_ops.SeriesOps.time_op('mean', 'float')
- 49.0±0.9μs 39.4±0.3μs 0.80 series_methods.All.time_all(1000000, 'fast', 'bool')
- 66.6±0.6μs 53.2±0.7μs 0.80 series_methods.NanOps.time_func('max', 1000, 'int32')
- 100±0.9μs 79.8±1μs 0.79 series_methods.NanOps.time_func('mean', 1000, 'float64')
- 177±1ms 140±0.8ms 0.79 categoricals.Rank.time_rank_string
- 85.5±1ms 67.8±0.8ms 0.79 rolling.Groupby.time_rolling_offset('sum')
- 182±2μs 144±1μs 0.79 series_methods.NanOps.time_func('std', 1000, 'Int64')
- 66.6±0.6μs 52.8±0.1μs 0.79 series_methods.NanOps.time_func('max', 1000, 'int64')
- 177±0.7μs 140±1μs 0.79 series_methods.NanOps.time_func('std', 1000, 'float64')
- 1.03±0.02s 815±5ms 0.79 groupby.Apply.time_copy_overhead_single_col
- 66.6±0.7μs 52.7±0.3μs 0.79 series_methods.NanOps.time_func('max', 1000, 'int8')
- 85.5±0.3ms 67.6±0.1ms 0.79 rolling.Groupby.time_rolling_offset('kurt')
- 84.9±0.5ms 67.1±0.6ms 0.79 rolling.Groupby.time_rolling_offset('max')
- 9.05±0.02ms 7.14±0.03ms 0.79 join_merge.Merge.time_merge_dataframe_integer_2key(False)
- 6.64±0.7ms 5.24±0.03ms 0.79 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'kurt')
- 183±1μs 145±0.8μs 0.79 series_methods.NanOps.time_func('std', 1000, 'boolean')
- 2.31±0.04ms 1.82±0.07ms 0.79 rolling.Engine.time_expanding_apply('DataFrame', 'int', <function sum at 0x7f2790e97430>, 'numba')
- 2.11±0.01ms 1.66±0.03ms 0.79 rolling.EWMMethods.time_ewm('DataFrame', 1000, 'float', 'mean')
- 85.0±1ms 67.0±0.6ms 0.79 rolling.Groupby.time_rolling_offset('mean')
- 5.58±0.7ms 4.40±0.02ms 0.79 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'skew')
- 2.24±0.02ms 1.76±0.02ms 0.79 rolling.EWMMethods.time_ewm_times('DataFrame', 10, 'int', 'std')
- 2.12±0.01ms 1.66±0.02ms 0.79 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 15)
- 5.59±0.7ms 4.39±0.02ms 0.79 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'skew')
- 88.9±1ms 69.7±0.6ms 0.78 rolling.Groupby.time_rolling_offset('median')
- 3.92±0.02ms 3.07±0.05ms 0.78 series_methods.NanOps.time_func('mean', 1000000, 'Int64')
- 3.27±0.4ms 2.56±0.01ms 0.78 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'min')
- 5.50±0.05ms 4.31±0.02ms 0.78 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'std')
- 86.0±0.6ms 67.4±0.4ms 0.78 rolling.Groupby.time_rolling_offset('min')
- 2.46±0.01ms 1.92±0.03ms 0.78 groupby.RankWithTies.time_rank_ties('int64', 'average')
- 2.43±0.01ms 1.90±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('datetime64', 'average')
- 2.25±0.01ms 1.76±0.03ms 0.78 rolling.EWMMethods.time_ewm_times('DataFrame', 1000, 'int', 'mean')
- 151±2μs 118±1μs 0.78 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('period', 'unique_monotonic_inc')
- 2.44±0.02ms 1.90±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('datetime64', 'dense')
- 2.44±0.02ms 1.90±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('datetime64', 'min')
- 2.30±0.09ms 1.79±0.02ms 0.78 rolling.Engine.time_expanding_apply('DataFrame', 'int', <function Engine.<lambda> at 0x7f277d8de310>, 'numba')
- 2.45±0.01ms 1.90±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('int64', 'min')
- 2.25±0.01ms 1.75±0.02ms 0.78 rolling.EWMMethods.time_ewm_times('DataFrame', 1000, 'int', 'std')
- 2.44±0.02ms 1.90±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('datetime64', 'first')
- 34.6±0.3μs 26.9±0.6μs 0.78 series_methods.Any.time_any(1000, 'slow', 'bool')
- 2.44±0.01ms 1.90±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('int64', 'dense')
- 2.24±0.02ms 1.74±0.01ms 0.78 rolling.EWMMethods.time_ewm('DataFrame', 10, 'int', 'mean')
- 2.24±0.01ms 1.74±0.02ms 0.78 rolling.EWMMethods.time_ewm_times('DataFrame', 10, 'int', 'mean')
- 2.43±0.02ms 1.89±0.02ms 0.78 groupby.RankWithTies.time_rank_ties('float32', 'max')
- 2.41±0.02ms 1.86±0.01ms 0.78 groupby.RankWithTies.time_rank_ties('float64', 'dense')
- 2.12±0.03ms 1.64±0.01ms 0.78 rolling.EWMMethods.time_ewm_times('DataFrame', 10, 'float', 'mean')
- 2.44±0.03ms 1.89±0.02ms 0.77 groupby.RankWithTies.time_rank_ties('float32', 'min')
- 2.12±0.01ms 1.64±0.02ms 0.77 rolling.EWMMethods.time_ewm_times('DataFrame', 1000, 'float', 'std')
- 3.38±0.02ms 2.61±0.02ms 0.77 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'max')
- 2.45±0.01ms 1.90±0.01ms 0.77 groupby.RankWithTies.time_rank_ties('int64', 'first')
- 2.32±0.07ms 1.79±0.03ms 0.77 rolling.Engine.time_expanding_apply('DataFrame', 'float', <function sum at 0x7f2790e97430>, 'numba')
- 11.0±0.4μs 8.51±0.1μs 0.77 timeseries.TzLocalize.time_infer_dst(None)
- 75.4±1ms 58.3±0.2ms 0.77 reshape.Cut.time_qcut_timedelta(1000)
- 2.48±0.04ms 1.91±0.02ms 0.77 groupby.RankWithTies.time_rank_ties('datetime64', 'max')
- 2.46±0.02ms 1.89±0.02ms 0.77 groupby.RankWithTies.time_rank_ties('float32', 'dense')
- 2.12±0.01ms 1.63±0.01ms 0.77 rolling.EWMMethods.time_ewm_times('DataFrame', 10, 'float', 'std')
- 5.44±0.03ms 4.18±0.04ms 0.77 rolling.Pairwise.time_pairwise(None, 'cov', False)
- 2.32±0.05ms 1.78±0.03ms 0.77 rolling.Engine.time_expanding_apply('DataFrame', 'float', <function Engine.<lambda> at 0x7f277d8de310>, 'numba')
- 2.42±0.02ms 1.86±0.01ms 0.77 groupby.RankWithTies.time_rank_ties('float64', 'average')
- 11.5±0.06μs 8.86±0.1μs 0.77 indexing.CategoricalIndexIndexing.time_get_loc_scalar('monotonic_incr')
- 86.4±1ms 66.4±1ms 0.77 series_methods.SeriesConstructor.time_constructor('dict')
- 5.87±0.8ms 4.50±0.01ms 0.77 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'skew')
- 2.45±0.02ms 1.88±0.02ms 0.77 groupby.RankWithTies.time_rank_ties('float32', 'average')
- 2.42±0.02ms 1.86±0ms 0.77 groupby.RankWithTies.time_rank_ties('float64', 'min')
- 2.46±0.02ms 1.88±0.01ms 0.77 groupby.RankWithTies.time_rank_ties('float32', 'first')
- 1.03±0ms 789±4μs 0.77 period.Algorithms.time_value_counts('index')
- 6.71±0.01ms 5.13±0.01ms 0.77 rolling.Methods.time_rolling('Series', 1000, 'int', 'kurt')
- 2.49±0.05ms 1.90±0.02ms 0.76 groupby.RankWithTies.time_rank_ties('int64', 'max')
- 2.43±0.02ms 1.86±0.01ms 0.76 groupby.RankWithTies.time_rank_ties('float64', 'max')
- 3.94±0.01ms 3.01±0.02ms 0.76 series_methods.NanOps.time_func('max', 1000000, 'float64')
- 2.45±0.01ms 1.87±0.01ms 0.76 groupby.RankWithTies.time_rank_ties('float64', 'first')
- 35.4±0.3μs 27.0±0.3μs 0.76 series_methods.All.time_all(1000, 'slow', 'bool')
- 3.39±0.4ms 2.58±0.02ms 0.76 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'max')
- 5.64±0.7ms 4.30±0.01ms 0.76 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'float', 'std')
- 34.6±0.5μs 26.4±0.2μs 0.76 series_methods.Any.time_any(1000, 'fast', 'bool')
- 4.42±0.1μs 3.36±0.1μs 0.76 index_cached_properties.IndexCache.time_shape('DatetimeIndex')
- 33.4±0.3ms 25.4±0.5ms 0.76 categoricals.Indexing.time_intersection
- 72.3±10ms 54.9±0.3ms 0.76 reshape.Cut.time_qcut_datetime(1000)
- 35.0±0.2μs 26.6±0.4μs 0.76 series_methods.All.time_all(1000, 'fast', 'bool')
- 8.87±0.2μs 6.73±0.1μs 0.76 index_cached_properties.IndexCache.time_engine('DatetimeIndex')
- 85.0±0.8μs 64.4±0.9μs 0.76 series_methods.NanOps.time_func('sum', 1000, 'float64')
- 5.94±0.8ms 4.50±0.01ms 0.76 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'skew')
- 3.41±0.02s 2.57±0.03s 0.76 groupby.Apply.time_copy_function_multi_col
- 3.35±0.8ms 2.53±0.01ms 0.76 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'sum')
- 3.92±0.02ms 2.95±0.04ms 0.75 series_methods.NanOps.time_func('mean', 1000000, 'float64')
- 5.84±0.7ms 4.39±0.01ms 0.75 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'skew')
- 6.66±0.01ms 5.01±0.01ms 0.75 rolling.Methods.time_rolling('Series', 10, 'float', 'kurt')
- 14.3±0.4μs 10.7±0.4μs 0.75 index_cached_properties.IndexCache.time_engine('TimedeltaIndex')
- 958±9μs 717±3μs 0.75 period.Algorithms.time_value_counts('series')
- 8.93±0.5μs 6.68±0.2μs 0.75 index_cached_properties.IndexCache.time_engine('PeriodIndex')
- 5.81±0.7ms 4.34±0.02ms 0.75 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'float', 'std')
- 2.19±0.1ms 1.64±0.02ms 0.75 rolling.EWMMethods.time_ewm_times('DataFrame', 1000, 'float', 'mean')
- 5.52±0.7ms 4.12±0.01ms 0.75 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'float', 'std')
- 4.20±0.05ms 3.12±0.2ms 0.74 stat_ops.FrameOps.time_op('prod', 'float', 0)
- 4.67±0.1μs 3.46±0.2μs 0.74 index_cached_properties.IndexCache.time_shape('PeriodIndex')
- 134±2μs 99.4±0.4μs 0.74 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('period', 'non_monotonic')
- 303±2μs 223±1μs 0.74 index_cached_properties.IndexCache.time_is_monotonic('Float64Index')
- 4.86±0.07ms 3.58±0.06ms 0.74 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f277fe8a160>, True, 'float')
- 4.68±0.06ms 3.43±0.05ms 0.73 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f277fe8a160>, False, 'float')
- 5.87±0.7ms 4.30±0.02ms 0.73 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'skew')
- 666±3μs 487±0.8μs 0.73 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 13)
- 7.84±0.08μs 5.73±0.04μs 0.73 categoricals.SearchSorted.time_categorical_index_contains
- 57.8±0.7ms 42.2±0.4ms 0.73 reshape.Cut.time_cut_datetime(1000)
- 304±1μs 222±2μs 0.73 index_cached_properties.IndexCache.time_is_monotonic_increasing('Float64Index')
- 3.92±0.6ms 2.86±0.05ms 0.73 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'mean')
- 303±1μs 221±1μs 0.73 index_cached_properties.IndexCache.time_is_monotonic_decreasing('Float64Index')
- 5.39±0.2ms 3.92±0.2ms 0.73 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'count')
- 5.51±0.1ms 4.00±0.03ms 0.73 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'max')
- 5.44±0.4ms 3.95±0.2ms 0.73 rolling.Methods.time_rolling('DataFrame', 1000, 'float', 'count')
- 87.0±0.5μs 63.2±0.6μs 0.73 series_methods.NanOps.time_func('max', 1000, 'float64')
- 4.45±0.7ms 3.23±0.01ms 0.73 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'mean')
- 7.14±0.2μs 5.18±0.02μs 0.72 categoricals.SearchSorted.time_categorical_contains
- 4.38±0.7ms 3.17±0.01ms 0.72 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'mean')
- 87.6±0.4μs 63.3±0.7μs 0.72 series_methods.NanOps.time_func('min', 1000, 'float64')
- 4.48±0.7ms 3.23±0.01ms 0.72 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'mean')
- 112±1μs 80.5±0.7μs 0.72 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('period', 'non_monotonic')
- 5.43±0.1ms 3.91±0.2ms 0.72 rolling.Methods.time_rolling('DataFrame', 10, 'float', 'count')
- 299±1μs 215±1μs 0.72 index_cached_properties.IndexCache.time_is_monotonic_increasing('UInt64Index')
- 299±2μs 215±2μs 0.72 index_cached_properties.IndexCache.time_is_monotonic('UInt64Index')
- 112±2μs 80.2±0.5μs 0.72 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('period', 'nonunique_monotonic_inc')
- 299±2μs 214±1μs 0.72 index_cached_properties.IndexCache.time_is_monotonic_decreasing('UInt64Index')
- 7.18±0.01ms 5.14±0.02ms 0.72 rolling.Methods.time_rolling('Series', 10, 'int', 'kurt')
- 5.41±0.4ms 3.87±0.2ms 0.72 rolling.Methods.time_rolling('DataFrame', 1000, 'int', 'count')
- 111±2μs 79.3±0.2μs 0.71 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('period', 'unique_monotonic_inc')
- 63.6±1ms 45.3±0.1ms 0.71 reshape.Cut.time_cut_timedelta(1000)
- 4.12±0.7ms 2.92±0.01ms 0.71 rolling.VariableWindowMethods.time_rolling('DataFrame', '1h', 'int', 'sum')
- 196M 139M 0.71 rolling.PeakMemFixedWindowMinMax.peakmem_fixed('max')
- 196M 139M 0.71 rolling.PeakMemFixedWindowMinMax.peakmem_fixed('min')
- 6.04±0.02ms 4.28±0.02ms 0.71 rolling.Methods.time_rolling('Series', 1000, 'float', 'skew')
- 32.9±0.5ms 23.2±1ms 0.71 hash_functions.UniqueAndFactorizeArange.time_factorize(7)
- 4.10±0.7ms 2.90±0.02ms 0.71 rolling.VariableWindowMethods.time_rolling('DataFrame', '1d', 'int', 'sum')
- 6.75±0.02ms 4.75±0.01ms 0.70 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'kurt')
- 5.37±1μs 3.78±0.1μs 0.70 index_cached_properties.IndexCache.time_values('TimedeltaIndex')
- 6.76±0.03ms 4.75±0.01ms 0.70 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'kurt')
- 163±10μs 114±1μs 0.70 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('period', 'nonunique_monotonic_inc')
- 104±10ms 72.7±4ms 0.70 frame_methods.Equals.time_frame_object_equal
- 6.21±0.03ms 4.34±0.01ms 0.70 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'min')
- 33.4±1ms 23.3±1ms 0.70 hash_functions.UniqueAndFactorizeArange.time_factorize(12)
- 6.99±0.1ms 4.86±0.03ms 0.70 gil.ParallelRolling.time_rolling('var')
- 6.12±0.03ms 4.25±0.04ms 0.70 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'min')
- 5.65±0.4ms 3.93±0.02ms 0.69 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'min')
- 6.20±0.03ms 4.28±0.01ms 0.69 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'min')
- 4.32±0.7ms 2.95±0.03ms 0.68 rolling.VariableWindowMethods.time_rolling('DataFrame', '50s', 'int', 'sum')
- 6.35±0.03ms 4.33±0.01ms 0.68 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'max')
- 45.5±0.2ms 30.9±0.03ms 0.68 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 8000, -2)
- 5.79±0.03ms 3.92±0.03ms 0.68 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'max')
- 2.75±0ms 1.86±0.02ms 0.68 series_methods.NanOps.time_func('argmax', 1000000, 'float64')
- 7.78±0.2ms 5.25±0.7ms 0.67 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'std')
- 8.70±1μs 5.87±0.2μs 0.67 index_cached_properties.IndexCache.time_shape('TimedeltaIndex')
- 1.78±0.04ms 1.20±0.06ms 0.67 replace.FillNa.time_replace(True)
- 6.31±0.02ms 4.24±0.02ms 0.67 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'max')
- 519±3ms 348±2ms 0.67 series_methods.IsInLongSeriesLookUpDominates.time_isin('object', 5, 'random_misses')
- 6.56±0.01ms 4.39±0.02ms 0.67 rolling.Methods.time_rolling('Series', 1000, 'int', 'skew')
- 4.67±0.03ms 3.11±0.01ms 0.67 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'mean')
- 5.72±0.03ms 3.79±0.01ms 0.66 rolling.Methods.time_rolling('Series', 1000, 'float', 'std')
- 40.9±1μs 27.1±0.2μs 0.66 series_methods.NanOps.time_func('argmax', 1000, 'int32')
- 73.1±0.6μs 48.3±0.5μs 0.66 series_methods.NanOps.time_func('argmax', 1000, 'float64')
- 41.0±0.8μs 27.1±0.2μs 0.66 series_methods.NanOps.time_func('argmax', 1000, 'int8')
- 17.4±0.2ms 11.5±2ms 0.66 stat_ops.FrameOps.time_op('skew', 'float', 0)
- 6.50±0.03ms 4.28±0.01ms 0.66 rolling.Methods.time_rolling('Series', 10, 'float', 'skew')
- 1.09±0.05ms 717±60μs 0.66 rolling.Engine.time_rolling_apply('DataFrame', 'int', <function sum at 0x7f2790e97430>, 'numba')
- 2.67±0.05μs 1.75±0.03μs 0.66 period.Indexing.time_shallow_copy
- 2.75±0.01ms 1.80±0.01ms 0.65 series_methods.NanOps.time_func('prod', 1000000, 'int8')
- 1.35±0ms 879±3μs 0.65 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 14)
- 234±2μs 153±1μs 0.65 stat_ops.SeriesOps.time_op('sum', 'float')
- 41.4±0.4μs 27.0±0.1μs 0.65 series_methods.NanOps.time_func('argmax', 1000, 'int64')
- 6.50±0.02ms 4.19±0.02ms 0.64 rolling.Methods.time_rolling('Series', 1000, 'float', 'min')
- 13.3±1ms 8.57±0.05ms 0.64 series_methods.NanOps.time_func('std', 1000000, 'float64')
- 6.51±0.01ms 4.18±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'midpoint')
- 6.55±0.01ms 4.20±0.03ms 0.64 rolling.Methods.time_rolling('Series', 1000, 'float', 'max')
- 6.51±0.02ms 4.17±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'linear')
- 6.50±0.03ms 4.16±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'nearest')
- 6.50±0.03ms 4.16±0.02ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'higher')
- 15.7±0.9ms 10.1±0.9ms 0.64 stat_ops.FrameOps.time_op('sem', 'int', 0)
- 359±1μs 229±1μs 0.64 index_cached_properties.IndexCache.time_is_monotonic('CategoricalIndex')
- 359±0.9μs 229±1μs 0.64 index_cached_properties.IndexCache.time_is_monotonic_decreasing('CategoricalIndex')
- 482±2μs 308±2μs 0.64 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 12)
- 6.53±0.03ms 4.17±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 0, 'lower')
- 6.55±0.01ms 4.18±0.02ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'linear')
- 6.57±0.02ms 4.19±0.02ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'nearest')
- 359±1μs 229±1μs 0.64 index_cached_properties.IndexCache.time_is_monotonic_increasing('CategoricalIndex')
- 6.54±0.01ms 4.17±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'higher')
- 4.38±0.02ms 2.79±0.01ms 0.64 rolling.Methods.time_rolling('DataFrame', 10, 'int', 'sum')
- 6.54±0.02ms 4.16±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'midpoint')
- 6.14±0.3ms 3.90±0.03ms 0.64 gil.ParallelRolling.time_rolling('mean')
- 6.57±0.01ms 4.18±0.01ms 0.64 rolling.Quantile.time_quantile('Series', 1000, 'float', 1, 'lower')
- 7.69±0.5ms 4.87±0.02ms 0.63 stat_ops.FrameOps.time_op('mad', 'int', 0)
- 7.02±0.03ms 4.43±0.03ms 0.63 rolling.Methods.time_rolling('Series', 10, 'int', 'skew')
- 4.49±0.01ms 2.82±0.01ms 0.63 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'nearest')
- 6.94±0.7ms 4.36±0.01ms 0.63 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'min')
- 4.49±0.01ms 2.81±0.01ms 0.63 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'lower')
- 97.8±8ms 61.3±1ms 0.63 frame_methods.Equals.time_frame_object_unequal
- 4.50±0.01ms 2.82±0.01ms 0.63 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'higher')
- 4.50±0.01ms 2.82±0.02ms 0.63 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'midpoint')
- 4.57±0.01ms 2.86±0.03ms 0.63 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'linear')
- 6.24±0.04ms 3.90±0.02ms 0.63 rolling.Methods.time_rolling('Series', 1000, 'int', 'std')
- 6.82±0.02ms 4.26±0.02ms 0.63 rolling.Methods.time_rolling('Series', 10, 'float', 'min')
- 2.04±0.02ms 1.27±0ms 0.62 series_methods.NanOps.time_func('sum', 1000000, 'int8')
- 7.19±0.8ms 4.49±0.03ms 0.62 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'min')
- 6.81±0.01ms 4.25±0.01ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'linear')
- 7.02±0.8ms 4.38±0.01ms 0.62 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'max')
- 7.04±0.8ms 4.38±0.03ms 0.62 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'min')
- 4.49±0.01ms 2.80±0.02ms 0.62 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 0, 'linear')
- 6.86±0.01ms 4.26±0.01ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'linear')
- 6.85±0.03ms 4.26±0.01ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'nearest')
- 6.88±0.02ms 4.27±0.02ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'lower')
- 6.83±0.02ms 4.24±0.02ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'midpoint')
- 6.84±0.02ms 4.24±0.02ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'nearest')
- 5.81±0.02ms 3.60±0.05ms 0.62 rolling.ExpandingMethods.time_expanding('Series', 'float', 'kurt')
- 4.57±0.01ms 2.83±0.02ms 0.62 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'midpoint')
- 4.59±0.02ms 2.84±0.01ms 0.62 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'lower')
- 6.90±0.03ms 4.27±0.02ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'midpoint')
- 6.85±0.02ms 4.24±0.01ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'lower')
- 6.89±0.02ms 4.27±0.01ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 1, 'higher')
- 6.85±0.03ms 4.24±0.02ms 0.62 rolling.Quantile.time_quantile('Series', 10, 'float', 0, 'higher')
- 6.64±0.09ms 4.10±0.03ms 0.62 period.DataFramePeriodColumn.time_set_index
- 6.91±0.08ms 4.26±0.01ms 0.62 rolling.Methods.time_rolling('Series', 10, 'float', 'max')
- 4.59±0.03ms 2.83±0.03ms 0.62 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'higher')
- 4.58±0.02ms 2.82±0.01ms 0.62 rolling.Quantile.time_quantile('DataFrame', 10, 'int', 1, 'nearest')
- 7.00±0.4ms 4.29±0ms 0.61 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'max')
- 7.38±0.8ms 4.51±0.01ms 0.61 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'max')
- 6.45±0.8ms 3.94±0.01ms 0.61 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'std')
- 6.96±0.02ms 4.25±0.02ms 0.61 rolling.Methods.time_rolling('Series', 1000, 'int', 'min')
- 18.0±0.4ms 10.9±1ms 0.61 stat_ops.FrameOps.time_op('kurt', 'float', 0)
- 6.46±0.8ms 3.92±0.01ms 0.61 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'std')
- 6.25±0.8ms 3.78±0.04ms 0.61 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'std')
- 7.21±0.8ms 4.36±0.01ms 0.60 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'max')
- 14.0±1ms 8.42±0.07ms 0.60 series_methods.NanOps.time_func('median', 1000000, 'float64')
- 1.30±0.01ms 779±7μs 0.60 groupby.GroupByMethods.time_dtype_as_group('int', 'rank', 'transformation')
- 1.04±0.02ms 625±20μs 0.60 rolling.Engine.time_rolling_apply('DataFrame', 'int', <function Engine.<lambda> at 0x7f277d8de310>, 'numba')
- 1.29±0.01ms 774±4μs 0.60 groupby.GroupByMethods.time_dtype_as_field('int', 'rank', 'direct')
- 7.07±0.03ms 4.24±0.01ms 0.60 rolling.Methods.time_rolling('Series', 1000, 'int', 'max')
- 7.92±0.2ms 4.73±0.7ms 0.60 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'std')
- 1.29±0ms 773±3μs 0.60 groupby.GroupByMethods.time_dtype_as_field('int', 'rank', 'transformation')
- 210±0.8ms 125±0.7ms 0.60 groupby.DateAttributes.time_len_groupby_object
- 1.30±0.01ms 775±2μs 0.59 groupby.GroupByMethods.time_dtype_as_group('int', 'rank', 'direct')
- 1.31±0.01ms 780±5μs 0.59 groupby.GroupByMethods.time_dtype_as_group('float', 'rank', 'direct')
- 7.33±0.03ms 4.35±0.01ms 0.59 rolling.Methods.time_rolling('Series', 10, 'int', 'min')
- 1.27±0.01ms 755±4μs 0.59 groupby.GroupByMethods.time_dtype_as_field('float', 'rank', 'transformation')
- 7.40±0.03ms 4.38±0.01ms 0.59 rolling.Methods.time_rolling('Series', 10, 'int', 'max')
- 2.32±0.01ms 1.37±0.01ms 0.59 series_methods.NanOps.time_func('sum', 1000000, 'float64')
- 6.35±0.01ms 3.76±0.06ms 0.59 rolling.ExpandingMethods.time_expanding('Series', 'int', 'kurt')
- 7.98±0.2ms 4.72±0.7ms 0.59 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'std')
- 1.32±0.01ms 778±4μs 0.59 groupby.GroupByMethods.time_dtype_as_group('float', 'rank', 'transformation')
- 1.06±0.03ms 624±60μs 0.59 rolling.Engine.time_rolling_apply('DataFrame', 'float', <function sum at 0x7f2790e97430>, 'numba')
- 29.1±1ms 17.1±2ms 0.59 hash_functions.UniqueAndFactorizeArange.time_unique(7)
- 1.03±0.05ms 605±10μs 0.59 rolling.Engine.time_rolling_apply('DataFrame', 'float', <function Engine.<lambda> at 0x7f277d8de310>, 'numba')
- 1.28±0.01ms 752±2μs 0.59 groupby.GroupByMethods.time_dtype_as_field('float', 'rank', 'direct')
- 29.4±1ms 17.2±2ms 0.58 hash_functions.UniqueAndFactorizeArange.time_unique(12)
- 4.45±0.01ms 2.59±0.02ms 0.58 rolling.EWMMethods.time_ewm('Series', 1000, 'int', 'std')
- 4.44±0.02ms 2.58±0.03ms 0.58 rolling.EWMMethods.time_ewm('Series', 10, 'int', 'std')
- 6.53±0.02ms 3.79±0.01ms 0.58 rolling.Methods.time_rolling('Series', 10, 'float', 'std')
- 5.45±0.01ms 3.15±0.1ms 0.58 rolling.ExpandingMethods.time_expanding('DataFrame', 'int', 'count')
- 1.33±0.01ms 765±3μs 0.58 groupby.GroupByMethods.time_dtype_as_group('datetime', 'rank', 'direct')
- 1.33±0.01ms 762±2μs 0.57 groupby.GroupByMethods.time_dtype_as_group('datetime', 'rank', 'transformation')
- 384±2μs 218±2μs 0.57 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 11)
- 4.36±0.01ms 2.45±0.03ms 0.56 rolling.EWMMethods.time_ewm('Series', 10, 'float', 'std')
- 4.36±0.01ms 2.44±0.01ms 0.56 rolling.EWMMethods.time_ewm('Series', 1000, 'float', 'std')
- 6.32±0.03ms 3.52±0.1ms 0.56 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'kurt')
- 6.32±0.01ms 3.53±0.03ms 0.56 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'kurt')
- 7.07±0.05ms 3.94±0.01ms 0.56 rolling.Methods.time_rolling('Series', 10, 'int', 'std')
- 6.31±0.01ms 3.50±0.02ms 0.55 rolling.ExpandingMethods.time_expanding('Series', 'float', 'min')
- 4.99±0.7ms 2.77±0.01ms 0.55 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'mean')
- 4.95±0.7ms 2.74±0.03ms 0.55 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'mean')
- 6.39±0.01ms 3.50±0.03ms 0.55 rolling.ExpandingMethods.time_expanding('Series', 'float', 'max')
- 4.94±0.7ms 2.70±0.03ms 0.55 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'mean')
- 5.24±0.8ms 2.87±0.02ms 0.55 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'mean')
- 3.94±0.05ms 2.16±0.01ms 0.55 series_methods.ValueCounts.time_value_counts('float')
- 56.0±0.5ms 30.6±0.05ms 0.55 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 2000, 2)
- 5.29±0.8ms 2.88±0.01ms 0.55 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'mean')
- 1.12±0ms 611±5μs 0.54 groupby.GroupByMethods.time_dtype_as_field('datetime', 'rank', 'transformation')
- 1.13±0ms 612±3μs 0.54 groupby.GroupByMethods.time_dtype_as_field('datetime', 'rank', 'direct')
- 5.21±0.8ms 2.81±0.01ms 0.54 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'mean')
- 43.0±0.1ms 23.0±0.1ms 0.54 join_merge.Concat.time_concat_small_frames(0)
- 88.6±1ms 47.4±0.09ms 0.54 frame_methods.Equals.time_frame_nonunique_equal
- 6.80±0.01ms 3.63±0.02ms 0.53 rolling.ExpandingMethods.time_expanding('Series', 'int', 'min')
- 89.8±1ms 48.0±0.2ms 0.53 frame_methods.Equals.time_frame_nonunique_unequal
- 5.89±0.03ms 3.15±0.04ms 0.53 rolling.ExpandingMethods.time_expanding('Series', 'float', 'skew')
- 956±4μs 507±2μs 0.53 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 13)
- 6.89±0.02ms 3.63±0.02ms 0.53 rolling.ExpandingMethods.time_expanding('Series', 'int', 'max')
- 1.14±0.01ms 595±6μs 0.52 groupby.GroupByMethods.time_dtype_as_group('float', 'cumprod', 'transformation')
- 67.4±0.3ms 35.3±0.3ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 5, 'random_hits')
- 68.9±0.4ms 36.1±0.3ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 5, 'random_hits')
- 68.3±0.3ms 35.7±0.4ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 5, 'monotone_hits')
- 1.14±0.01ms 594±5μs 0.52 groupby.GroupByMethods.time_dtype_as_group('float', 'cumprod', 'direct')
- 1.11±0ms 580±2μs 0.52 groupby.GroupByMethods.time_dtype_as_group('int', 'cumprod', 'transformation')
- 68.3±0.4ms 35.5±0.4ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 5, 'random_misses')
- 68.0±0.3ms 35.3±0.3ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 5, 'monotone_misses')
- 66.7±0.4ms 34.6±0.4ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 5, 'random_misses')
- 4.66±0.7ms 2.42±0.01ms 0.52 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'float', 'sum')
- 67.2±0.3ms 34.8±0.3ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 5, 'monotone_hits')
- 66.9±0.2ms 34.6±0.3ms 0.52 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 5, 'monotone_misses')
- 6.41±0.01ms 3.31±0.06ms 0.52 rolling.ExpandingMethods.time_expanding('Series', 'int', 'skew')
- 1.13±0.03ms 582±8μs 0.52 groupby.GroupByMethods.time_dtype_as_group('int', 'cumprod', 'direct')
- 4.95±0.8ms 2.55±0.02ms 0.51 rolling.VariableWindowMethods.time_rolling('Series', '1h', 'int', 'sum')
- 4.65±0.7ms 2.39±0.01ms 0.51 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'float', 'sum')
- 4.71±0.7ms 2.42±0.01ms 0.51 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'float', 'sum')
- 1.08±0.01ms 556±2μs 0.51 groupby.GroupByMethods.time_dtype_as_field('int', 'cumprod', 'transformation')
- 1.09±0.01ms 557±2μs 0.51 groupby.GroupByMethods.time_dtype_as_field('int', 'cumprod', 'direct')
- 7.78±0.02ms 3.97±0.01ms 0.51 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'min')
- 7.86±0.02ms 4.01±0.02ms 0.51 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'max')
- 5.89±0.2μs 2.93±0.03μs 0.50 categoricals.Indexing.time_get_loc
- 338±2μs 167±0.9μs 0.50 hash_functions.IsinAlmostFullWithRandomInt.time_isin_outside(<class 'numpy.float64'>, 10)
- 5.30±0.03ms 2.62±0.01ms 0.49 rolling.Methods.time_rolling('Series', 1000, 'float', 'mean')
- 5.53±0.01ms 2.73±0.02ms 0.49 rolling.ExpandingMethods.time_expanding('DataFrame', 'float', 'count')
- 1.59±0ms 782±2μs 0.49 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.float64'>, 8000)
- 5.29±0.8ms 2.57±0.01ms 0.49 rolling.VariableWindowMethods.time_rolling('Series', '50s', 'int', 'sum')
- 621±1ms 302±0.3ms 0.49 series_methods.IsInLongSeriesLookUpDominates.time_isin('float64', 1000, 'monotone_misses')
- 4.64±0.3ms 2.23±0.01ms 0.48 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'min')
- 4.70±0.3ms 2.25±0.01ms 0.48 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'max')
- 5.82±0.02ms 2.74±0.04ms 0.47 rolling.Methods.time_rolling('Series', 1000, 'int', 'mean')
- 5.01±0.01ms 2.31±0.02ms 0.46 rolling.Methods.time_rolling('Series', 1000, 'float', 'sum')
- 5.73±0.01ms 2.63±0.01ms 0.46 rolling.Methods.time_rolling('Series', 10, 'float', 'mean')
- 11.4±0.8ms 5.20±0.02ms 0.46 stat_ops.FrameOps.time_op('mad', 'int', 1)
- 1.58±0s 713±5ms 0.45 series_methods.IsInLongSeriesValuesDominate.time_isin('float64', 'random')
- 5.65±0.8ms 2.53±0.01ms 0.45 rolling.VariableWindowMethods.time_rolling('Series', '1d', 'int', 'sum')
- 5.72±0.02ms 2.54±0.03ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'midpoint')
- 5.71±0.02ms 2.53±0.02ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'linear')
- 6.24±0.01ms 2.77±0.02ms 0.44 rolling.Methods.time_rolling('Series', 10, 'int', 'mean')
- 5.69±0.02ms 2.52±0.01ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'lower')
- 41.1±0.3ms 18.1±0.05ms 0.44 index_object.Range.time_iter_dec
- 5.74±0.02ms 2.52±0.01ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'lower')
- 6.08±0.03ms 2.67±0.2ms 0.44 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'nearest')
- 5.69±0.04ms 2.50±0.04ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'midpoint')
- 5.74±0.03ms 2.51±0.01ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'nearest')
- 5.74±0.02ms 2.51±0.01ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 1, 'higher')
- 5.70±0.02ms 2.49±0.01ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'linear')
- 5.72±0.01ms 2.50±0.02ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'nearest')
- 41.5±0.9ms 18.1±0.1ms 0.44 index_object.Range.time_iter_inc
- 5.58±0.02ms 2.44±0.02ms 0.44 rolling.Methods.time_rolling('Series', 1000, 'int', 'sum')
- 6.08±0.02ms 2.65±0.2ms 0.44 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'higher')
- 5.71±0.04ms 2.48±0.01ms 0.44 rolling.Quantile.time_quantile('Series', 1000, 'int', 0, 'higher')
- 639±0.5ms 278±0.7ms 0.44 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 1000, 'monotone_misses')
- 915±5μs 394±3μs 0.43 groupby.GroupByMethods.time_dtype_as_field('int', 'cummax', 'transformation')
- 920±9μs 393±4μs 0.43 groupby.GroupByMethods.time_dtype_as_group('int', 'cummax', 'transformation')
- 913±3μs 389±4μs 0.43 groupby.GroupByMethods.time_dtype_as_group('int', 'cummin', 'transformation')
- 939±4μs 400±4μs 0.43 groupby.GroupByMethods.time_dtype_as_group('float', 'cumsum', 'direct')
- 914±4μs 389±2μs 0.43 groupby.GroupByMethods.time_dtype_as_group('int', 'cummax', 'direct')
- 912±8μs 388±3μs 0.43 groupby.GroupByMethods.time_dtype_as_field('int', 'cummin', 'direct')
- 925±9μs 393±4μs 0.42 groupby.GroupByMethods.time_dtype_as_field('int', 'cummax', 'direct')
- 5.45±0.02ms 2.31±0ms 0.42 rolling.Methods.time_rolling('Series', 10, 'float', 'sum')
- 4.40±0.04ms 1.87±0.02ms 0.42 stat_ops.FrameOps.time_op('mean', 'float', 0)
- 913±3μs 387±2μs 0.42 groupby.GroupByMethods.time_dtype_as_field('int', 'cummin', 'transformation')
- 909±4μs 383±4μs 0.42 groupby.GroupByMethods.time_dtype_as_field('int', 'cumsum', 'direct')
- 915±4μs 385±3μs 0.42 groupby.GroupByMethods.time_dtype_as_group('int', 'cummin', 'direct')
- 912±3μs 383±3μs 0.42 groupby.GroupByMethods.time_dtype_as_group('int', 'cumsum', 'direct')
- 4.38±0.04ms 1.83±0.02ms 0.42 stat_ops.FrameOps.time_op('sum', 'float', 0)
- 943±7μs 395±4μs 0.42 groupby.GroupByMethods.time_dtype_as_group('float', 'cumsum', 'transformation')
- 931±4μs 390±1μs 0.42 groupby.GroupByMethods.time_dtype_as_group('float', 'cummin', 'transformation')
- 759±5μs 318±4μs 0.42 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 12)
- 907±9μs 379±3μs 0.42 groupby.GroupByMethods.time_dtype_as_field('int', 'cumsum', 'transformation')
- 936±8μs 391±3μs 0.42 groupby.GroupByMethods.time_dtype_as_group('float', 'cummax', 'direct')
- 16.8±0.9ms 7.03±0.3ms 0.42 stat_ops.FrameOps.time_op('mad', 'float', 1)
- 932±20μs 388±9μs 0.42 groupby.GroupByMethods.time_dtype_as_group('int', 'cumsum', 'transformation')
- 934±20μs 389±3μs 0.42 groupby.GroupByMethods.time_dtype_as_group('float', 'cummax', 'transformation')
- 935±2μs 388±2μs 0.42 groupby.GroupByMethods.time_dtype_as_group('float', 'cummin', 'direct')
- 1.50±0s 621±2ms 0.42 series_methods.IsInLongSeriesValuesDominate.time_isin('int64', 'random')
- 1.61±0s 667±5ms 0.41 series_methods.IsInLongSeriesValuesDominate.time_isin('float32', 'random')
- 3.24±0.2ms 1.34±0.01ms 0.41 rolling.EWMMethods.time_ewm_times('Series', 1000, 'int', 'std')
- 6.17±0.03ms 2.53±0.02ms 0.41 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'nearest')
- 6.07±0.01ms 2.48±0.02ms 0.41 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'lower')
- 3.28±0.2ms 1.34±0.01ms 0.41 rolling.EWMMethods.time_ewm_times('Series', 10, 'int', 'std')
- 3.28±0.2ms 1.34±0ms 0.41 rolling.EWMMethods.time_ewm('Series', 1000, 'int', 'mean')
- 5.99±0.02ms 2.45±0.01ms 0.41 rolling.Methods.time_rolling('Series', 10, 'int', 'sum')
- 14.0±0.9ms 5.70±1ms 0.41 stat_ops.FrameOps.time_op('mad', 'float', 0)
- 6.06±0.02ms 2.47±0.01ms 0.41 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'linear')
- 3.28±0.2ms 1.34±0.01ms 0.41 rolling.EWMMethods.time_ewm_times('Series', 10, 'int', 'mean')
- 6.06±0.02ms 2.47±0.01ms 0.41 rolling.Quantile.time_quantile('Series', 10, 'int', 0, 'midpoint')
- 5.83±0.03ms 2.37±0.04ms 0.41 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'mean')
- 3.30±0.2ms 1.34±0.01ms 0.41 rolling.EWMMethods.time_ewm_times('Series', 1000, 'int', 'mean')
- 6.16±0.03ms 2.49±0.01ms 0.40 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'lower')
- 6.16±0.01ms 2.49±0.01ms 0.40 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'higher')
- 6.17±0.03ms 2.49±0.02ms 0.40 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'linear')
- 5.82±0.01ms 2.35±0.01ms 0.40 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'mean')
- 949±8μs 383±4μs 0.40 groupby.GroupByMethods.time_dtype_as_group('datetime', 'cummin', 'transformation')
- 6.17±0.1ms 2.48±0.01ms 0.40 rolling.Quantile.time_quantile('Series', 10, 'int', 1, 'midpoint')
- 950±5μs 382±2μs 0.40 groupby.GroupByMethods.time_dtype_as_group('datetime', 'cummin', 'direct')
- 52.1±0.09ms 20.8±0.06ms 0.40 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 8000, 0)
- 6.34±0.01ms 2.49±0.01ms 0.39 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'mean')
- 859±3μs 336±3μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cumprod', 'transformation')
- 3.14±0.01ms 1.23±0.02ms 0.39 rolling.EWMMethods.time_ewm('Series', 1000, 'float', 'mean')
- 3.13±0.01ms 1.22±0.01ms 0.39 rolling.EWMMethods.time_ewm_times('Series', 10, 'float', 'std')
- 6.34±0.01ms 2.47±0ms 0.39 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'mean')
- 866±5μs 337±2μs 0.39 groupby.GroupByMethods.time_dtype_as_field('datetime', 'cummin', 'transformation')
- 3.14±0.01ms 1.22±0ms 0.39 rolling.EWMMethods.time_ewm_times('Series', 1000, 'float', 'mean')
- 859±2μs 335±2μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cumsum', 'direct')
- 3.14±0.02ms 1.22±0.01ms 0.39 rolling.EWMMethods.time_ewm_times('Series', 10, 'float', 'mean')
- 866±3μs 336±3μs 0.39 groupby.GroupByMethods.time_dtype_as_field('datetime', 'cummin', 'direct')
- 3.14±0.02ms 1.22±0.01ms 0.39 rolling.EWMMethods.time_ewm_times('Series', 1000, 'float', 'std')
- 867±5μs 336±4μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cummin', 'transformation')
- 870±4μs 337±1μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cummax', 'transformation')
- 871±7μs 337±0.9μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cummax', 'direct')
- 858±7μs 332±2μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cumsum', 'transformation')
- 865±3μs 334±3μs 0.39 groupby.GroupByMethods.time_dtype_as_field('float', 'cumprod', 'direct')
- 3.15±0.02ms 1.22±0.01ms 0.39 rolling.EWMMethods.time_ewm('Series', 10, 'float', 'mean')
- 5.23±0.05ms 2.01±0ms 0.38 stat_ops.FrameOps.time_op('mean', 'float', 1)
- 768±2μs 294±7μs 0.38 indexing_engines.NumericEngineIndexing.time_get_loc((<class 'pandas._libs.index.Int16Engine'>, <class 'numpy.int16'>), 'monotonic_incr')
- 873±2μs 334±2μs 0.38 groupby.GroupByMethods.time_dtype_as_field('float', 'cummin', 'direct')
- 3.51±0.2ms 1.33±0ms 0.38 rolling.EWMMethods.time_ewm('Series', 10, 'int', 'mean')
- 1.02±0ms 388±1μs 0.38 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 1300)
- 1.70±0.01ms 640±3μs 0.38 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 2000)
- 1.70±0.01ms 638±6μs 0.37 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 2000)
- 5.50±0.01ms 2.06±0.04ms 0.37 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'sum')
- 5.51±0.02ms 2.06±0.01ms 0.37 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'sum')
- 5.06±0.02ms 1.89±0.03ms 0.37 stat_ops.FrameOps.time_op('sum', 'float', 1)
- 27.2±2ms 10.0±3ms 0.37 stat_ops.FrameOps.time_op('sem', 'float', 0)
- 5.01±0.01ms 1.84±0.03ms 0.37 rolling.ExpandingMethods.time_expanding('Series', 'float', 'mean')
- 13.2±0.8ms 4.83±1ms 0.37 stat_ops.FrameOps.time_op('var', 'float', 0)
- 6.22±0.03ms 2.27±0.01ms 0.37 rolling.ExpandingMethods.time_expanding('Series', 'float', 'std')
- 1.12±0ms 409±4μs 0.36 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 1300)
- 6.03±0.02ms 2.19±0.01ms 0.36 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'sum')
- 6.05±0.05ms 2.18±0.01ms 0.36 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'sum')
- 4.72±0.02ms 1.69±0.02ms 0.36 rolling.ExpandingMethods.time_expanding('Series', 'float', 'sum')
- 6.75±0.03ms 2.41±0.05ms 0.36 rolling.ExpandingMethods.time_expanding('Series', 'int', 'std')
- 5.59±0.01ms 1.96±0.02ms 0.35 rolling.ExpandingMethods.time_expanding('Series', 'int', 'mean')
- 26.2±2ms 9.02±0.3ms 0.34 frame_methods.Equals.time_frame_float_unequal
- 5.26±0.03ms 1.81±0.04ms 0.34 rolling.ExpandingMethods.time_expanding('Series', 'int', 'sum')
- 5.93±0.02ms 2.03±0.02ms 0.34 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 7000)
- 6.51±0.02ms 2.21±0.01ms 0.34 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'min')
- 772±6μs 260±2μs 0.34 series_methods.IsInDatetime64.time_isin_empty
- 89.2±0.2ms 30.0±0.04ms 0.34 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 1000, 2)
- 6.60±0.01ms 2.22±0.01ms 0.34 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'max')
- 9.09±0.02ms 3.02±0.1ms 0.33 rolling.Methods.time_rolling('Series', 1000, 'float', 'count')
- 646±7μs 214±2μs 0.33 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 11)
- 8.99±0.01ms 2.97±0.1ms 0.33 rolling.Methods.time_rolling('Series', 1000, 'int', 'count')
- 812±40μs 268±3μs 0.33 indexing_engines.NumericEngineIndexing.time_get_loc((<class 'pandas._libs.index.Int8Engine'>, <class 'numpy.int8'>), 'monotonic_incr')
- 7.00±0.03ms 2.30±0.02ms 0.33 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 8000)
- 1.51±0s 488±1ms 0.32 series_methods.IsInLongSeriesValuesDominate.time_isin('int32', 'random')
- 9.52±0.04ms 3.06±0.1ms 0.32 rolling.Methods.time_rolling('Series', 10, 'float', 'count')
- 9.45±0.07ms 2.99±0.1ms 0.32 rolling.Methods.time_rolling('Series', 10, 'int', 'count')
- 6.10±0.1ms 1.92±0ms 0.32 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 7000)
- 98.7±0.3ms 30.5±0.1ms 0.31 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 2000, -2)
- 586±1ms 179±0.2ms 0.31 series_methods.IsInLongSeriesLookUpDominates.time_isin('int64', 1000, 'monotone_misses')
- 529±6μs 162±1μs 0.31 hash_functions.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.float64'>, 10)
- 7.26±0.08ms 2.19±0.01ms 0.30 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 8000)
- 14.3±0.2ms 4.25±2ms 0.30 stat_ops.FrameOps.time_op('std', 'float', 0)
- 1.02±0.01ms 297±1μs 0.29 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.float64'>, 2000)
- 8.86±0.2ms 2.56±0.02ms 0.29 arithmetic.Timeseries.time_timestamp_ops_diff(None)
- 16.3±0.05ms 4.67±0.04ms 0.29 indexing.InsertColumns.time_assign_list_like_with_setitem
- 939±8μs 263±3μs 0.28 series_methods.IsInDatetime64.time_isin_mismatched_dtype
- 78.2±3ms 21.5±0.4ms 0.28 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 70000)
- 601±1ms 160±0.1ms 0.27 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 1000, 'monotone_misses')
- 1.71±0.01ms 437±2μs 0.26 series_methods.Dir.time_dir_strings
- 109±0.9ms 27.0±0.3ms 0.25 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 80000)
- 495±0.9ms 120±0.8ms 0.24 series_methods.IsInLongSeriesLookUpDominates.time_isin('float64', 1000, 'monotone_hits')
- 8.81±0.06ms 2.09±0.1ms 0.24 rolling.ExpandingMethods.time_expanding('Series', 'float', 'count')
- 864±10μs 205±0.8μs 0.24 hash_functions.IsinWithArangeSorted.time_isin(<class 'numpy.float64'>, 1000)
- 8.98±0.2ms 2.04±0.1ms 0.23 rolling.ExpandingMethods.time_expanding('Series', 'int', 'count')
- 3.55±0.02s 800±3ms 0.23 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 900000)
- 3.56±0.01s 733±4ms 0.21 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 900000)
- 513±1ms 104±0.2ms 0.20 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 1000, 'monotone_hits')
- 99.5±4ms 19.8±0.3ms 0.20 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 70000)
- 165±0.4ms 30.8±0.03ms 0.19 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 1000, -2)
- 140±10ms 25.6±0.2ms 0.18 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 80000)
- 3.14±0.02s 539±4ms 0.17 hash_functions.IsinWithRandomFloat.time_isin(<class 'object'>, 750000)
- 118±0.1ms 19.9±0.04ms 0.17 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 2000, 0)
- 388±0.7ms 64.5±0.8ms 0.17 series_methods.IsInLongSeriesValuesDominate.time_isin('int32', 'monotone')
- 1.89±0s 309±0.3ms 0.16 series_methods.IsInLongSeriesLookUpDominates.time_isin('float64', 1000, 'random_misses')
- 4.28±0.01ms 678±6μs 0.16 index_cached_properties.IndexCache.time_is_unique('CategoricalIndex')
- 3.97±0.1s 600±2ms 0.15 hash_functions.IsinWithRandomFloat.time_isin_outside(<class 'object'>, 750000)
- 1.90±0s 284±0.2ms 0.15 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 1000, 'random_misses')
- 4.57±0.08ms 670±4μs 0.15 indexing.NonNumericSeriesIndexing.time_getitem_list_like('period', 'nonunique_monotonic_inc')
- 465±1ms 59.1±0.2ms 0.13 series_methods.IsInLongSeriesLookUpDominates.time_isin('int64', 1000, 'monotone_hits')
- 184±6ms 23.1±1ms 0.13 hash_functions.UniqueAndFactorizeArange.time_factorize(11)
- 194±10ms 23.2±1ms 0.12 hash_functions.UniqueAndFactorizeArange.time_factorize(8)
- 483±0.6ms 57.1±0.1ms 0.12 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 1000, 'monotone_hits')
- 1.89±0s 187±0.7ms 0.10 series_methods.IsInLongSeriesLookUpDominates.time_isin('float64', 1000, 'random_hits')
- 178±6ms 17.1±2ms 0.10 hash_functions.UniqueAndFactorizeArange.time_unique(11)
- 200±0.1ms 19.0±0.1ms 0.10 hash_functions.IsinWithArange.time_isin(<class 'numpy.float64'>, 1000, 0)
- 588±6ms 54.0±0.5ms 0.09 categoricals.Indexing.time_reindex_missing
- 187±9ms 17.1±2ms 0.09 hash_functions.UniqueAndFactorizeArange.time_unique(8)
- 27.8±3ms 2.50±0.06ms 0.09 frame_methods.Equals.time_frame_float_equal
- 1.90±0s 171±0.3ms 0.09 series_methods.IsInLongSeriesLookUpDominates.time_isin('float32', 1000, 'random_hits')
- 10.6±0.3ms 924±10μs 0.09 frame_methods.Shift.time_shift(1)
- 128±0.8ms 5.47±0.05ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'sum')
- 129±0.7ms 5.49±0.06ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'sum')
- 129±0.9ms 5.45±0.05ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'min')
- 128±0.6ms 5.44±0.04ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'mean')
- 129±0.9ms 5.45±0.02ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'min')
- 129±1ms 5.44±0.03ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'mean')
- 132±1ms 5.54±0.06ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'median')
- 132±0.8ms 5.48±0.03ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'median')
- 129±0.7ms 5.30±0.04ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'max')
- 128±0.8ms 5.27±0.02ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'max')
- 137±0.7ms 5.53±0.02ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'std')
- 137±1ms 5.48±0.05ms 0.04 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'std')
- 182±0.6ms 5.79±0.05ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'median')
- 180±0.9ms 5.71±0.09ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'sum')
- 180±1ms 5.70±0.1ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'sum')
- 1.87±0.02s 59.1±0.5ms 0.03 series_methods.IsInLongSeriesLookUpDominates.time_isin('int64', 1000, 'random_hits')
- 183±0.9ms 5.78±0.05ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'median')
- 180±1ms 5.68±0.04ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'mean')
- 181±1ms 5.68±0.04ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'min')
- 181±1ms 5.66±0.05ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'mean')
- 181±1ms 5.66±0.08ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'max')
- 181±1ms 5.64±0.02ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'max')
- 181±1ms 5.62±0.06ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'min')
- 189±0.7ms 5.83±0.07ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'std')
- 189±0.9ms 5.81±0.07ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'std')
- 1.88±0s 57.4±0.1ms 0.03 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 1000, 'random_hits')
- 1.86±0.06s 54.8±0.1ms 0.03 series_methods.IsInLongSeriesLookUpDominates.time_isin('int64', 1000, 'random_misses')
- 205±2ms 5.76±0.02ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('Series', 'int', 'count')
- 205±2ms 5.74±0.04ms 0.03 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'int', 'count')
- 869±40ms 23.0±1ms 0.03 hash_functions.UniqueAndFactorizeArange.time_factorize(10)
- 84.1±0.5μs 2.05±0.02μs 0.02 period.Indexing.time_unique
- 1.88±0s 42.8±0.1ms 0.02 series_methods.IsInLongSeriesLookUpDominates.time_isin('int32', 1000, 'random_misses')
- 114±0.4ms 2.56±0.5ms 0.02 timeseries.ToDatetimeFromIntsFloats.time_nanosec_float64
- 103±1μs 2.06±0.01μs 0.02 timedelta.TimedeltaIndexing.time_unique
- 862±50ms 17.1±2ms 0.02 hash_functions.UniqueAndFactorizeArange.time_unique(10)
- 348±2ms 6.14±0.05ms 0.02 rolling.ExpandingMethods.time_expanding_groupby('DataFrame', 'float', 'count')
- 347±2ms 6.09±0.02ms 0.02 rolling.ExpandingMethods.time_expanding_groupby('Series', 'float', 'count')
- 2.30±0.1s 36.8±0.7ms 0.02 hash_functions.Float64GroupIndex.time_groupby
- 1.64±0.09s 23.5±1ms 0.01 hash_functions.UniqueAndFactorizeArange.time_factorize(9)
- 171±0.6μs 2.32±0.01μs 0.01 timeseries.DatetimeIndex.time_unique('dst')
- 1.63±0.09s 17.2±2ms 0.01 hash_functions.UniqueAndFactorizeArange.time_unique(9)
- 4.31±0.04s 9.19±0.7ms 0.00 timeseries.ToDatetimeFromIntsFloats.time_sec_float64
- 3.34±0.01ms 3.16±0.02μs 0.00 timeseries.DatetimeIndex.time_unique('tz_naive')
- 3.40±0.03ms 3.15±0.01μs 0.00 timeseries.DatetimeIndex.time_unique('tz_local')
- 3.43±0.03ms 3.13±0.06μs 0.00 timeseries.DatetimeIndex.time_unique('tz_aware')
SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY.
PERFORMANCE DECREASED.