Mailman 3 October 2022 - Pandas-dev

Is it time for a bi-weekly pandas call?
by Marco Gorelli May 13, 2024

May 13, 2024

Currently, there's a monthly pandas call, which has been in place for several years. Seeing as there's now more people working on pandas as part of their jobs, might it be time to increase the frequency? E.g. to meet every 2 weeks, instead of once a month?

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PDEPs: pandas enhancement proposals
by Marc Garcia Nov. 30, 2022

Nov. 30, 2022

We're in the process of implementing PDEPs, equivalent to Python's PEPs and NumPy's NEPs, but for pandas. This should help build the roadmap, make discussions more efficient, obtain more structured feedback from the community, and add visibility to agreed future plans for pandas. The initial implementation (workflow) is a bit simpler than PEP or NEP, but we'll iterate in the future as convenient. You can see the PR for PDEP-1 with the purpose, scope and guidelines here: https://github.com/pandas-dev/pandas/pull/47444 Feedback is very welcome.

6 10

August 2022 monthly community meeting (Wednesday August 10, UTC 18:00)
by Joris Van den Bossche Nov. 8, 2022

Nov. 8, 2022

Hi all, A reminder that the next monthly dev call is tomorrow (Wednesday, August 10) at 18:00 UTC (1pm Central). Our calendar is at https://pandas.pydata.org/docs/development/meeting.html#calendar to check your local time. All are welcome to attend! Video Call: https://us06web.zoom.us/j/84484803210?pwd=TjUxNmcyNHcvcG9SNGJvbE53Y21GZz09 Minutes: https://docs.google.com/document/u/1/d/1tGbTiYORHiSPgVMXawiweGJlBw5dOkVJLY-… Joris

1 3

Proposal to host a PyData Global sprint: call for mentors 📣
by Noa Tamir Oct. 31, 2022

Oct. 31, 2022

Hi folks, We’ve been asked if we’d like to host a pandas sprint at [PyData global](https://pydata.org/global2022/). There’s [an informal guide for the sprint](https://hackmd.io/lkkx0XCcQb2tZd_wO23WYw?view). We can do a short sprint, in one time zone, or a long one crossing timezones (Dec 1st & 2nd) – depending on the availability of maintainers and mentors to participate. I’m happy to coordinate this activity. Please let me know by the end of the week (Sunday 6.11) if you are interested in mentoring the sprint. If we have enough maintainers and mentors in one or two timezones, I'll prepare the sprint registration next week. Cheers, Noa she/they/היא/sie

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ANN: pandas v1.5.1
by Marc Garcia Oct. 20, 2022

Oct. 20, 2022

We are pleased to announce the release of pandas v1.5.1. This is a patch release in the 1.5.x series and includes some regression fixes and bug fixes. We recommend that all users in the 1.5.x series upgrade to this version. See the release notes <https://pandas.pydata.org/docs/whatsnew/v1.5.1.html> for a list of all the changes. The release can be installed from PyPI python -m pip install --upgrade pandas==1.5.1 Or from conda-forge mamba install -c conda-forge pandas==1.5.1 Please report any issues with the release on the pandas issue tracker <https://github.com/pandas-dev/pandas/issues/new/choose>. Thanks to all the contributors <https://pandas.pydata.org/docs/whatsnew/v1.5.1.html#contributors> who made this release possible.

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asv vs 1.4.0
by Brock Mendel Oct. 17, 2022

Oct. 17, 2022

I ran the asv suite (a few times with --record-samples) with main (as of a few days ago) vs 1.4.0. Below are the full results. Emailing bc it won't fit in a GH issue. Some of these have easy explanations. - time_tz_localize_to_utc with utc slowed down bc a fastpath was moved from inside the function to the calling function - TimestampProperties slowed down because of Timestamp.freq deprecation (~10% of all slowed asvs) - OffestDatetimeArithmetic.time_apply* slowed down bc of a DateOffset.apply deprecation Not sure what's going on with select_dtypes (~20% of slowed asvs) or algos.isin. before after ratio [bb1f6515] [56d82a9b] <v1.4.0^0> <main> + 480±7ns 460±20μs 960.13 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1000000, datetime.timezone.utc) + 58.5±0.9μs 20.5±0.4ms 349.36 algos.isin.IsIn.time_isin_mismatched_dtype('bool') + 79.5±2μs 20.6±0.5ms 259.38 algos.isin.IsIn.time_isin_mismatched_dtype('boolean') + 58.4±0.9μs 9.22±0.2ms 157.81 algos.isin.IsIn.time_isin_mismatched_dtype('uint64') + 142±1μs 6.78±0.03ms 47.71 inference.ToNumericDowncast.time_downcast('int32', 'float') + 285±2μs 9.21±0.2ms 32.30 algos.isin.IsIn.time_isin_mismatched_dtype('object') + 2.83±0.03μs 76.4±0.7μs 27.02 categoricals.Contains.time_categorical_index_contains + 36.1±0.9μs 948±30μs 26.26 dtypes.SelectDtypes.time_select_dtype_string_exclude(<class 'int'>) + 36.6±1μs 941±30μs 25.72 dtypes.SelectDtypes.time_select_dtype_string_exclude(<class 'float'>) + 44.5±0.9μs 1.01±0.04ms 22.81 dtypes.SelectDtypes.time_select_dtype_string_exclude(<class 'complex'>) + 44.6±0.9μs 961±40μs 21.52 dtypes.SelectDtypes.time_select_dtype_string_exclude(<class 'bool'>) + 49.1±0.9μs 1.03±0.04ms 21.00 dtypes.SelectDtypes.time_select_dtype_string_exclude('Int16') + 616±30μs 12.9±0.3ms 20.93 inference.ToNumericDowncast.time_downcast('datetime64', 'float') + 48.2±0.6μs 974±40μs 20.19 dtypes.SelectDtypes.time_select_dtype_string_exclude('Int8') + 49.7±0.6μs 973±30μs 19.59 dtypes.SelectDtypes.time_select_dtype_string_exclude('Int32') + 52.1±0.7μs 1.01±0.04ms 19.44 dtypes.SelectDtypes.time_select_dtype_string_exclude('UInt32') + 50.4±0.7μs 969±30μs 19.22 dtypes.SelectDtypes.time_select_dtype_string_exclude('Int64') + 51.0±0.8μs 980±40μs 19.22 dtypes.SelectDtypes.time_select_dtype_string_exclude('UInt8') + 52.8±0.7μs 1.01±0.04ms 19.10 dtypes.SelectDtypes.time_select_dtype_string_exclude('UInt64') + 51.3±0.6μs 976±40μs 19.02 dtypes.SelectDtypes.time_select_dtype_string_exclude('UInt16') + 60.6±0.7μs 1.05±0.04ms 17.38 dtypes.SelectDtypes.time_select_dtype_string_exclude('M8[ns]') + 60.5±0.9μs 1.05±0.04ms 17.36 dtypes.SelectDtypes.time_select_dtype_string_exclude('float32') + 60.5±0.7μs 1.05±0.04ms 17.35 dtypes.SelectDtypes.time_select_dtype_string_exclude('complex128') + 60.6±0.8μs 1.05±0.04ms 17.33 dtypes.SelectDtypes.time_select_dtype_string_exclude('complex64') + 60.5±0.9μs 1.02±0.04ms 16.88 dtypes.SelectDtypes.time_select_dtype_string_exclude('uint16') + 60.4±0.9μs 992±40μs 16.43 dtypes.SelectDtypes.time_select_dtype_string_exclude('uint64') + 60.5±0.7μs 990±40μs 16.35 dtypes.SelectDtypes.time_select_dtype_string_exclude('m8[ns]') + 60.4±0.8μs 987±40μs 16.35 dtypes.SelectDtypes.time_select_dtype_string_exclude('int8') + 60.5±0.7μs 989±40μs 16.35 dtypes.SelectDtypes.time_select_dtype_string_exclude('bool') + 60.7±0.9μs 992±40μs 16.35 dtypes.SelectDtypes.time_select_dtype_string_exclude('int32') + 60.6±0.7μs 990±40μs 16.34 dtypes.SelectDtypes.time_select_dtype_string_exclude('float64') + 60.8±1μs 992±40μs 16.31 dtypes.SelectDtypes.time_select_dtype_string_exclude('int64') + 60.6±0.6μs 987±20μs 16.30 dtypes.SelectDtypes.time_select_dtype_string_exclude('uint32') + 60.6±0.9μs 986±20μs 16.29 dtypes.SelectDtypes.time_select_dtype_string_exclude('uint8') + 60.8±0.9μs 987±40μs 16.24 dtypes.SelectDtypes.time_select_dtype_string_exclude('int16') + 61.2±0.7μs 992±40μs 16.21 dtypes.SelectDtypes.time_select_dtype_string_exclude('timedelta64[ns]') + 61.6±0.7μs 996±40μs 16.17 dtypes.SelectDtypes.time_select_dtype_string_exclude('datetime64[ns]') + 36.0±0.8μs 567±3μs 15.77 dtypes.SelectDtypes.time_select_dtype_int_include(<class 'int'>) + 36.3±0.7μs 569±4μs 15.66 dtypes.SelectDtypes.time_select_dtype_float_include(<class 'float'>) + 36.3±0.6μs 566±4μs 15.60 dtypes.SelectDtypes.time_select_dtype_float_exclude(<class 'int'>) + 36.7±0.7μs 568±5μs 15.48 dtypes.SelectDtypes.time_select_dtype_int_exclude(<class 'float'>) + 44.4±0.8μs 578±4μs 13.02 dtypes.SelectDtypes.time_select_dtype_int_exclude(<class 'bool'>) + 44.4±1μs 577±4μs 13.00 dtypes.SelectDtypes.time_select_dtype_int_exclude(<class 'complex'>) + 44.4±0.7μs 577±3μs 12.99 dtypes.SelectDtypes.time_select_dtype_float_exclude(<class 'bool'>) + 44.5±0.8μs 576±3μs 12.94 dtypes.SelectDtypes.time_select_dtype_float_exclude(<class 'complex'>) + 281±4μs 3.41±0.06ms 12.14 algos.isin.IsIn.time_isin_mismatched_dtype('str') + 48.1±0.8μs 583±4μs 12.11 dtypes.SelectDtypes.time_select_dtype_int_exclude('Int8') + 48.3±0.8μs 583±4μs 12.06 dtypes.SelectDtypes.time_select_dtype_float_exclude('Int8') + 49.0±0.6μs 584±4μs 11.92 dtypes.SelectDtypes.time_select_dtype_int_exclude('Int16') + 49.0±0.9μs 582±3μs 11.88 dtypes.SelectDtypes.time_select_dtype_float_exclude('Int16') + 288±5μs 3.40±0.07ms 11.82 algos.isin.IsIn.time_isin_mismatched_dtype('string[python]') + 49.5±0.7μs 584±4μs 11.80 dtypes.SelectDtypes.time_select_dtype_int_exclude('Int32') + 49.9±0.6μs 585±4μs 11.73 dtypes.SelectDtypes.time_select_dtype_int_include('Int64') + 49.8±0.7μs 584±4μs 11.73 dtypes.SelectDtypes.time_select_dtype_float_exclude('Int32') + 50.2±0.9μs 583±4μs 11.61 dtypes.SelectDtypes.time_select_dtype_float_exclude('Int64') + 50.8±0.8μs 585±4μs 11.51 dtypes.SelectDtypes.time_select_dtype_int_exclude('UInt8') + 50.9±0.9μs 584±4μs 11.47 dtypes.SelectDtypes.time_select_dtype_float_exclude('UInt8') + 51.2±0.7μs 586±4μs 11.44 dtypes.SelectDtypes.time_select_dtype_int_exclude('UInt16') + 51.2±0.6μs 584±4μs 11.40 dtypes.SelectDtypes.time_select_dtype_float_exclude('UInt16') + 52.1±0.7μs 588±3μs 11.28 dtypes.SelectDtypes.time_select_dtype_int_exclude('UInt32') + 52.1±0.7μs 586±4μs 11.25 dtypes.SelectDtypes.time_select_dtype_float_exclude('UInt32') + 22.2±0.3μs 248±20μs 11.17 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') + 52.6±0.7μs 585±5μs 11.13 dtypes.SelectDtypes.time_select_dtype_int_exclude('UInt64') + 52.7±0.8μs 585±4μs 11.12 dtypes.SelectDtypes.time_select_dtype_float_exclude('UInt64') + 22.2±0.3μs 247±4μs 11.11 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc') + 60.4±0.7μs 599±3μs 9.91 dtypes.SelectDtypes.time_select_dtype_int_exclude('bool') + 60.4±0.8μs 597±4μs 9.90 dtypes.SelectDtypes.time_select_dtype_int_include('int64') + 60.5±0.8μs 598±4μs 9.89 dtypes.SelectDtypes.time_select_dtype_int_exclude('int32') + 60.4±0.9μs 597±3μs 9.89 dtypes.SelectDtypes.time_select_dtype_int_exclude('float64') + 60.5±0.7μs 598±5μs 9.89 dtypes.SelectDtypes.time_select_dtype_int_exclude('M8[ns]') + 60.4±0.6μs 597±4μs 9.89 dtypes.SelectDtypes.time_select_dtype_float_exclude('m8[ns]') + 60.5±0.9μs 598±4μs 9.88 dtypes.SelectDtypes.time_select_dtype_int_exclude('uint16') + 60.3±0.7μs 596±4μs 9.87 dtypes.SelectDtypes.time_select_dtype_float_exclude('bool') + 60.4±0.8μs 596±4μs 9.87 dtypes.SelectDtypes.time_select_dtype_float_exclude('uint8') + 60.7±0.8μs 599±4μs 9.87 dtypes.SelectDtypes.time_select_dtype_int_exclude('uint64') + 60.5±0.7μs 597±4μs 9.87 dtypes.SelectDtypes.time_select_dtype_float_exclude('complex64') + 60.3±0.8μs 595±4μs 9.86 dtypes.SelectDtypes.time_select_dtype_float_include('float64') + 60.5±0.9μs 596±4μs 9.86 dtypes.SelectDtypes.time_select_dtype_float_exclude('int64') + 60.5±0.8μs 597±3μs 9.85 dtypes.SelectDtypes.time_select_dtype_int_exclude('complex64') + 60.6±0.9μs 598±5μs 9.85 dtypes.SelectDtypes.time_select_dtype_int_exclude('uint8') + 60.5±0.9μs 596±4μs 9.85 dtypes.SelectDtypes.time_select_dtype_float_exclude('int8') + 60.5±0.8μs 596±4μs 9.85 dtypes.SelectDtypes.time_select_dtype_float_exclude('complex128') + 60.5±0.7μs 596±4μs 9.85 dtypes.SelectDtypes.time_select_dtype_int_exclude('m8[ns]') + 60.7±0.9μs 598±4μs 9.85 dtypes.SelectDtypes.time_select_dtype_int_exclude('float32') + 60.6±0.7μs 596±3μs 9.85 dtypes.SelectDtypes.time_select_dtype_int_exclude('uint32') + 60.6±0.7μs 597±4μs 9.85 dtypes.SelectDtypes.time_select_dtype_int_exclude('int8') + 60.5±0.8μs 595±5μs 9.84 dtypes.SelectDtypes.time_select_dtype_float_exclude('M8[ns]') + 60.6±0.6μs 596±4μs 9.84 dtypes.SelectDtypes.time_select_dtype_float_exclude('int32') + 60.6±0.7μs 596±5μs 9.84 dtypes.SelectDtypes.time_select_dtype_int_exclude('complex128') + 60.5±0.8μs 595±4μs 9.84 dtypes.SelectDtypes.time_select_dtype_float_exclude('uint32') + 60.5±1μs 594±4μs 9.83 dtypes.SelectDtypes.time_select_dtype_float_exclude('float32') + 60.8±0.8μs 597±4μs 9.82 dtypes.SelectDtypes.time_select_dtype_float_exclude('uint64') + 60.7±0.8μs 595±4μs 9.81 dtypes.SelectDtypes.time_select_dtype_float_exclude('int16') + 60.9±0.7μs 597±4μs 9.81 dtypes.SelectDtypes.time_select_dtype_int_exclude('int16') + 60.6±0.8μs 595±5μs 9.81 dtypes.SelectDtypes.time_select_dtype_float_exclude('uint16') + 61.3±0.6μs 598±5μs 9.74 dtypes.SelectDtypes.time_select_dtype_int_exclude('timedelta64[ns]') + 61.2±0.8μs 596±5μs 9.74 dtypes.SelectDtypes.time_select_dtype_float_exclude('timedelta64[ns]') + 61.5±0.9μs 598±4μs 9.72 dtypes.SelectDtypes.time_select_dtype_float_exclude('datetime64[ns]') + 61.7±0.7μs 598±5μs 9.69 dtypes.SelectDtypes.time_select_dtype_int_exclude('datetime64[ns]') + 482±8ns 4.55±0.08μs 9.44 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(10000, datetime.timezone.utc) + 718±30μs 6.12±0.04ms 8.52 frame_methods.ToDict.time_to_dict_ints('list') + 22.3±0.3μs 186±4μs 8.35 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc') + 36.8±0.7μs 298±10μs 8.11 dtypes.SelectDtypes.time_select_dtype_bool_exclude(<class 'float'>) + 2.37±0.01ms 18.7±0.7ms 7.90 ctors.SeriesConstructors.time_series_constructor(<class 'list'>, False, 'int') + 296±5μs 2.33±0.01ms 7.89 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 36.6±0.8μs 284±20μs 7.77 dtypes.SelectDtypes.time_select_dtype_bool_exclude(<class 'int'>) + 2.41±0.01ms 18.5±0.6ms 7.67 ctors.SeriesConstructors.time_series_constructor(<class 'list'>, True, 'int') + 44.3±0.9μs 302±20μs 6.82 dtypes.SelectDtypes.time_select_dtype_bool_include(<class 'bool'>) + 22.1±0.3μs 149±4μs 6.74 indexing.NumericSeriesIndexing.time_getitem_slice(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc') + 44.7±1μs 287±20μs 6.42 dtypes.SelectDtypes.time_select_dtype_bool_exclude(<class 'complex'>) + 49.3±0.8μs 314±20μs 6.36 dtypes.SelectDtypes.time_select_dtype_bool_exclude('Int16') + 37.6±1ms 237±0.5ms 6.30 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 48.5±0.8μs 299±20μs 6.17 dtypes.SelectDtypes.time_select_dtype_bool_exclude('Int8') + 50.1±1μs 308±20μs 6.15 dtypes.SelectDtypes.time_select_dtype_bool_exclude('Int32') + 51.4±0.7μs 314±20μs 6.10 dtypes.SelectDtypes.time_select_dtype_bool_exclude('UInt8') + 51.6±0.9μs 301±20μs 5.83 dtypes.SelectDtypes.time_select_dtype_bool_exclude('UInt16') + 50.7±0.7μs 294±20μs 5.79 dtypes.SelectDtypes.time_select_dtype_bool_exclude('Int64') + 52.4±0.7μs 297±20μs 5.67 dtypes.SelectDtypes.time_select_dtype_bool_exclude('UInt32') + 53.0±0.8μs 296±20μs 5.59 dtypes.SelectDtypes.time_select_dtype_bool_exclude('UInt64') + 61.2±0.8μs 332±10μs 5.43 dtypes.SelectDtypes.time_select_dtype_bool_exclude('uint8') + 780±20ns 4.20±0.05μs 5.38 tslibs.timestamp.TimestampProperties.time_freqstr(tzlocal(), 'B') + 60.9±0.9μs 326±20μs 5.36 dtypes.SelectDtypes.time_select_dtype_bool_exclude('uint16') + 786±20ns 4.20±0.07μs 5.35 tslibs.timestamp.TimestampProperties.time_freqstr(None, 'B') + 788±10ns 4.22±0.04μs 5.35 tslibs.timestamp.TimestampProperties.time_freqstr(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 788±20ns 4.20±0.06μs 5.33 tslibs.timestamp.TimestampProperties.time_freqstr(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 791±20ns 4.21±0.04μs 5.32 tslibs.timestamp.TimestampProperties.time_freqstr(datetime.timezone.utc, 'B') + 61.0±0.9μs 323±20μs 5.30 dtypes.SelectDtypes.time_select_dtype_bool_exclude('int16') + 790±10ns 4.18±0.05μs 5.29 tslibs.timestamp.TimestampProperties.time_freqstr(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 61.0±0.8μs 323±20μs 5.29 dtypes.SelectDtypes.time_select_dtype_bool_exclude('float64') + 60.8±0.7μs 318±20μs 5.24 dtypes.SelectDtypes.time_select_dtype_bool_exclude('uint32') + 60.9±0.8μs 318±20μs 5.22 dtypes.SelectDtypes.time_select_dtype_bool_exclude('float32') + 61.9±0.9μs 321±20μs 5.19 dtypes.SelectDtypes.time_select_dtype_bool_exclude('datetime64[ns]') + 60.7±1μs 315±20μs 5.19 dtypes.SelectDtypes.time_select_dtype_bool_exclude('complex64') + 60.0±0.8μs 311±20μs 5.19 dtypes.SelectDtypes.time_select_dtype_bool_include('bool') + 1.81±0.02ms 9.36±0.2ms 5.17 stat_ops.FrameOps.time_op('skew', 'int', 0) + 60.7±0.8μs 314±20μs 5.17 dtypes.SelectDtypes.time_select_dtype_bool_exclude('M8[ns]') + 60.8±0.6μs 314±20μs 5.16 dtypes.SelectDtypes.time_select_dtype_bool_exclude('m8[ns]') + 61.7±0.8μs 318±20μs 5.15 dtypes.SelectDtypes.time_select_dtype_bool_exclude('timedelta64[ns]') + 1.77±0.01ms 9.12±0.4ms 5.14 stat_ops.FrameOps.time_op('kurt', 'int', 0) + 60.9±0.8μs 313±20μs 5.14 dtypes.SelectDtypes.time_select_dtype_bool_exclude('int64') + 61.0±0.9μs 311±20μs 5.10 dtypes.SelectDtypes.time_select_dtype_bool_exclude('int32') + 61.0±0.7μs 310±20μs 5.09 dtypes.SelectDtypes.time_select_dtype_bool_exclude('uint64') + 60.8±0.9μs 307±20μs 5.05 dtypes.SelectDtypes.time_select_dtype_bool_exclude('complex128') + 60.7±0.9μs 304±20μs 5.01 dtypes.SelectDtypes.time_select_dtype_bool_exclude('int8') + 4.30±0.02ms 21.1±0.2ms 4.90 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f68db67e700>, False, 'int') + 907±8ns 4.42±0.06μs 4.87 tslibs.timestamp.TimestampProperties.time_freqstr(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) + 908±10ns 4.40±0.07μs 4.84 tslibs.timestamp.TimestampProperties.time_freqstr(None, None) + 4.39±0.02ms 21.2±0.2ms 4.83 ctors.SeriesConstructors.time_series_constructor(<function arr_dict at 0x7f68db67e700>, True, 'int') + 912±8ns 4.38±0.04μs 4.81 tslibs.timestamp.TimestampProperties.time_freqstr(tzlocal(), None) + 915±10ns 4.38±0.05μs 4.79 tslibs.timestamp.TimestampProperties.time_freqstr(datetime.timezone(datetime.timedelta(seconds=3600)), None) + 913±8ns 4.37±0.07μs 4.79 tslibs.timestamp.TimestampProperties.time_freqstr(datetime.timezone.utc, None) + 916±10ns 4.38±0.05μs 4.78 tslibs.timestamp.TimestampProperties.time_freqstr(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), None) + 18.8±0.3μs 86.0±2μs 4.57 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 415±6μs 1.74±0.05ms 4.20 stat_ops.FrameOps.time_op('sum', 'int', 0) + 1.22±0.02ms 5.02±0.2ms 4.13 stat_ops.FrameOps.time_op('var', 'int', 0) + 616±7μs 2.53±0.04ms 4.10 stat_ops.FrameOps.time_op('mean', 'int', 0) + 716±4μs 2.93±0.01ms 4.09 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.23±0.02ms 4.98±0.2ms 4.06 stat_ops.FrameOps.time_op('std', 'int', 0) + 1.04±0.02μs 4.12±0.2μs 3.98 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(0, datetime.timezone(datetime.timedelta(seconds=3600))) + 629±10μs 2.49±0.09ms 3.96 stat_ops.FrameOps.time_op('mean', 'int', 1) + 2.41±0.03ms 9.46±0.2ms 3.93 stat_ops.FrameOps.time_op('mad', 'int', 0) + 409±5μs 1.60±0.04ms 3.90 stat_ops.FrameOps.time_op('prod', 'int', 1) + 34.5±0.5μs 133±1μs 3.86 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'nonunique_monotonic_inc') + 360±3μs 1.37±0.01ms 3.80 indexing.NonNumericSeriesIndexing.time_getitem_list_like('string', 'unique_monotonic_inc') + 360±3μs 1.36±0.01ms 3.78 indexing.NonNumericSeriesIndexing.time_getitem_list_like('string', 'non_monotonic') + 19.8±0.3μs 74.6±0.4μs 3.76 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'unique_monotonic_inc') + 79.3±0.6ms 297±0.6ms 3.74 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.16±0.01ms 4.32±0.06ms 3.74 timeseries.TzLocalize.time_infer_dst('US/Eastern') + 20.0±0.2μs 74.5±0.4μs 3.73 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'non_monotonic') + 20.1±0.3μs 74.8±0.4μs 3.72 indexing.NonNumericSeriesIndexing.time_getitem_pos_slice('string', 'nonunique_monotonic_inc') + 9.45±0.04ms 34.6±0.1ms 3.66 timeseries.DatetimeIndex.time_normalize('tz_aware') + 330±4μs 1.21±0ms 3.66 indexing.NonNumericSeriesIndexing.time_getitem_list_like('string', 'nonunique_monotonic_inc') + 5.38±0.1μs 19.6±0.5μs 3.65 timeseries.TzLocalize.time_infer_dst(tzutc()) + 27.8±0.4μs 101±0.5μs 3.63 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'unique_monotonic_inc') + 26.4±0.4μs 95.7±0.5μs 3.62 indexing.NonNumericSeriesIndexing.time_getitem_label_slice('string', 'non_monotonic') + 9.99±0.05ms 35.1±0.1ms 3.51 timeseries.DatetimeAccessor.time_dt_accessor_normalize('US/Eastern') + 21.7±1ms 75.9±2ms 3.49 frame_methods.MaskBool.time_frame_mask_bools + 2.52±0.02ms 8.73±0.02ms 3.47 stat_ops.Correlation.time_corr_wide('pearson') + 6.05±0.1μs 20.9±0.6μs 3.46 timeseries.TzLocalize.time_infer_dst('UTC') + 4.84±0.07μs 16.6±0.6μs 3.43 timeseries.TzLocalize.time_infer_dst(None) + 415±3μs 1.39±0.07ms 3.35 stat_ops.FrameOps.time_op('sum', 'int', 1) + 2.93±0.05ms 9.58±0.3ms 3.27 stat_ops.FrameOps.time_op('mad', 'int', 1) + 1.63±0.02ms 5.26±0.2ms 3.23 stat_ops.FrameOps.time_op('var', 'int', 1) + 22.2±0.2μs 70.2±0.7μs 3.16 arithmetic.Ops2.time_series_dot + 634±4μs 1.95±0.06ms 3.08 stat_ops.FrameOps.time_op('prod', 'int', 0) + 4.17±0.08μs 12.8±0.3μs 3.07 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<Day>) + 1.83±0.02ms 5.45±0.1ms 2.98 stat_ops.FrameOps.time_op('std', 'int', 1) + 109±1μs 294±3μs 2.70 algos.isin.IsIn.time_isin('bool') + 4.25±0.05μs 10.9±0.3μs 2.56 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<Day>) + 134±2μs 327±2μs 2.44 algos.isin.IsIn.time_isin('boolean') + 15.8±0.7μs 37.2±1μs 2.36 series_methods.NanOps.time_func('mean', 1000, 'Int64') + 480±6ns 1.08±0.02μs 2.26 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(100, datetime.timezone.utc) + 4.28±0.1μs 9.61±0.2μs 2.24 index_cached_properties.IndexCache.time_engine('UInt64Index') + 479±9ns 1.07±0.02μs 2.23 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(0, datetime.timezone.utc) + 5.11±0.1μs 11.4±0.2μs 2.22 tslibs.timestamp.TimestampProperties.time_is_quarter_end(tzlocal(), 'B') + 5.04±0.1μs 11.2±0.5μs 2.22 tslibs.timestamp.TimestampProperties.time_is_year_start(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 5.04±0.1μs 11.2±0.3μs 2.22 tslibs.timestamp.TimestampProperties.time_is_quarter_start(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 5.05±0.1μs 11.2±0.5μs 2.21 tslibs.timestamp.TimestampProperties.time_is_year_start(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 5.07±0.1μs 11.2±0.5μs 2.21 tslibs.timestamp.TimestampProperties.time_is_year_start(tzlocal(), 'B') + 5.02±0.1μs 11.1±0.5μs 2.21 tslibs.timestamp.TimestampProperties.time_is_quarter_start(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 481±7ns 1.06±0.03μs 2.21 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1, datetime.timezone.utc) + 5.08±0.09μs 11.2±0.3μs 2.20 tslibs.timestamp.TimestampProperties.time_is_month_start(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 5.07±0.1μs 11.2±0.4μs 2.20 tslibs.timestamp.TimestampProperties.time_is_quarter_end(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 5.04±0.2μs 11.1±0.4μs 2.20 tslibs.timestamp.TimestampProperties.time_is_year_start(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 5.05±0.1μs 11.1±0.3μs 2.20 tslibs.timestamp.TimestampProperties.time_is_month_start(tzlocal(), 'B') + 5.06±0.1μs 11.1±0.4μs 2.20 tslibs.timestamp.TimestampProperties.time_is_month_start(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 5.02±0.09μs 11.0±0.5μs 2.20 tslibs.timestamp.TimestampProperties.time_is_month_start(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 5.10±0.1μs 11.2±0.3μs 2.20 tslibs.timestamp.TimestampProperties.time_is_month_end(tzlocal(), 'B') + 1.04±0.01ms 2.29±0.02ms 2.19 timeseries.DatetimeIndex.time_normalize('repeated') + 3.89±0.1μs 8.53±0.2μs 2.19 index_cached_properties.IndexCache.time_engine('Float64Index') + 5.08±0.1μs 11.1±0.5μs 2.19 tslibs.timestamp.TimestampProperties.time_is_year_end(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 5.07±0.2μs 11.1±0.4μs 2.19 tslibs.timestamp.TimestampProperties.time_is_month_end(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 5.07±0.1μs 11.1±0.4μs 2.19 tslibs.timestamp.TimestampProperties.time_is_month_end(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 5.05±0.1μs 11.0±0.4μs 2.18 tslibs.timestamp.TimestampProperties.time_is_quarter_start(tzlocal(), 'B') + 5.08±0.1μs 11.1±0.5μs 2.18 tslibs.timestamp.TimestampProperties.time_is_month_end(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 1.05±0.02ms 2.30±0.02ms 2.18 timeseries.DatetimeIndex.time_normalize('tz_naive') + 5.07±0.1μs 11.0±0.4μs 2.18 tslibs.timestamp.TimestampProperties.time_is_quarter_end(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 5.07±0.1μs 11.0±0.4μs 2.18 tslibs.timestamp.TimestampProperties.time_is_quarter_start(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 5.06±0.1μs 11.0±0.5μs 2.17 tslibs.timestamp.TimestampProperties.time_is_year_end(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') + 5.09±0.1μs 11.0±0.4μs 2.17 tslibs.timestamp.TimestampProperties.time_is_quarter_end(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') + 5.13±0.07μs 11.1±0.4μs 2.17 tslibs.timestamp.TimestampProperties.time_is_year_end(tzlocal(), 'B') + 5.08±0.1μs 11.0±0.3μs 2.17 tslibs.timestamp.TimestampProperties.time_is_year_end(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') + 4.91±0.1μs 10.6±0.5μs 2.16 tslibs.timestamp.TimestampProperties.time_is_month_end(datetime.timezone.utc, 'B') + 4.87±0.06μs 10.5±0.4μs 2.16 tslibs.timestamp.TimestampProperties.time_is_year_start(datetime.timezone.utc, 'B') + 4.88±0.1μs 10.5±0.3μs 2.15 tslibs.timestamp.TimestampProperties.time_is_month_end(None, 'B') + 4.85±0.1μs 10.4±0.4μs 2.15 tslibs.timestamp.TimestampProperties.time_is_quarter_start(datetime.timezone.utc, 'B') + 17.3±0.5μs 37.1±1μs 2.14 series_methods.NanOps.time_func('mean', 1000, 'boolean') + 4.88±0.1μs 10.4±0.5μs 2.13 tslibs.timestamp.TimestampProperties.time_is_month_start(datetime.timezone.utc, 'B') + 1.24±0.01ms 2.64±0.02ms 2.13 timeseries.DatetimeAccessor.time_dt_accessor_normalize(tzutc()) + 4.91±0.07μs 10.4±0.4μs 2.13 tslibs.timestamp.TimestampProperties.time_is_year_end(None, 'B') + 950±10μs 2.02±0.03ms 2.12 series_methods.NanOps.time_func('mean', 1000000, 'Int64') + 4.92±0.1μs 10.4±0.6μs 2.12 tslibs.timestamp.TimestampProperties.time_is_year_start(None, 'B') + 4.93±0.1μs 10.4±0.4μs 2.12 tslibs.timestamp.TimestampProperties.time_is_quarter_end(None, 'B') + 4.89±0.1μs 10.3±0.4μs 2.12 tslibs.timestamp.TimestampProperties.time_is_month_start(None, 'B') + 4.91±0.1μs 10.4±0.4μs 2.11 tslibs.timestamp.TimestampProperties.time_is_quarter_start(None, 'B') + 1.25±0.01ms 2.64±0.01ms 2.11 timeseries.DatetimeAccessor.time_dt_accessor_normalize('UTC') + 4.92±0.08μs 10.4±0.4μs 2.11 tslibs.timestamp.TimestampProperties.time_is_quarter_end(datetime.timezone.utc, 'B') + 4.92±0.08μs 10.3±0.4μs 2.10 tslibs.timestamp.TimestampProperties.time_is_year_end(datetime.timezone.utc, 'B') + 12.3±0.2μs 25.8±0.3μs 2.09 dtypes.SelectDtypes.time_select_dtype_float_include(<class 'int'>) + 12.2±0.2μs 25.5±0.4μs 2.08 dtypes.SelectDtypes.time_select_dtype_string_include(<class 'int'>) + 12.2±0.2μs 25.4±0.4μs 2.08 dtypes.SelectDtypes.time_select_dtype_float_exclude(<class 'float'>) + 12.4±0.2μs 25.8±0.3μs 2.07 dtypes.SelectDtypes.time_select_dtype_bool_include(<class 'float'>) + 12.3±0.2μs 25.6±0.3μs 2.07 dtypes.SelectDtypes.time_select_dtype_bool_include(<class 'int'>) + 12.5±0.2μs 25.9±0.4μs 2.07 dtypes.SelectDtypes.time_select_dtype_string_include(<class 'float'>) + 12.3±0.2μs 25.4±0.4μs 2.06 dtypes.SelectDtypes.time_select_dtype_int_exclude(<class 'int'>) + 12.5±0.2μs 25.7±0.4μs 2.06 dtypes.SelectDtypes.time_select_dtype_int_include(<class 'float'>) + 1.23±0.01ms 2.54±0.02ms 2.06 timeseries.DatetimeAccessor.time_dt_accessor_normalize(None) + 10.1±0.2μs 20.5±0.5μs 2.03 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessDay>) + 5.66±0.9ms 11.0±0.4ms 1.95 stat_ops.FrameOps.time_op('sem', 'int', 0) + 10.1±0.1μs 19.5±0.5μs 1.93 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BusinessDay>) + 967±10ns 1.86±0.02μs 1.93 array.IntegerArray.time_constructor + 5.17±0.2μs 9.83±0.3μs 1.90 index_cached_properties.IndexCache.time_engine('TimedeltaIndex') + 29.9±3ms 55.7±7ms 1.87 gil.ParallelDatetimeFields.time_datetime_field_normalize + 133±2μs 246±0.6μs 1.85 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.13±0.1ms 2.06±0.2ms 1.83 inference.ToDatetimeFromIntsFloats.time_nanosec_int64 + 18.0±0.3μs 32.8±0.4μs 1.83 dtypes.SelectDtypes.time_select_dtype_string_include(<class 'bool'>) + 18.0±0.4μs 32.9±0.4μs 1.83 dtypes.SelectDtypes.time_select_dtype_float_include(<class 'complex'>) + 4.34±1ms 7.92±0.2ms 1.82 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 18.0±0.3μs 32.9±0.4μs 1.82 dtypes.SelectDtypes.time_select_dtype_float_include(<class 'bool'>) + 18.1±0.3μs 32.8±0.4μs 1.81 dtypes.SelectDtypes.time_select_dtype_int_include(<class 'complex'>) + 18.1±0.3μs 32.8±0.3μs 1.81 dtypes.SelectDtypes.time_select_dtype_string_include(<class 'complex'>) + 1.16±0.1ms 2.11±0.2ms 1.81 inference.ToDatetimeFromIntsFloats.time_nanosec_uint64 + 18.2±0.3μs 32.8±0.4μs 1.80 dtypes.SelectDtypes.time_select_dtype_bool_include(<class 'complex'>) + 18.2±0.3μs 32.6±0.4μs 1.79 dtypes.SelectDtypes.time_select_dtype_int_include(<class 'bool'>) + 18.1±0.3μs 32.4±0.4μs 1.79 dtypes.SelectDtypes.time_select_dtype_bool_exclude(<class 'bool'>) + 21.0±0.3μs 37.5±0.6μs 1.78 dtypes.SelectDtypes.time_select_dtype_float_include('Int8') + 21.3±0.3μs 37.7±0.4μs 1.77 dtypes.SelectDtypes.time_select_dtype_string_include('Int8') + 21.6±0.4μs 38.3±0.5μs 1.77 dtypes.SelectDtypes.time_select_dtype_float_include('Int16') + 21.2±0.3μs 37.5±0.4μs 1.77 dtypes.SelectDtypes.time_select_dtype_int_include('Int8') + 21.6±0.5μs 38.2±0.5μs 1.76 dtypes.SelectDtypes.time_select_dtype_int_include('Int16') + 21.8±0.3μs 38.4±0.4μs 1.76 dtypes.SelectDtypes.time_select_dtype_string_include('Int16') + 21.3±0.3μs 37.1±0.5μs 1.74 dtypes.SelectDtypes.time_select_dtype_bool_include('Int8') + 22.0±0.4μs 38.1±0.4μs 1.73 dtypes.SelectDtypes.time_select_dtype_bool_include('Int16') + 225±6ms 389±2ms 1.73 join_merge.Merge.time_merge_dataframes_cross(False) + 225±7ms 390±4ms 1.73 join_merge.Merge.time_merge_dataframes_cross(True) + 22.4±0.4μs 38.6±0.6μs 1.73 dtypes.SelectDtypes.time_select_dtype_string_include('Int32') + 22.4±0.4μs 38.7±0.6μs 1.73 dtypes.SelectDtypes.time_select_dtype_float_include('Int32') + 22.9±0.5μs 39.4±0.7μs 1.72 dtypes.SelectDtypes.time_select_dtype_float_include('Int64') + 22.6±0.5μs 38.9±0.7μs 1.72 dtypes.SelectDtypes.time_select_dtype_int_include('Int32') + 7.28±0.3ms 12.5±0.3ms 1.71 stat_ops.FrameOps.time_op('kurt', 'int', 1) + 22.9±0.5μs 39.1±0.6μs 1.71 dtypes.SelectDtypes.time_select_dtype_int_exclude('Int64') + 23.0±0.4μs 39.3±0.6μs 1.71 dtypes.SelectDtypes.time_select_dtype_string_include('Int64') + 23.8±0.3μs 40.6±0.7μs 1.71 dtypes.SelectDtypes.time_select_dtype_int_include('UInt16') + 23.8±0.4μs 40.7±0.5μs 1.71 dtypes.SelectDtypes.time_select_dtype_float_include('UInt16') + 1.22±0.2ms 2.08±0.2ms 1.71 inference.ToDatetimeFromIntsFloats.time_nanosec_float64 + 4.84±0.1μs 8.26±0.2μs 1.71 index_cached_properties.IndexCache.time_engine('PeriodIndex') + 6.55±0.2μs 11.2±0.3μs 1.71 index_cached_properties.IndexCache.time_engine('DatetimeIndex') + 23.7±0.4μs 40.5±0.5μs 1.70 dtypes.SelectDtypes.time_select_dtype_string_include('UInt16') + 23.7±0.3μs 40.3±0.4μs 1.70 dtypes.SelectDtypes.time_select_dtype_float_include('UInt8') + 176±2μs 299±2μs 1.70 stat_ops.Correlation.time_corr('pearson') + 23.7±0.4μs 40.2±0.6μs 1.70 dtypes.SelectDtypes.time_select_dtype_string_include('UInt8') + 734±8μs 1.24±0.01ms 1.69 stat_ops.FrameOps.time_op('mean', 'Int64', 0) + 22.7±0.4μs 38.4±0.6μs 1.69 dtypes.SelectDtypes.time_select_dtype_bool_include('Int32') + 23.7±0.5μs 40.0±0.6μs 1.69 dtypes.SelectDtypes.time_select_dtype_int_include('UInt8') + 70.0±0.9μs 118±2μs 1.69 tslibs.timestamp.TimestampOps.time_floor(None) + 24.5±0.4μs 41.3±0.5μs 1.69 dtypes.SelectDtypes.time_select_dtype_float_include('UInt32') + 171±1μs 288±2μs 1.69 algos.isin.IsIn.time_isin_empty('bool') + 23.3±0.3μs 39.4±0.4μs 1.69 dtypes.SelectDtypes.time_select_dtype_bool_include('Int64') + 23.8±0.3μs 40.1±0.6μs 1.69 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt8') + 8.25±0.1ms 13.9±0.4ms 1.68 stat_ops.FrameOps.time_op('skew', 'int', 1) + 24.5±0.3μs 41.1±0.6μs 1.68 dtypes.SelectDtypes.time_select_dtype_string_include('UInt32') + 25.0±0.3μs 41.7±0.5μs 1.67 dtypes.SelectDtypes.time_select_dtype_string_include('UInt64') + 25.1±0.4μs 41.9±0.6μs 1.67 dtypes.SelectDtypes.time_select_dtype_int_include('UInt64') + 24.7±0.4μs 41.2±0.7μs 1.67 dtypes.SelectDtypes.time_select_dtype_int_include('UInt32') + 25.1±0.3μs 41.9±0.5μs 1.67 dtypes.SelectDtypes.time_select_dtype_float_include('UInt64') + 24.2±0.3μs 40.3±0.5μs 1.66 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt16') + 24.7±0.3μs 41.0±0.5μs 1.66 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt32') + 71.4±1μs 119±2μs 1.66 tslibs.timestamp.TimestampOps.time_ceil(None) + 25.4±0.4μs 41.7±0.5μs 1.64 dtypes.SelectDtypes.time_select_dtype_bool_include('UInt64') + 7.88±0.3ms 12.8±0.2ms 1.63 join_merge.Join.time_join_dataframe_index_single_key_small(True) + 3.42±0.07μs 5.57±0.2μs 1.63 tslibs.offsets.OffestDatetimeArithmetic.time_add(<Day>) + 330±2ms 536±3ms 1.62 join_merge.MergeCategoricals.time_merge_object + 79.5±0.7μs 129±2μs 1.62 tslibs.timestamp.TimestampOps.time_floor(datetime.timezone.utc) + 80.5±0.7μs 130±2μs 1.61 tslibs.timestamp.TimestampOps.time_ceil(datetime.timezone.utc) + 199±2μs 321±3μs 1.61 algos.isin.IsIn.time_isin_empty('boolean') + 309±2ms 496±2ms 1.61 join_merge.MergeCategoricals.time_merge_on_cat_col + 10.3±0.1μs 16.0±0.5μs 1.56 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<YearEnd: month=12>) + 4.32±0.1μs 6.71±0.2μs 1.55 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<Day>) + 10.3±0.2μs 16.0±0.7μs 1.55 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<QuarterBegin: startingMonth=3>) + 10.2±0.2μs 15.8±0.7μs 1.55 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<YearBegin: month=1>) + 10.4±0.1μs 16.0±0.5μs 1.55 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BYearEnd: month=12>) + 10.1±0.2μs 15.6±0.5μs 1.55 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<MonthBegin>) + 32.2±0.6μs 49.5±0.6μs 1.54 dtypes.SelectDtypes.time_select_dtype_float_include('complex64') + 32.1±0.5μs 49.5±0.5μs 1.54 dtypes.SelectDtypes.time_select_dtype_int_include('complex128') + 10.3±0.1μs 15.9±0.4μs 1.54 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BYearBegin: month=1>) + 32.2±0.4μs 49.5±0.5μs 1.54 dtypes.SelectDtypes.time_select_dtype_float_include('complex128') + 10.4±0.2μs 16.1±0.5μs 1.54 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<QuarterEnd: startingMonth=3>) + 68.1±0.5μs 105±0.7μs 1.54 categoricals.Concat.time_append_overlapping_index + 32.3±0.3μs 49.6±0.6μs 1.54 dtypes.SelectDtypes.time_select_dtype_string_include('uint16') + 32.2±0.4μs 49.4±0.4μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('complex128') + 33.1±0.5μs 50.8±0.7μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('datetime64[ns]') + 10.4±0.3μs 16.0±0.7μs 1.53 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessQuarterEnd: startingMonth=3>) + 32.3±0.4μs 49.5±0.6μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('uint16') + 32.3±0.4μs 49.6±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('uint32') + 32.3±0.5μs 49.5±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('uint32') + 32.2±0.4μs 49.4±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('int8') + 10.3±0.2μs 15.8±0.5μs 1.53 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<SemiMonthEnd: day_of_month=15>) + 32.4±0.5μs 49.7±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('uint8') + 10.1±0.2μs 15.4±0.5μs 1.53 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<MonthBegin>) + 32.3±0.4μs 49.4±0.6μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('float32') + 32.4±0.5μs 49.6±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('uint64') + 32.2±0.4μs 49.3±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('M8[ns]') + 10.2±0.09μs 15.7±0.5μs 1.53 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessMonthEnd>) + 32.4±0.5μs 49.6±0.6μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('float64') + 32.4±0.4μs 49.6±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('uint64') + 32.4±0.6μs 49.6±0.6μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('float64') + 32.5±0.5μs 49.7±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('int32') + 10.2±0.2μs 15.7±0.3μs 1.53 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<SemiMonthBegin: day_of_month=15>) + 13.3±0.2ms 20.3±0.1ms 1.53 frame_methods.ToDict.time_to_dict_ints('index') + 10.5±0.2μs 16.1±0.6μs 1.53 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessQuarterBegin: startingMonth=3>) + 32.7±0.4μs 50.1±0.6μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('timedelta64[ns]') + 32.3±0.5μs 49.4±0.6μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('bool') + 347±1ms 531±3ms 1.53 join_merge.MergeCategoricals.time_merge_on_cat_idx + 32.4±0.4μs 49.5±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('uint8') + 1.24±0.01ms 1.90±0.02ms 1.53 series_methods.NanOps.time_func('mean', 1000000, 'boolean') + 32.3±0.4μs 49.3±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('complex64') + 32.3±0.5μs 49.3±0.7μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('bool') + 32.7±0.4μs 50.0±0.4μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('uint8') + 32.4±0.5μs 49.4±0.4μs 1.53 dtypes.SelectDtypes.time_select_dtype_float_include('int8') + 32.4±0.5μs 49.4±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('uint16') + 32.5±0.6μs 49.5±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_string_include('m8[ns]') + 32.4±0.5μs 49.3±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('complex64') + 32.5±0.3μs 49.5±0.5μs 1.53 dtypes.SelectDtypes.time_select_dtype_int_include('int8') + 32.5±0.5μs 49.6±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('uint64') + 32.5±0.3μs 49.6±0.7μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_include('int16') + 33.1±0.5μs 50.5±0.4μs 1.52 dtypes.SelectDtypes.time_select_dtype_string_include('datetime64[ns]') + 32.4±0.4μs 49.4±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('M8[ns]') + 32.5±0.4μs 49.5±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_string_include('int32') + 10.4±0.2μs 15.9±0.6μs 1.52 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<QuarterBegin: startingMonth=3>) + 32.4±0.4μs 49.4±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_string_include('M8[ns]') + 32.4±0.4μs 49.3±0.8μs 1.52 dtypes.SelectDtypes.time_select_dtype_string_include('uint32') + 10.2±0.2μs 15.5±0.6μs 1.52 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<MonthEnd>) + 32.3±0.5μs 49.2±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_include('m8[ns]') + 32.3±0.5μs 49.3±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_exclude('int64') + 32.4±0.3μs 49.3±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('m8[ns]') + 10.3±0.1μs 15.7±0.6μs 1.52 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<YearBegin: month=1>) + 32.6±0.4μs 49.6±0.4μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('float32') + 1.04±0.02μs 1.58±0.1μs 1.52 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 32.5±0.3μs 49.5±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('int64') + 32.5±0.4μs 49.4±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_include('int64') + 32.2±0.4μs 49.0±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_exclude('float64') + 32.6±0.4μs 49.5±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('int16') + 32.5±0.4μs 49.3±0.7μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('complex64') + 32.5±0.4μs 49.5±0.7μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_include('float32') + 32.6±0.4μs 49.6±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('uint16') + 32.5±0.4μs 49.4±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('complex128') + 32.4±0.4μs 49.3±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_string_include('int64') + 32.5±0.5μs 49.4±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_include('M8[ns]') + 32.6±0.3μs 49.5±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_include('uint32') + 32.4±0.4μs 49.2±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('bool') + 32.5±0.4μs 49.4±0.4μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('m8[ns]') + 10.4±0.2μs 15.8±0.5μs 1.52 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BYearBegin: month=1>) + 32.5±0.3μs 49.3±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_string_include('int16') + 19.7±0.6μs 29.9±0.8μs 1.52 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<CustomBusinessDay>) + 33.0±0.3μs 50.1±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_float_include('timedelta64[ns]') + 32.2±0.3μs 48.8±0.5μs 1.52 dtypes.SelectDtypes.time_select_dtype_bool_exclude('bool') + 33.4±0.4μs 50.6±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('datetime64[ns]') + 17.9±0.3μs 27.1±0.2μs 1.52 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 32.6±0.6μs 49.5±0.6μs 1.52 dtypes.SelectDtypes.time_select_dtype_int_include('int32') + 10.3±0.1μs 15.5±0.5μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<BusinessMonthBegin>) + 32.8±0.5μs 49.6±0.4μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('uint64') + 10.5±0.2μs 15.8±0.5μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<YearEnd: month=12>) + 32.6±0.3μs 49.4±0.7μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('float32') + 23.8±0.6μs 36.0±0.7μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<DateOffset: days=2, months=2>) + 10.1±0.2μs 15.3±0.5μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<MonthEnd>) + 33.2±0.4μs 50.1±0.6μs 1.51 dtypes.SelectDtypes.time_select_dtype_int_include('timedelta64[ns]') + 32.6±0.4μs 49.3±0.5μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('int8') + 32.7±0.4μs 49.5±0.6μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('int32') + 4.32±0.08μs 6.52±0.2μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<Day>) + 10.5±0.1μs 15.9±0.6μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BusinessQuarterEnd: startingMonth=3>) + 32.8±0.3μs 49.5±0.6μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('uint8') + 33.2±0.4μs 50.1±0.6μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('timedelta64[ns]') + 32.7±0.3μs 49.3±0.7μs 1.51 dtypes.SelectDtypes.time_select_dtype_bool_include('float64') + 10.4±0.2μs 15.7±0.6μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<QuarterEnd: startingMonth=3>) + 10.5±0.2μs 15.9±0.4μs 1.51 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BusinessQuarterBegin: startingMonth=3>) + 24.5±0.6μs 36.8±0.6μs 1.50 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<DateOffset: days=2, months=2>) + 32.8±0.4μs 49.4±0.7μs 1.50 dtypes.SelectDtypes.time_select_dtype_bool_include('int16') + 10.5±0.2μs 15.7±0.6μs 1.50 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BYearEnd: month=12>) + 21.9±0.4μs 32.9±0.2μs 1.50 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(100, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 10.3±0.1μs 15.5±0.3μs 1.50 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BusinessMonthEnd>) + 33.7±0.3μs 50.6±0.6μs 1.50 dtypes.SelectDtypes.time_select_dtype_bool_include('datetime64[ns]') + 10.2±0.1μs 15.3±0.5μs 1.50 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<BusinessMonthBegin>) + 10.4±0.2μs 15.5±0.5μs 1.49 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<SemiMonthEnd: day_of_month=15>) + 8.29±0.1ms 12.4±0.1ms 1.49 indexing.InsertColumns.time_assign_list_like_with_setitem + 10.4±0.2μs 15.5±0.6μs 1.49 tslibs.offsets.OffestDatetimeArithmetic.time_apply_np_dt64(<SemiMonthBegin: day_of_month=15>) + 156±2μs 231±3μs 1.48 algos.isin.IsIn.time_isin_empty('uint64') + 10.8±0.4ms 16.0±0.3ms 1.48 join_merge.Join.time_join_dataframe_index_shuffle_key_bigger_sort(True) + 102±0.9μs 151±2μs 1.48 tslibs.timestamp.TimestampOps.time_floor(datetime.timezone(datetime.timedelta(seconds=3600))) + 102±0.8μs 152±2μs 1.48 tslibs.timestamp.TimestampOps.time_ceil(datetime.timezone(datetime.timedelta(seconds=3600))) + 19.7±0.7μs 29.1±0.9μs 1.48 tslibs.offsets.OffestDatetimeArithmetic.time_apply(<CustomBusinessDay>) + 10.7±0.3ms 15.8±0.3ms 1.47 join_merge.Join.time_join_dataframe_index_single_key_bigger(True) + 18.8±0.08ms 27.6±0.8ms 1.47 index_object.SetOperations.time_operation('monotonic', 'date_string', 'symmetric_difference') + 4.92±0.1μs 7.23±0.2μs 1.47 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<Day>) + 230±4μs 337±4μs 1.46 arithmetic.Ops2.time_frame_series_dot + 9.15±0.4ms 13.3±0.8ms 1.46 arithmetic.AddOverflowArray.time_add_overflow_arr_mask_nan + 9.20±0.4ms 13.3±0.8ms 1.45 arithmetic.AddOverflowArray.time_add_overflow_b_mask_nan + 656±8μs 946±100μs 1.44 stat_ops.SeriesOps.time_op('mad', 'float') + 640±9μs 923±100μs 1.44 stat_ops.SeriesOps.time_op('mad', 'int') + 20.7±0.07ms 29.7±0.2ms 1.44 index_object.SetOperations.time_operation('non_monotonic', 'date_string', 'intersection') + 734±20μs 1.05±0.02ms 1.44 strings.StringArrayConstruction.time_string_array_with_nan_construction + 26.3±0.1ms 37.7±0.6ms 1.43 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 6000) + 3.92±0.02ms 5.56±0.04ms 1.42 series_methods.NanOps.time_func('var', 1000000, 'boolean') + 2.46±0.08ms 3.48±0.03ms 1.42 stat_ops.FrameOps.time_op('mad', 'float', 0) + 271±0.9μs 383±3μs 1.41 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 6000) + 2.35±0.03μs 3.28±0.03μs 1.40 series_methods.SeriesGetattr.time_series_datetimeindex_repr + 755±20μs 1.04±0.04ms 1.37 strings.StringArrayConstruction.time_string_array_construction + 63.8±1μs 87.5±0.9μs 1.37 timedelta.TimedeltaIndexing.time_union + 37.9±0.6ms 51.5±0.4ms 1.36 groupby.GroupByMethods.time_dtype_as_group('int16', 'mad', 'transformation', 1) + 39.0±0.8ms 52.9±0.7ms 1.36 groupby.GroupByMethods.time_dtype_as_field('int16', 'unique', 'direct', 1) + 247±2μs 334±4μs 1.35 algos.isin.IsIn.time_isin('uint64') + 24.4±0.4ms 33.0±0.3ms 1.35 groupby.GroupByMethods.time_dtype_as_field('float', 'mad', 'transformation', 1) + 57.8±0.9ms 78.2±1ms 1.35 groupby.GroupByMethods.time_dtype_as_group('int', 'unique', 'direct', 1) + 56.4±0.8ms 76.2±0.9ms 1.35 groupby.GroupByMethods.time_dtype_as_group('float', 'mad', 'transformation', 1) + 38.9±0.9ms 52.5±0.7ms 1.35 groupby.GroupByMethods.time_dtype_as_field('uint', 'unique', 'direct', 1) + 39.5±0.8ms 53.2±0.6ms 1.35 groupby.GroupByMethods.time_dtype_as_field('float', 'unique', 'direct', 1) + 24.7±0.4ms 33.3±0.4ms 1.35 groupby.GroupByMethods.time_dtype_as_field('uint', 'mad', 'transformation', 1) + 39.2±0.9ms 52.8±0.7ms 1.35 groupby.GroupByMethods.time_dtype_as_field('int', 'unique', 'direct', 1) + 57.8±0.9ms 77.9±1ms 1.35 groupby.GroupByMethods.time_dtype_as_group('uint', 'unique', 'direct', 1) + 36.8±0.6ms 49.5±0.6ms 1.35 groupby.GroupByMethods.time_dtype_as_group('int', 'mad', 'transformation', 1) + 24.7±0.4ms 33.3±0.3ms 1.35 groupby.GroupByMethods.time_dtype_as_field('int', 'mad', 'transformation', 1) + 36.8±0.6ms 49.5±0.5ms 1.35 groupby.GroupByMethods.time_dtype_as_group('uint', 'mad', 'transformation', 1) + 57.3±0.9ms 77.0±1ms 1.34 groupby.GroupByMethods.time_dtype_as_group('int16', 'unique', 'direct', 1) + 24.2±0.4ms 32.5±0.4ms 1.34 groupby.GroupByMethods.time_dtype_as_field('float', 'mad', 'direct', 1) + 25.4±0.4ms 34.1±0.4ms 1.34 groupby.GroupByMethods.time_dtype_as_field('float', 'mad', 'transformation', 5) + 24.8±0.3ms 33.2±0.3ms 1.34 groupby.GroupByMethods.time_dtype_as_field('int16', 'mad', 'transformation', 1) + 984±10μs 1.32±0.02ms 1.34 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'sum') + 11.7±0.5ms 15.7±0.5ms 1.34 stat_ops.FrameOps.time_op('sem', 'int', 1) + 25.7±0.4ms 34.4±0.3ms 1.34 groupby.GroupByMethods.time_dtype_as_field('int', 'mad', 'transformation', 5) + 91.1±2ms 122±2ms 1.34 groupby.GroupByMethods.time_dtype_as_group('float', 'unique', 'direct', 1) + 25.7±0.4ms 34.3±0.3ms 1.33 groupby.GroupByMethods.time_dtype_as_field('int16', 'mad', 'transformation', 5) + 36.7±0.6ms 48.9±0.5ms 1.33 groupby.GroupByMethods.time_dtype_as_group('int', 'mad', 'direct', 1) + 25.1±0.4ms 33.5±0.3ms 1.33 groupby.GroupByMethods.time_dtype_as_field('float', 'mad', 'direct', 5) + 24.5±0.4ms 32.7±0.3ms 1.33 groupby.GroupByMethods.time_dtype_as_field('int16', 'mad', 'direct', 1) + 24.6±0.4ms 32.8±0.3ms 1.33 groupby.GroupByMethods.time_dtype_as_field('int', 'mad', 'direct', 1) + 38.0±0.6ms 50.6±0.4ms 1.33 groupby.GroupByMethods.time_dtype_as_group('int16', 'mad', 'direct', 1) + 56.5±1ms 75.2±0.9ms 1.33 groupby.GroupByMethods.time_dtype_as_group('float', 'mad', 'direct', 1) + 25.8±0.4ms 34.3±0.3ms 1.33 groupby.GroupByMethods.time_dtype_as_field('uint', 'mad', 'transformation', 5) + 930±10μs 1.24±0.02ms 1.33 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'sum') + 36.7±0.6ms 48.8±0.4ms 1.33 groupby.GroupByMethods.time_dtype_as_group('uint', 'mad', 'direct', 1) + 935±10μs 1.24±0.02ms 1.33 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'sum') + 319±4ms 424±3ms 1.33 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'mad') + 24.6±0.4ms 32.7±0.2ms 1.33 groupby.GroupByMethods.time_dtype_as_field('uint', 'mad', 'direct', 1) + 25.4±0.4ms 33.7±0.3ms 1.32 groupby.GroupByMethods.time_dtype_as_field('int16', 'mad', 'direct', 5) + 25.4±0.4ms 33.5±0.3ms 1.32 groupby.GroupByMethods.time_dtype_as_field('uint', 'mad', 'direct', 5) + 1.06±0.01ms 1.41±0.02ms 1.32 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'sum') + 25.4±0.4ms 33.5±0.4ms 1.32 groupby.GroupByMethods.time_dtype_as_field('int', 'mad', 'direct', 5) + 36.8±0.2ms 48.5±0.6ms 1.32 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 7000) + 987±10μs 1.30±0.02ms 1.32 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'sum') + 94.9±1ms 125±2ms 1.32 groupby.GroupByMethods.time_dtype_as_group('datetime', 'unique', 'direct', 1) + 3.88±0.1μs 5.09±0.2μs 1.31 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.08±0.01ms 1.41±0.02ms 1.31 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'sum') + 42.8±0.3ms 56.1±0.4ms 1.31 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 8000) + 18.5±0.6ms 24.3±0.1ms 1.31 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.00±0.01ms 1.31±0.01ms 1.31 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'sum') + 812±3μs 1.06±0ms 1.31 tslibs.resolution.TimeResolution.time_get_resolution('D', 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 9.98±4ms 13.0±1ms 1.31 eval.Eval.time_mult('python', 'all') + 81.3±0.3ms 106±0.3ms 1.30 tslibs.resolution.TimeResolution.time_get_resolution('D', 1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 377±2μs 490±2μs 1.30 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 7000) + 47.0±0.1ms 61.2±0.5ms 1.30 frame_methods.Rename.time_dict_rename_both_axes + 47.1±0.2ms 61.1±0.6ms 1.30 frame_methods.Rename.time_rename_both_axes + 1.01±0.01ms 1.31±0.01ms 1.30 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'sum') + 867±3μs 1.12±0ms 1.30 tslibs.resolution.TimeResolution.time_get_resolution('h', 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 436±1μs 565±3μs 1.30 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 8000) + 86.7±0.3ms 112±0.3ms 1.29 tslibs.resolution.TimeResolution.time_get_resolution('h', 1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 3.95±0.1μs 5.10±0.2μs 1.29 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 86.7±0.4ms 112±0.3ms 1.29 tslibs.resolution.TimeResolution.time_get_resolution('s', 1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 865±3μs 1.12±0ms 1.29 tslibs.resolution.TimeResolution.time_get_resolution('m', 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 868±2μs 1.12±0ms 1.29 tslibs.resolution.TimeResolution.time_get_resolution('s', 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 14.2±0.2ms 18.4±0.2ms 1.29 groupby.Cumulative.time_frame_transform('Float64', 'cummax') + 3.96±0.2μs 5.10±0.2μs 1.29 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 86.7±0.4ms 112±0.3ms 1.29 tslibs.resolution.TimeResolution.time_get_resolution('m', 1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 161±2μs 207±3μs 1.28 tslibs.timestamp.TimestampOps.time_floor(tzlocal()) + 90.4±5ms 116±5ms 1.28 gil.ParallelDatetimeFields.time_period_to_datetime + 9.30±0.4ms 11.9±0.8ms 1.28 arithmetic.AddOverflowArray.time_add_overflow_both_arg_nan + 144±1ms 184±1ms 1.28 series_methods.SeriesConstructor.time_constructor_dict + 163±1μs 208±3μs 1.28 tslibs.timestamp.TimestampOps.time_ceil(tzlocal()) + 1.07±0.02ms 1.36±0.02ms 1.28 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'mean') + 11.3±0.2ms 14.3±0.4ms 1.27 groupby.Cumulative.time_frame_transform_many_nulls('Int64', 'cummin') + 6.42±0.04ms 8.15±0.07ms 1.27 join_merge.Concat.time_concat_small_frames(1) + 1.09±0.01ms 1.38±0.02ms 1.27 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'mean') + 52.2±0.2ms 66.2±0.5ms 1.27 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 9000) + 2.52±0.06ms 3.18±0.2ms 1.26 rolling.Apply.time_rolling('DataFrame', 300, 'int', <function sum at 0x7f68e553ac10>, True) + 11.5±0.2ms 14.5±0.3ms 1.26 groupby.Cumulative.time_frame_transform_many_nulls('Int64', 'cummax') + 23.0±3ms 28.9±3ms 1.26 algos.isin.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.uint64'>, 20, 'outside') + 198±2ms 249±4ms 1.26 frame_methods.Iteration.time_iterrows + 66.3±0.1ms 83.4±0.2ms 1.26 tslibs.resolution.TimeResolution.time_get_resolution('h', 1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.03±0.02μs 1.30±0.06μs 1.26 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 2.49±0.08ms 3.13±0.2ms 1.26 rolling.Apply.time_rolling('Series', 300, 'int', <function sum at 0x7f68e553ac10>, True) + 530±1μs 667±2μs 1.26 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 9000) + 657±1μs 826±3μs 1.26 tslibs.resolution.TimeResolution.time_get_resolution('D', 10000, datetime.timezone.utc) + 65.7±0.1ms 82.5±0.2ms 1.26 tslibs.resolution.TimeResolution.time_get_resolution('D', 1000000, None) + 65.7±0.07ms 82.5±0.2ms 1.26 tslibs.resolution.TimeResolution.time_get_resolution('D', 1000000, datetime.timezone.utc) + 668±2μs 839±3μs 1.26 tslibs.resolution.TimeResolution.time_get_resolution('h', 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 661±2μs 830±4μs 1.26 tslibs.resolution.TimeResolution.time_get_resolution('s', 10000, None) + 67.1±0.1ms 84.2±0.3ms 1.26 tslibs.resolution.TimeResolution.time_get_resolution('D', 1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 66.0±0.1ms 82.9±0.4ms 1.26 tslibs.resolution.TimeResolution.time_get_resolution('s', 1000000, None) + 658±2μs 826±3μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('D', 10000, None) + 66.0±0.1ms 82.8±0.3ms 1.25 tslibs.resolution.TimeResolution.time_get_resolution('s', 1000000, datetime.timezone.utc) + 3.52±0.2ms 4.41±0.2ms 1.25 frame_methods.NSort.time_nlargest_two_columns('first') + 676±1μs 847±3μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('D', 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 21.8±0.4ms 27.4±0.4ms 1.25 groupby.GroupByCythonAgg.time_frame_agg('float64', 'last') + 662±1μs 829±4μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('s', 10000, datetime.timezone.utc) + 32.6±0.6μs 40.8±0.5μs 1.25 boolean.TimeLogicalOps.time_or_scalar + 337±3μs 421±2μs 1.25 frame_methods.Quantile.time_frame_quantile(0) + 67.3±0.1ms 84.2±0.2ms 1.25 tslibs.resolution.TimeResolution.time_get_resolution('s', 1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 33.8±0.6μs 42.3±0.7μs 1.25 boolean.TimeLogicalOps.time_and_scalar + 1.16±0.02ms 1.45±0.02ms 1.25 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'mean') + 678±1μs 847±4μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('s', 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 66.2±0.06ms 82.6±0.3ms 1.25 tslibs.resolution.TimeResolution.time_get_resolution('m', 1000000, None) + 66.2±0.1ms 82.6±0.3ms 1.25 tslibs.resolution.TimeResolution.time_get_resolution('m', 1000000, datetime.timezone.utc) + 665±2μs 831±4μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('h', 10000, datetime.timezone.utc) + 662±1μs 826±2μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('m', 10000, datetime.timezone.utc) + 663±1μs 826±2μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('m', 10000, None) + 66.4±0.08ms 82.7±0.4ms 1.25 tslibs.resolution.TimeResolution.time_get_resolution('h', 1000000, datetime.timezone.utc) + 163±0.7ms 204±5ms 1.25 join_merge.MergeCategoricals.time_merge_cat + 66.4±0.09ms 82.7±0.3ms 1.25 tslibs.resolution.TimeResolution.time_get_resolution('h', 1000000, None) + 665±2μs 828±4μs 1.25 tslibs.resolution.TimeResolution.time_get_resolution('h', 10000, None) + 4.00±0.1μs 4.98±0.3μs 1.24 tslibs.resolution.TimeResolution.time_get_resolution('us', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 67.3±0.1ms 83.7±0.2ms 1.24 tslibs.resolution.TimeResolution.time_get_resolution('m', 1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 17.2±0.2μs 21.4±0.3μs 1.24 boolean.TimeLogicalOps.time_or_array + 679±1μs 843±2μs 1.24 tslibs.resolution.TimeResolution.time_get_resolution('m', 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 33.1±0.3μs 41.0±0.6μs 1.24 boolean.TimeLogicalOps.time_xor_scalar + 17.0±0.1μs 21.1±0.4μs 1.24 boolean.TimeLogicalOps.time_and_array + 14.2±0.3ms 17.7±0.3ms 1.24 groupby.Cumulative.time_frame_transform('Float64', 'cummin') + 4.68±0.2μs 5.81±0.4μs 1.24 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 41.5±0.9ms 51.4±0.6ms 1.24 groupby.GroupByMethods.time_dtype_as_field('object', 'unique', 'direct', 1) + 10.8±0.2μs 13.4±0.3μs 1.24 tslibs.resolution.TimeResolution.time_get_resolution('D', 100, datetime.timezone(datetime.timedelta(seconds=3600))) + 2.56±0.05ms 3.17±0.1ms 1.24 rolling.Apply.time_rolling('DataFrame', 300, 'float', <function sum at 0x7f68e553ac10>, True) + 1.94±0.04ms 2.40±0.05ms 1.24 indexing.NumericSeriesIndexing.time_getitem_list_like(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc') + 4.61±0.2μs 5.69±0.3μs 1.24 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 10.8±0.1μs 13.3±0.3μs 1.24 tslibs.resolution.TimeResolution.time_get_resolution('s', 100, datetime.timezone(datetime.timedelta(seconds=3600))) + 571±1μs 705±4μs 1.24 inference.ToTimedelta.time_convert_int + 10.7±0.1μs 13.2±0.3μs 1.24 tslibs.resolution.TimeResolution.time_get_resolution('h', 100, datetime.timezone(datetime.timedelta(seconds=3600))) + 2.56±0.05ms 3.17±0.1ms 1.23 rolling.Apply.time_rolling('Series', 300, 'float', <function sum at 0x7f68e553ac10>, True) + 11.1±0.7ms 13.7±0.3ms 1.23 groupby.Cumulative.time_frame_transform('int64', 'cummin') + 7.65±0.02μs 9.43±0.04μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('s', 100, datetime.timezone.utc) + 2.37±0.02ms 2.92±0.02ms 1.23 join_merge.Join.time_join_dataframes_cross(False) + 3.89±0.1μs 4.79±0.3μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('us', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.17±0.02ms 1.44±0.02ms 1.23 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'mean') + 10.4±0.1ms 12.8±0.1ms 1.23 indexing.InsertColumns.time_assign_with_setitem + 776±10μs 955±10μs 1.23 rolling.Methods.time_method('Series', ('expanding', {}), 'float', 'sum') + 7.70±0.03μs 9.48±0.06μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('D', 100, None) + 7.65±0.02μs 9.42±0.04μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('m', 100, datetime.timezone.utc) + 7.62±0.03μs 9.37±0.05μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('D', 100, datetime.timezone.utc) + 4.03±0.1μs 4.96±0.3μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('m', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 7.75±0.03μs 9.53±0.05μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('s', 100, None) + 3.50±0.1ms 4.30±0.2ms 1.23 rolling.Apply.time_rolling('DataFrame', 3, 'float', <function sum at 0x7f68e553ac10>, True) + 946±0.9ms 1.16±0s 1.23 join_merge.JoinIndex.time_left_outer_join_index + 4.06±0.1μs 4.99±0.3μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 5.01±0.2μs 6.15±0.4μs 1.23 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 2.45±0.06s 3.00±0.09s 1.23 replace.ReplaceDict.time_replace_series(True) + 1.15±0.01μs 1.41±0.01μs 1.23 attrs_caching.SeriesArrayAttribute.time_extract_array('category') + 16.1±0.2μs 19.7±0.3μs 1.23 boolean.TimeLogicalOps.time_xor_array + 1.14±0.01μs 1.40±0.01μs 1.23 attrs_caching.SeriesArrayAttribute.time_extract_array('object') + 12.9±1ms 15.9±0.4ms 1.23 groupby.Cumulative.time_frame_transform_many_nulls('int64', 'cumsum') + 2.51±0.02ms 3.08±0.02ms 1.23 join_merge.Join.time_join_dataframes_cross(True) + 7.75±0.02μs 9.49±0.05μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('m', 100, None) + 7.69±0.02μs 9.43±0.05μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('h', 100, datetime.timezone.utc) + 4.00±0.2μs 4.90±0.2μs 1.23 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.36±0.02ms 1.66±0.02ms 1.23 join_merge.Merge.time_merge_dataframe_integer_key(False) + 1.15±0.01μs 1.41±0.01μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array_numpy('category') + 39.6±0.5ms 48.5±0.5ms 1.22 stat_ops.SeriesMultiIndexOps.time_op(1, 'mad') + 1.15±0.01μs 1.40±0.02μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array('datetime64') + 3.87±0.1μs 4.74±0.3μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('D', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 3.94±0.09μs 4.82±0.2μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('ns', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 7.78±0.03μs 9.52±0.05μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('h', 100, None) + 40.5±0.7μs 49.5±1μs 1.22 replace.ReplaceList.time_replace_list(True) + 14.8±0.2ms 18.1±0.2ms 1.22 indexing.InsertColumns.time_insert + 12.7±0.6ms 15.5±0.6ms 1.22 groupby.Cumulative.time_frame_transform('float64', 'cummin') + 901±3μs 1.10±0ms 1.22 tslibs.resolution.TimeResolution.time_get_resolution('us', 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 10.8±0.1μs 13.2±0.3μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('m', 100, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.79±0.03ms 2.19±0.04ms 1.22 indexing.NumericSeriesIndexing.time_loc_list_like(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc') + 3.80±0.05ms 4.65±0.3ms 1.22 rolling.Apply.time_rolling('DataFrame', 3, 'float', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 64.4±0.3ms 78.7±0.4ms 1.22 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 10000) + 1.16±0.01μs 1.41±0.01μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array_numpy('numeric') + 1.15±0.01μs 1.41±0.01μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array_numpy('object') + 1.15±0.01μs 1.40±0.01μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array('numeric') + 8.85±0.6ms 10.8±0.3ms 1.22 join_merge.Join.time_join_dataframe_index_single_key_small(False) + 4.07±0.1μs 4.96±0.3μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('D', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.16±0.01μs 1.42±0.01μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array_numpy('datetime64tz') + 833±10μs 1.01±0.01ms 1.22 rolling.Methods.time_method('Series', ('expanding', {}), 'int', 'sum') + 3.43±0.2ms 4.18±0.3ms 1.22 rolling.Apply.time_rolling('Series', 3, 'int', <function sum at 0x7f68e553ac10>, True) + 4.07±0.1μs 4.96±0.3μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('h', 1, datetime.timezone(datetime.timedelta(seconds=3600))) + 90.3±0.4ms 110±0.3ms 1.22 tslibs.resolution.TimeResolution.time_get_resolution('us', 1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 3.93±0.1μs 4.78±0.3μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('m', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 310±5μs 377±6μs 1.22 groupby.GroupByMethods.time_dtype_as_group('object', 'unique', 'direct', 1) + 1.16±0.01μs 1.41±0.01μs 1.22 attrs_caching.SeriesArrayAttribute.time_extract_array('datetime64tz') + 3.96±0.2μs 4.82±0.3μs 1.22 tslibs.resolution.TimeResolution.time_get_resolution('h', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 66.9±0.9ms 81.3±1ms 1.22 groupby.GroupByMethods.time_dtype_as_field('datetime', 'unique', 'direct', 1) + 652±1μs 793±3μs 1.22 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 10000) + 39.6±0.4μs 48.0±0.7μs 1.21 period.DataFramePeriodColumn.time_setitem_period_column + 1.13±0.02ms 1.37±0.02ms 1.21 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'mean') + 2.68±0.07s 3.25±0.09s 1.21 replace.ReplaceDict.time_replace_series(False) + 1.16±0.01μs 1.41±0.01μs 1.21 attrs_caching.SeriesArrayAttribute.time_extract_array_numpy('datetime64') + 64.4±0.3ms 78.0±0.4ms 1.21 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1000000, 11000) + 3.42±0.07ms 4.14±0.1ms 1.21 rolling.Apply.time_rolling('Series', 3, 'float', <function sum at 0x7f68e553ac10>, True) + 3.64±0.2ms 4.41±0.2ms 1.21 frame_methods.NSort.time_nlargest_two_columns('all') + 13.4±0.6ms 16.2±0.6ms 1.21 groupby.Cumulative.time_frame_transform('float64', 'cummax') + 85.6±0.4ms 103±0.2ms 1.21 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1000000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 8.42±0.3ms 10.2±0.3ms 1.21 groupby.GroupByMethods.time_dtype_as_field('float', 'skew', 'direct', 1) + 651±1μs 785±3μs 1.21 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(10000, 11000) + 45.7±0.1ms 55.1±0.5ms 1.21 frame_methods.Rename.time_rename_axis0 + 6.88±0.7ms 8.30±1ms 1.21 series_methods.NanOps.time_func('median', 1000000, 'int32') + 3.64±0.2ms 4.39±0.2ms 1.21 frame_methods.NSort.time_nlargest_two_columns('last') + 14.3±0.3ms 17.3±0.4ms 1.21 groupby.Cumulative.time_frame_transform_many_nulls('Float64', 'cummin') + 3.89±0.1μs 4.68±0.3μs 1.20 tslibs.resolution.TimeResolution.time_get_resolution('s', 0, datetime.timezone(datetime.timedelta(seconds=3600))) + 3.86±0.08ms 4.65±0.2ms 1.20 rolling.Apply.time_rolling('Series', 3, 'int', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 8.19±0.2ms 9.85±0.3ms 1.20 groupby.GroupByMethods.time_dtype_as_field('int', 'skew', 'direct', 1) + 13.6±1ms 16.3±0.4ms 1.20 groupby.Cumulative.time_frame_transform_many_nulls('int64', 'cummin') + 29.2±0.2ms 35.0±0.1ms 1.20 inference.ToNumericDowncast.time_downcast('int-list', 'float') + 860±10μs 1.03±0.01ms 1.20 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'float', 'sum') + 22.4±0.5ms 26.9±0.4ms 1.20 groupby.GroupByCythonAgg.time_frame_agg('float64', 'first') + 858±3μs 1.03±0ms 1.20 tslibs.resolution.TimeResolution.time_get_resolution('ns', 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 2.86±0.05ms 3.42±0.2ms 1.20 rolling.Apply.time_rolling('DataFrame', 300, 'int', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 7.40±0.02ms 8.87±0.05ms 1.20 timeseries.DatetimeIndex.time_timeseries_is_month_start('tz_aware') + 19.2±0.4ms 23.0±0.3ms 1.20 join_merge.Join.time_join_dataframe_index_multi(True) + 10.5±0.2μs 12.6±0.5μs 1.20 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BusinessDay>) + 1.13±0.01ms 1.35±0.02ms 1.20 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'mean') + 2.26±0.03μs 2.71±0.09μs 1.20 tslibs.timestamp.TimestampOps.time_replace_None(datetime.timezone.utc) + 1.21±0.01ms 1.45±0.02ms 1.20 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'mean') + 3.80±0.2ms 4.54±0.4ms 1.20 rolling.Apply.time_rolling('Series', 3, 'float', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 1.60±0.01ms 1.91±0.02ms 1.19 join_merge.Merge.time_merge_dataframe_integer_key(True) + 919±10μs 1.10±0.01ms 1.19 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'int', 'sum') + 7.74±0.03ms 9.22±0.02ms 1.19 timeseries.DatetimeAccessor.time_dt_accessor_year('US/Eastern') + 3.54±0.04ms 4.22±0.3ms 1.19 rolling.Apply.time_rolling('DataFrame', 3, 'int', <function sum at 0x7f68e553ac10>, True) + 1.23±0.02ms 1.47±0.02ms 1.19 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'mean') + 10.3±0.3ms 12.2±0.4ms 1.19 join_merge.Join.time_join_dataframe_index_shuffle_key_bigger_sort(False) + 3.87±0.2ms 4.60±0.3ms 1.19 rolling.Apply.time_rolling('DataFrame', 3, 'int', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 2.83±0.1ms 3.36±0.2ms 1.19 rolling.Apply.time_rolling('Series', 300, 'int', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 42.0±0.4ms 49.9±0.3ms 1.19 groupby.GroupByMethods.time_dtype_as_field('float', 'describe', 'direct', 5) + 11.8±0.2μs 14.0±0.4μs 1.19 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BusinessDay>) + 3.10±0.1ms 3.68±0.3ms 1.19 frame_methods.NSort.time_nsmallest_two_columns('last') + 105±2μs 124±2μs 1.19 groupby.GroupByMethods.time_dtype_as_group('datetime', 'size', 'direct', 1) + 121±2μs 144±3μs 1.18 groupby.GroupByMethods.time_dtype_as_field('uint', 'size', 'direct', 5) + 10.9±0.2μs 12.9±0.3μs 1.18 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BusinessDay>) + 3.12±0.1ms 3.69±0.3ms 1.18 frame_methods.NSort.time_nsmallest_two_columns('all') + 309±2μs 366±2μs 1.18 categoricals.Concat.time_concat_overlapping_index + 103±2μs 122±2μs 1.18 groupby.GroupByMethods.time_dtype_as_group('int', 'size', 'direct', 1) + 42.0±0.5ms 49.7±0.4ms 1.18 groupby.GroupByMethods.time_dtype_as_field('uint', 'describe', 'direct', 5) + 1.15±0.05μs 1.35±0.08μs 1.18 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(0, tzlocal()) + 42.1±0.4ms 49.7±0.4ms 1.18 groupby.GroupByMethods.time_dtype_as_field('int16', 'describe', 'direct', 5) + 42.1±0.4ms 49.7±0.4ms 1.18 groupby.GroupByMethods.time_dtype_as_field('int', 'describe', 'direct', 5) + 101±2μs 120±2μs 1.18 groupby.GroupByMethods.time_dtype_as_field('int', 'size', 'direct', 1) + 102±2μs 120±3μs 1.18 groupby.GroupByMethods.time_dtype_as_field('uint', 'size', 'direct', 1) + 2.87±0.1ms 3.39±0.2ms 1.18 rolling.Apply.time_rolling('DataFrame', 300, 'float', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 122±2μs 144±3μs 1.18 groupby.GroupByMethods.time_dtype_as_field('datetime', 'size', 'direct', 5) + 24.4±0.3ms 28.7±0.5ms 1.18 groupby.GroupByCythonAgg.time_frame_agg('float64', 'prod') + 888±2μs 1.05±0ms 1.18 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 101±2μs 120±2μs 1.18 groupby.GroupByMethods.time_dtype_as_field('float', 'size', 'direct', 1) + 102±1μs 121±2μs 1.18 groupby.GroupByMethods.time_dtype_as_group('uint', 'size', 'direct', 1) + 3.12±0.1ms 3.67±0.3ms 1.18 frame_methods.NSort.time_nsmallest_two_columns('first') + 6.30±0.3ms 7.42±0.6ms 1.18 inference.ToDatetimeFromIntsFloats.time_sec_int64 + 11.1±0.2μs 13.1±0.4μs 1.18 tslibs.resolution.TimeResolution.time_get_resolution('us', 100, datetime.timezone(datetime.timedelta(seconds=3600))) + 103±2μs 121±3μs 1.18 groupby.GroupByMethods.time_dtype_as_group('int16', 'size', 'direct', 1) + 122±2μs 144±3μs 1.18 groupby.GroupByMethods.time_dtype_as_field('int', 'size', 'direct', 5) + 2.05±0.1μs 2.41±0.07μs 1.18 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(0, 11000) + 103±2μs 121±2μs 1.18 groupby.GroupByMethods.time_dtype_as_group('int16', 'size', 'direct', 5) + 391±3μs 459±5μs 1.18 frame_methods.Shift.time_shift(1) + 885±3μs 1.04±0ms 1.18 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 890±3μs 1.04±0ms 1.17 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 103±2μs 121±2μs 1.17 groupby.GroupByMethods.time_dtype_as_group('uint', 'size', 'direct', 5) + 12.4±0.4ms 14.6±0.4ms 1.17 groupby.Cumulative.time_frame_transform_many_nulls('float64', 'cummax') + 2.71±0.04ms 3.18±0.04ms 1.17 stat_ops.FrameOps.time_op('median', 'int', 0) + 2.04±0.1μs 2.39±0.08μs 1.17 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1, 9000) + 882±2μs 1.03±0ms 1.17 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 1011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 2.05±0.1μs 2.40±0.07μs 1.17 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1, 11000) + 104±2μs 122±2μs 1.17 groupby.GroupByMethods.time_dtype_as_group('float', 'size', 'direct', 1) + 883±3μs 1.03±0ms 1.17 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 1000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.28±0.03ms 1.51±0.03ms 1.17 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'float', 'mean') + 9.60±0.2ms 11.2±0.2ms 1.17 groupby.GroupByMethods.time_dtype_as_field('float', 'skew', 'transformation', 5) + 8.63±0.2ms 10.1±0.2ms 1.17 groupby.GroupByMethods.time_dtype_as_field('float', 'skew', 'transformation', 1) + 103±0.9μs 121±2μs 1.17 groupby.GroupByMethods.time_dtype_as_group('float', 'cumsum', 'direct', 5) + 106±2μs 124±2μs 1.17 groupby.GroupByMethods.time_dtype_as_group('datetime', 'size', 'direct', 5) + 102±2μs 119±2μs 1.17 groupby.GroupByMethods.time_dtype_as_field('int16', 'size', 'direct', 1) + 103±2μs 120±2μs 1.17 groupby.GroupByMethods.time_dtype_as_group('int', 'size', 'direct', 5) + 31.5±0.3μs 36.8±0.4μs 1.17 ctors.SeriesConstructors.time_series_constructor(<function no_change at 0x7f68db67e550>, False, 'float') + 10.6±0.4ms 12.4±0.4ms 1.17 join_merge.Join.time_join_dataframe_index_single_key_bigger(False) + 11.8±0.7ms 13.8±0.6ms 1.17 groupby.Cumulative.time_frame_transform_many_nulls('float64', 'cumsum') + 122±2μs 143±3μs 1.17 groupby.GroupByMethods.time_dtype_as_field('float', 'size', 'direct', 5) + 16.0±0.5μs 18.8±0.5μs 1.17 index_cached_properties.IndexCache.time_engine('CategoricalIndex') + 101±0.6μs 118±1μs 1.17 groupby.GroupByMethods.time_dtype_as_group('int', 'cumsum', 'direct', 5) + 30.5±0.2μs 35.6±0.4μs 1.17 ctors.SeriesConstructors.time_series_constructor(<function no_change at 0x7f68db67e550>, False, 'int') + 452±5μs 528±5μs 1.17 frame_methods.Quantile.time_frame_quantile(1) + 1.15±0.02ms 1.34±0.02ms 1.17 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'float', 'sum') + 1.14±0.02ms 1.34±0.02ms 1.17 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'float', 'sum') + 105±2μs 122±3μs 1.17 groupby.GroupByMethods.time_dtype_as_group('float', 'size', 'direct', 5) + 102±2μs 119±2μs 1.17 groupby.GroupByMethods.time_dtype_as_field('datetime', 'size', 'direct', 1) + 99.6±0.7μs 116±1μs 1.17 groupby.GroupByMethods.time_dtype_as_group('uint', 'cumsum', 'direct', 5) + 102±2μs 119±2μs 1.17 groupby.GroupByMethods.time_dtype_as_field('object', 'size', 'direct', 1) + 122±2μs 142±3μs 1.17 groupby.GroupByMethods.time_dtype_as_field('object', 'size', 'direct', 5) + 6.99±0.07ms 8.14±0.2ms 1.17 index_object.IntervalIndexMethod.time_intersection(100000) + 8.18±0.1ms 9.53±0.2ms 1.16 indexing.NumericSeriesIndexing.time_loc_slice(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') + 129±1μs 150±2μs 1.16 tslibs.timestamp.TimestampOps.time_floor(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 102±2μs 119±2μs 1.16 groupby.GroupByMethods.time_dtype_as_group('object', 'size', 'direct', 1) + 7.41±0.04ms 8.62±0.06ms 1.16 join_merge.Concat.time_concat_small_frames(0) + 9.36±0.2ms 10.9±0.2ms 1.16 groupby.GroupByMethods.time_dtype_as_field('int16', 'skew', 'transformation', 5) + 13.9±1ms 16.2±0.4ms 1.16 groupby.Cumulative.time_frame_transform_many_nulls('int64', 'cummax') + 123±2μs 143±2μs 1.16 groupby.GroupByMethods.time_dtype_as_field('int16', 'size', 'direct', 5) + 100.0±0.8μs 116±2μs 1.16 groupby.GroupByMethods.time_dtype_as_group('int16', 'cumsum', 'direct', 5) + 1.10±0.03ms 1.28±0.04ms 1.16 rolling.Methods.time_method('Series', ('expanding', {}), 'int', 'count') + 3.68±0.08ms 4.28±0.1ms 1.16 indexing.NumericSeriesIndexing.time_getitem_array(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc') + 102±2μs 119±2μs 1.16 groupby.GroupByMethods.time_dtype_as_group('object', 'size', 'direct', 5) + 2.06±0.1μs 2.40±0.07μs 1.16 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1, 6000) + 1.46±0.01ms 1.70±0.03ms 1.16 indexing.NumericSeriesIndexing.time_getitem_list_like(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') + 130±1μs 151±2μs 1.16 tslibs.timestamp.TimestampOps.time_ceil(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 2.07±0.1μs 2.41±0.07μs 1.16 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1, 7000) + 12.4±0.5ms 14.4±0.6ms 1.16 groupby.Cumulative.time_frame_transform_many_nulls('float64', 'cummin') + 1.13±0.03ms 1.31±0.04ms 1.16 rolling.Methods.time_method('Series', ('expanding', {}), 'float', 'count') + 8.75±0.2ms 10.2±0.2ms 1.16 groupby.GroupByMethods.time_dtype_as_field('float', 'skew', 'direct', 5) + 699±2μs 811±4μs 1.16 tslibs.resolution.TimeResolution.time_get_resolution('us', 10000, datetime.timezone.utc) + 10.7±0.1μs 12.4±0.3μs 1.16 tslibs.resolution.TimeResolution.time_get_resolution('ns', 100, datetime.timezone(datetime.timedelta(seconds=3600))) + 8.45±0.1ms 9.80±0.1ms 1.16 groupby.GroupByMethods.time_dtype_as_field('int', 'skew', 'direct', 5) + 997±2μs 1.16±0ms 1.16 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 8.48±0.2ms 9.82±0.1ms 1.16 groupby.GroupByMethods.time_dtype_as_field('int16', 'skew', 'direct', 5) + 1.28±0.02ms 1.49±0.02ms 1.16 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'int', 'sum') + 4.16±0.1ms 4.82±0.1ms 1.16 frame_methods.Fillna.time_frame_fillna(True, 'bfill', 'Int64') + 69.9±0.07ms 80.9±0.3ms 1.16 tslibs.resolution.TimeResolution.time_get_resolution('us', 1000000, None) + 1.05±0.05ms 1.21±0.04ms 1.16 algorithms.Quantile.time_quantile(0, 'higher', 'int') + 69.9±0.08ms 80.9±0.3ms 1.16 tslibs.resolution.TimeResolution.time_get_resolution('us', 1000000, datetime.timezone.utc) + 699±2μs 809±3μs 1.16 tslibs.resolution.TimeResolution.time_get_resolution('us', 10000, None) + 1.23±0.02ms 1.42±0.02ms 1.16 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'float', 'sum') + 995±2μs 1.15±0ms 1.16 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 6000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 74.9±2μs 86.7±0.8μs 1.16 reindex.DropDuplicates.time_series_drop_dups_int(True) + 1.01±0ms 1.16±0ms 1.16 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 9000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.01±0ms 1.16±0ms 1.16 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 11000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 22.3±0.5ms 25.8±0.6ms 1.16 rolling.Pairwise.time_groupby(({}, 'expanding'), 'cov', False) + 906±20μs 1.05±0.01ms 1.16 rolling.Methods.time_method('Series', ('expanding', {}), 'int', 'mean') + 717±1μs 828±3μs 1.16 tslibs.resolution.TimeResolution.time_get_resolution('us', 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 71.2±0.1ms 82.2±0.2ms 1.16 tslibs.resolution.TimeResolution.time_get_resolution('us', 1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 998±2μs 1.15±0ms 1.16 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 8000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 8.01±0.6ms 9.25±0.5ms 1.15 algorithms.Duplicated.time_duplicated(False, 'last', 'float') + 8.48±0.2ms 9.79±0.1ms 1.15 groupby.GroupByMethods.time_dtype_as_field('uint', 'skew', 'direct', 5) + 9.42±0.2ms 10.9±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_field('uint', 'skew', 'transformation', 5) + 1.19±0.04ms 1.38±0.04ms 1.15 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'int', 'count') + 1.02±0ms 1.18±0ms 1.15 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 12000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.23±0.02ms 1.42±0.02ms 1.15 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'int', 'sum') + 2.07±0.1μs 2.39±0.06μs 1.15 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(0, 9000) + 1.02±0ms 1.17±0ms 1.15 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 9.34±0.1μs 10.8±0.2μs 1.15 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BusinessDay>) + 9.43±0.2ms 10.9±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_field('int', 'skew', 'transformation', 5) + 130±0.9μs 150±2μs 1.15 tslibs.timestamp.TimestampOps.time_floor(tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 110±1μs 127±1μs 1.15 timeseries.DatetimeIndex.time_normalize('dst') + 751±3μs 864±3μs 1.15 tslibs.resolution.TimeResolution.time_get_resolution('D', 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 1.22±0.04ms 1.40±0.04ms 1.15 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'float', 'count') + 2.07±0.1μs 2.38±0.08μs 1.15 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(0, 8000) + 23.6±0.5ms 27.2±0.7ms 1.15 rolling.Pairwise.time_groupby(({'window': 1000}, 'rolling'), 'corr', False) + 1.02±0ms 1.17±0ms 1.15 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 4000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.02±0ms 1.17±0ms 1.15 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 4006, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.29±0.02ms 1.49±0.02ms 1.15 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'int', 'sum') + 2.08±0.1μs 2.39±0.09μs 1.15 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1, 8000) + 938±7μs 1.08±0.01ms 1.15 groupby.FillNA.time_df_ffill + 3.68±0.5ms 4.23±0.4ms 1.15 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'int', 'sem') + 132±1μs 151±2μs 1.15 tslibs.timestamp.TimestampOps.time_ceil(tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 2.10±0.08μs 2.41±0.07μs 1.15 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(0, 7000) + 8.17±0.2ms 9.38±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_field('int16', 'skew', 'direct', 1) + 74.3±0.3ms 85.4±0.3ms 1.15 tslibs.resolution.TimeResolution.time_get_resolution('h', 1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 75.0±0.4ms 86.2±0.3ms 1.15 tslibs.resolution.TimeResolution.time_get_resolution('D', 1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 8.17±0.2ms 9.38±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_field('uint', 'skew', 'direct', 1) + 745±3μs 855±3μs 1.15 tslibs.resolution.TimeResolution.time_get_resolution('h', 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 1.47±0.06ms 1.69±0.06ms 1.15 frame_methods.Fillna.time_frame_fillna(True, 'bfill', 'datetime64[ns]') + 12.4±0.2ms 14.2±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_group('int', 'skew', 'transformation', 1) + 8.05±0.04μs 9.23±0.04μs 1.15 tslibs.resolution.TimeResolution.time_get_resolution('us', 100, datetime.timezone.utc) + 15.2±0.2ms 17.4±0.4ms 1.15 groupby.Cumulative.time_frame_transform_many_nulls('Float64', 'cummax') + 8.45±0.2ms 9.69±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_field('int', 'skew', 'transformation', 1) + 2.92±0.08ms 3.35±0.2ms 1.15 rolling.Apply.time_rolling('Series', 300, 'float', <function Apply.<lambda> at 0x7f68d77f9280>, True) + 12.4±0.4ms 14.2±0.4ms 1.15 groupby.GroupByMethods.time_dtype_as_group('int', 'skew', 'direct', 1) + 8.15±0.05μs 9.34±0.05μs 1.15 tslibs.resolution.TimeResolution.time_get_resolution('us', 100, None) + 91.3±0.5ms 105±0.3ms 1.15 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 8.40±0.2ms 9.62±0.1ms 1.15 groupby.GroupByMethods.time_dtype_as_field('uint', 'skew', 'transformation', 1) + 12.8±0.2ms 14.7±0.2ms 1.15 groupby.GroupByMethods.time_dtype_as_group('int16', 'skew', 'transformation', 1) + 3.70±0.03μs 4.24±0.05μs 1.14 dtypes.Dtypes.time_pandas_dtype('Int8') + 2.06±0.1μs 2.35±0.1μs 1.14 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(0, 6000) + 75.4±0.4ms 86.2±0.4ms 1.14 tslibs.resolution.TimeResolution.time_get_resolution('s', 1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 947±20μs 1.08±0.01ms 1.14 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'float', 'mean') + 65.3±0.1ms 74.6±0.3ms 1.14 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1000000, None) + 65.3±0.2ms 74.6±0.3ms 1.14 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1000000, datetime.timezone.utc) + 757±4μs 864±4μs 1.14 tslibs.resolution.TimeResolution.time_get_resolution('s', 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 2.11±0.1μs 2.41±0.07μs 1.14 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(1, 10000) + 47.8±1μs 54.5±0.6μs 1.14 timedelta.TimedeltaIndexing.time_intersection + 651±2μs 742±3μs 1.14 tslibs.resolution.TimeResolution.time_get_resolution('ns', 10000, None) + 8.45±0.2ms 9.64±0.1ms 1.14 groupby.GroupByMethods.time_dtype_as_field('int16', 'skew', 'transformation', 1) + 1.08±0ms 1.23±0ms 1.14 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(10000, 5000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 993±20μs 1.13±0.01ms 1.14 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'int', 'mean') + 651±2μs 742±3μs 1.14 tslibs.resolution.TimeResolution.time_get_resolution('ns', 10000, datetime.timezone.utc) + 12.9±0.4ms 14.7±0.4ms 1.14 groupby.GroupByMethods.time_dtype_as_group('int16', 'skew', 'direct', 1) + 754±2μs 860±4μs 1.14 tslibs.resolution.TimeResolution.time_get_resolution('m', 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 91.1±0.6ms 104±0.2ms 1.14 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 12.4±0.2ms 14.1±0.2ms 1.14 groupby.GroupByMethods.time_dtype_as_group('uint', 'skew', 'transformation', 1) + 23.8±0.4ms 27.1±0.3ms 1.14 rolling.Pairwise.time_groupby(({'window': 10}, 'rolling'), 'corr', False) + 91.6±0.6ms 104±0.3ms 1.14 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 12.4±0.3ms 14.1±0.4ms 1.14 groupby.GroupByMethods.time_dtype_as_group('uint', 'skew', 'direct', 1) + 1.23±0.02ms 1.40±0.02ms 1.14 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'int', 'sum') + 22.7±0.5ms 25.8±0.7ms 1.14 rolling.Pairwise.time_groupby(({}, 'expanding'), 'corr', False) + 23.4±0.5ms 26.7±0.3ms 1.14 rolling.Pairwise.time_groupby(({'window': 1000}, 'rolling'), 'cov', False) + 668±1μs 760±3μs 1.14 tslibs.resolution.TimeResolution.time_get_resolution('ns', 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 90.8±0.7ms 103±0.3ms 1.14 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 1011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 90.9±0.7ms 103±0.4ms 1.14 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 1000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 75.6±0.4ms 85.8±0.3ms 1.14 tslibs.resolution.TimeResolution.time_get_resolution('m', 1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) + 66.6±0.1ms 75.7±0.3ms 1.14 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1000000, datetime.timezone(datetime.timedelta(seconds=3600))) + 23.5±0.5ms 26.7±0.6ms 1.14 rolling.Pairwise.time_groupby(({'window': 10}, 'rolling'), 'cov', False) + 17.6±0.2μs 19.9±0.2μs 1.13 ctors.SeriesDtypesConstructors.time_dtindex_from_series + 26.2±0.6ms 29.7±0.3ms 1.13 groupby.TransformEngine.time_series_cython(False) + 18.9±0.5ms 21.4±0.3ms 1.13 groupby.GroupByMethods.time_dtype_as_group('float', 'skew', 'direct', 1) + 26.3±0.5ms 29.8±0.3ms 1.13 groupby.TransformEngine.time_series_cython(True) + 19.0±0.4ms 21.5±0.2ms 1.13 groupby.GroupByMethods.time_dtype_as_group('float', 'skew', 'transformation', 1) + 20.1±0.3ms 22.8±0.2ms 1.13 groupby.GroupByMethods.time_dtype_as_field('int16', 'describe', 'direct', 1) + 14.9±1ms 16.8±0.9ms 1.13 algorithms.Factorize.time_factorize(False, True, 'datetime64[ns, tz]') + 2.11±0.08μs 2.39±0.08μs 1.13 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(0, 10000) + 1.31±0.01ms 1.48±0.02ms 1.13 rolling.Methods.time_method('Series', ('expanding', {}), 'float', 'std') + 20.1±0.2ms 22.7±0.2ms 1.13 groupby.GroupByMethods.time_dtype_as_field('int', 'describe', 'direct', 1) + 20.3±0.2ms 22.9±0.2ms 1.13 groupby.GroupByMethods.time_dtype_as_field('float', 'describe', 'direct', 1) + 5.02±0.4ms 5.67±1ms 1.13 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('add') + 4.06±0.1μs 4.59±0.3μs 1.13 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, datetime.timezone(datetime.timedelta(seconds=3600))) + 2.45±0.1ms 2.76±0.08ms 1.13 groupby.GroupManyLabels.time_sum(1000) + 30.2±0.4ms 34.1±0.3ms 1.13 groupby.GroupByMethods.time_dtype_as_group('int16', 'describe', 'direct', 1) + 94.6±0.9μs 107±1μs 1.13 groupby.GroupByMethods.time_dtype_as_field('float', 'cumprod', 'direct', 5) + 7.54±0.02μs 8.51±0.03μs 1.13 tslibs.resolution.TimeResolution.time_get_resolution('ns', 100, datetime.timezone.utc) + 872±20μs 984±10μs 1.13 rolling.Methods.time_method('Series', ('expanding', {}), 'float', 'mean') + 4.66±0.03μs 5.25±0.08μs 1.13 dtypes.Dtypes.time_pandas_dtype('Int32') + 20.2±0.3ms 22.7±0.2ms 1.13 groupby.GroupByMethods.time_dtype_as_field('uint', 'describe', 'direct', 1) + 126±3μs 142±4μs 1.13 groupby.GroupByMethods.time_dtype_as_group('object', 'head', 'direct', 5) + 34.7±0.4ms 39.2±0.4ms 1.13 groupby.GroupByMethods.time_dtype_as_group('uint', 'describe', 'direct', 1) + 1.37±0.02ms 1.55±0.03ms 1.13 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'float', 'mean') + 133±2ms 150±2ms 1.13 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'skew') + 102±0.5ms 115±0.3ms 1.13 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 103±0.3ms 116±0.2ms 1.13 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 9000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 104±0.8μs 117±1μs 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'cummax', 'direct', 5) + 7.64±0.02μs 8.60±0.04μs 1.13 tslibs.resolution.TimeResolution.time_get_resolution('ns', 100, None) + 4.17±0.03μs 4.69±0.05μs 1.13 dtypes.Dtypes.time_pandas_dtype('Int16') + 102±0.5ms 115±0.2ms 1.13 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 6000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 34.7±0.5ms 39.1±0.3ms 1.13 groupby.GroupByMethods.time_dtype_as_group('int', 'describe', 'direct', 1) + 469±5μs 528±4μs 1.13 groupby.Datelike.time_sum('date_range') + 286±2μs 322±2μs 1.12 groupby.GroupByMethods.time_dtype_as_group('int', 'median', 'direct', 5) + 102±0.6ms 115±0.2ms 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 8000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 105±0.6ms 118±0.3ms 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 12000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 85.9±0.8μs 96.6±1μs 1.12 groupby.GroupByMethods.time_dtype_as_field('float', 'cumprod', 'direct', 1) + 1.52±0.01ms 1.71±0.01ms 1.12 rolling.VariableWindowMethods.time_method('Series', '50s', 'int', 'sum') + 1.34±0.02ms 1.50±0.02ms 1.12 indexing.NumericSeriesIndexing.time_loc_list_like(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') + 4.04±0.2μs 4.54±0.2μs 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, datetime.timezone(datetime.timedelta(seconds=3600))) + 2.80±0.01ms 3.14±0.01ms 1.12 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'float', 'kurt') + 104±0.3ms 117±0.2ms 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 103±0.5ms 116±0.2ms 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 11000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.26±0.02ms 1.41±0.02ms 1.12 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'float', 'sum') + 8.19±0.5ms 9.20±0.5ms 1.12 algorithms.Duplicated.time_duplicated(False, 'first', 'float') + 2.88±0.01ms 3.24±0.02ms 1.12 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'float', 'kurt') + 1.37±0.03ms 1.54±0.03ms 1.12 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'float', 'mean') + 183±3μs 205±2μs 1.12 arithmetic.OffsetArrayArithmetic.time_add_series_offset(<Day>) + 70.7±1μs 79.3±1μs 1.12 indexing.DataFrameNumericIndexing.time_iloc_dups(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc') + 1.53±0.01ms 1.72±0.01ms 1.12 rolling.VariableWindowMethods.time_method('DataFrame', '50s', 'float', 'sum') + 950±5μs 1.07±0.01ms 1.12 groupby.FillNA.time_df_bfill + 71.0±1μs 79.6±1μs 1.12 indexing.DataFrameNumericIndexing.time_iloc_dups(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc') + 10.8±0.2μs 12.1±0.2μs 1.12 array.BooleanArray.time_from_bool_array + 1.44±0.01ms 1.62±0.01ms 1.12 rolling.VariableWindowMethods.time_method('Series', '1d', 'float', 'sum') + 1.50±0.01ms 1.68±0.01ms 1.12 rolling.VariableWindowMethods.time_method('Series', '1d', 'int', 'sum') + 70.7±1μs 79.3±2μs 1.12 indexing.DataFrameNumericIndexing.time_iloc_dups(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') + 1.23±0.01ms 1.37±0.01ms 1.12 rolling.ForwardWindowMethods.time_rolling('Series', 10, 'int', 'min') + 104±0.6μs 116±0.8μs 1.12 groupby.GroupByMethods.time_dtype_as_group('int16', 'cummax', 'direct', 5) + 45.4±1ms 50.9±2ms 1.12 gil.ParallelGroupbyMethods.time_parallel(8, 'last') + 103±0.9μs 115±1μs 1.12 groupby.GroupByMethods.time_dtype_as_group('uint', 'cummax', 'direct', 5) + 4.06±0.2μs 4.55±0.3μs 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 12000, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.39±0.02ms 1.56±0.02ms 1.12 rolling.Methods.time_method('Series', ('expanding', {}), 'int', 'std') + 2.35±0.07ms 2.63±0.06ms 1.12 timeseries.ResampleSeries.time_resample('period', '5min', 'ohlc') + 6.33±0.2μs 7.09±0.4μs 1.12 tslibs.timestamp.TimestampOps.time_replace_None(datetime.timezone(datetime.timedelta(seconds=3600))) + 104±0.4ms 117±0.2ms 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 4006, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 207±2μs 232±1μs 1.12 groupby.GroupByMethods.time_dtype_as_group('int', 'mean', 'direct', 5) + 1.45±0.01ms 1.62±0.01ms 1.12 rolling.VariableWindowMethods.time_method('Series', '50s', 'float', 'sum') + 1.30±0.03ms 1.46±0.02ms 1.12 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'float', 'mean') + 4.02±0.2μs 4.50±0.2μs 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, datetime.timezone(datetime.timedelta(seconds=3600))) + 104±0.4ms 117±0.3ms 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 4000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 1.59±0.01ms 1.78±0.01ms 1.12 rolling.VariableWindowMethods.time_method('DataFrame', '50s', 'int', 'sum') + 45.0±0.6ms 50.4±0.5ms 1.12 groupby.GroupByMethods.time_dtype_as_group('float', 'describe', 'direct', 1) + 270±3ms 302±3ms 1.12 groupby.GroupByMethods.time_dtype_as_group('float', 'describe', 'direct', 5) + 1.86±0.07ms 2.07±0.1ms 1.12 indexing.NumericSeriesIndexing.time_getitem_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc') + 2.99±0.07ms 3.34±0.07ms 1.12 timeseries.ResampleSeries.time_resample('datetime', '5min', 'mean') + 86.5±0.3μs 96.8±0.3μs 1.12 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(10000, 'days') + 204±3ms 228±2ms 1.12 groupby.GroupByMethods.time_dtype_as_group('int', 'describe', 'direct', 5) + 1.36±0.03ms 1.52±0.02ms 1.12 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'int', 'mean') + 1.45±0.03ms 1.62±0.03ms 1.12 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'int', 'mean') + 2.21±0.01ms 2.47±0.02ms 1.12 series_methods.Map.time_map('dict', 'object') + 1.77±0.08ms 1.98±0.07ms 1.12 indexing.NumericSeriesIndexing.time_loc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc') + 177±2ms 197±2ms 1.12 groupby.GroupByMethods.time_dtype_as_group('int16', 'describe', 'direct', 5) + 4.04±0.08μs 4.51±0.2μs 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 4.05±0.2μs 4.52±0.3μs 1.12 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, datetime.timezone(datetime.timedelta(seconds=3600))) + 204±3ms 227±2ms 1.12 groupby.GroupByMethods.time_dtype_as_group('uint', 'describe', 'direct', 5) + 14.1±0.07ms 15.8±0.09ms 1.12 join_merge.MergeAsof.time_on_int32('nearest', None) + 1.24±0.01ms 1.38±0.01ms 1.12 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'int', 'min') + 3.36±0.4ms 3.75±0.4ms 1.12 rolling.Methods.time_method('Series', ('expanding', {}), 'float', 'sem') + 1.52±0.01ms 1.69±0.01ms 1.12 rolling.VariableWindowMethods.time_method('Series', '1h', 'int', 'sum') + 1.60±0.01ms 1.79±0.01ms 1.11 rolling.VariableWindowMethods.time_method('DataFrame', '1h', 'int', 'sum') + 1.58±0.01ms 1.76±0.01ms 1.11 rolling.VariableWindowMethods.time_method('DataFrame', '1d', 'int', 'sum') + 47.0±2ms 52.3±2ms 1.11 gil.ParallelGroupbyMethods.time_parallel(8, 'var') + 1.54±0.01ms 1.71±0.01ms 1.11 rolling.VariableWindowMethods.time_method('DataFrame', '1h', 'float', 'sum') + 4.05±0.1μs 4.51±0.2μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, datetime.timezone(datetime.timedelta(seconds=3600))) + 70.9±2μs 79.0±2μs 1.11 indexing.DataFrameNumericIndexing.time_iloc_dups(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc') + 8.52±0.06ms 9.49±0.05ms 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(1000000, 'days') + 1.32±0.01ms 1.47±0.01ms 1.11 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'int', 'min') + 350±4μs 390±3μs 1.11 reindex.Reindex.time_reindex_columns + 4.09±0.1μs 4.55±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, datetime.timezone(datetime.timedelta(seconds=3600))) + 4.07±0.1μs 4.54±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, datetime.timezone(datetime.timedelta(seconds=3600))) + 86.6±0.3μs 96.4±0.2μs 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(10000, 'microseconds') + 1.85±0.01ms 2.06±0.01ms 1.11 series_methods.Map.time_map('Series', 'object') + 4.07±0.1μs 4.53±0.2μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, datetime.timezone(datetime.timedelta(seconds=3600))) + 115±2μs 128±2μs 1.11 groupby.GroupByMethods.time_dtype_as_group('object', 'first', 'direct', 1) + 1.09±0.05ms 1.21±0.04ms 1.11 algorithms.Quantile.time_quantile(0, 'lower', 'int') + 2.90±0.01ms 3.23±0.02ms 1.11 rolling.ForwardWindowMethods.time_rolling('DataFrame', 1000, 'float', 'kurt') + 1.46±0.01ms 1.62±0.01ms 1.11 rolling.VariableWindowMethods.time_method('Series', '1h', 'float', 'sum') + 24.7±0.3μs 27.5±0.4μs 1.11 ctors.SeriesDtypesConstructors.time_dtindex_from_index_with_series + 203±2μs 225±2μs 1.11 groupby.GroupByMethods.time_dtype_as_group('int', 'var', 'direct', 5) + 86.7±0.3μs 96.4±0.3μs 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(10000, 'seconds') + 4.03±0.1μs 4.48±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, datetime.timezone(datetime.timedelta(seconds=3600))) + 8.52±0.05ms 9.47±0.05ms 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(1000000, 'seconds') + 4.07±0.1μs 4.52±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, datetime.timezone(datetime.timedelta(seconds=3600))) + 70.7±2μs 78.6±1μs 1.11 indexing.DataFrameNumericIndexing.time_iloc_dups(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc') + 121±3μs 135±3μs 1.11 indexing.DataFrameStringIndexing.time_boolean_rows + 71.4±1μs 79.3±2μs 1.11 indexing.DataFrameNumericIndexing.time_iloc_dups(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc') + 4.08±0.2μs 4.53±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, datetime.timezone(datetime.timedelta(seconds=3600))) + 4.02±0.1μs 4.46±0.2μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, datetime.timezone(datetime.timedelta(seconds=3600))) + 110±0.4ms 123±0.2ms 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1000000, 5000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) + 28.9±1ms 32.0±2ms 1.11 gil.ParallelGroupbyMethods.time_parallel(2, 'last') + 1.52±0.01ms 1.69±0.01ms 1.11 rolling.VariableWindowMethods.time_method('DataFrame', '1d', 'float', 'sum') + 1.74±0.01ms 1.93±0.01ms 1.11 rolling.VariableWindowMethods.time_method('DataFrame', '50s', 'int', 'mean') + 2.83±0.01ms 3.13±0.02ms 1.11 rolling.ForwardWindowMethods.time_rolling('Series', 1000, 'float', 'kurt') + 1.44±0.04μs 1.60±0.06μs 1.11 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('date', 1, None) + 4.06±0.1μs 4.50±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 8000, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.10±0.05ms 1.22±0.04ms 1.11 algorithms.Quantile.time_quantile(0, 'nearest', 'int') + 8.52±0.06ms 9.43±0.05ms 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(1000000, 'microseconds') + 487±3μs 539±4μs 1.11 groupby.Datelike.time_sum('date_range_tz') + 42.9±0.1ms 47.5±0.2ms 1.11 frame_methods.Rename.time_rename_axis1 + 1.06±0.01μs 1.18±0.02μs 1.11 tslibs.resolution.TimeResolution.time_get_resolution('D', 1, datetime.timezone.utc) + 87.0±0.6μs 96.3±0.4μs 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(10000, 'nanoseconds') + 158±2μs 174±2μs 1.11 series_methods.Mode.time_mode(1000, 'uint') + 128±3μs 142±2μs 1.11 indexing.DataFrameStringIndexing.time_boolean_rows_boolean + 1.47±0.01ms 1.63±0.02ms 1.11 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'int', 'std') + 1.31±0.01ms 1.45±0.01ms 1.11 rolling.ForwardWindowMethods.time_rolling('DataFrame', 10, 'int', 'min') + 4.02±0.2μs 4.45±0.3μs 1.11 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, datetime.timezone(datetime.timedelta(seconds=3600))) + 1.92±0.06μs 2.13±0.09μs 1.11 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 1, None) + 1.07±0.01μs 1.18±0.02μs 1.11 tslibs.resolution.TimeResolution.time_get_resolution('h', 1, datetime.timezone.utc) + 128±2ms 141±2ms 1.11 groupby.Apply.time_copy_overhead_single_col(4) + 1.07±0.01ms 1.18±0.02ms 1.11 rolling.Pairwise.time_pairwise(({}, 'expanding'), 'corr', False) + 8.55±0.2ms 9.45±0.05ms 1.11 tslibs.fields.TimeGetTimedeltaField.time_get_timedelta_field(1000000, 'nanoseconds') + 1.07±0.01μs 1.18±0.02μs 1.10 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, datetime.timezone.utc) + 1.56±0.02ms 1.72±0.02ms 1.10 rolling.VariableWindowMethods.time_method('Series', '1d', 'float', 'mean') + 4.05±0.1μs 4.48±0.3μs 1.10 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 11000, datetime.timezone(datetime.timedelta(seconds=3600))) + 5.13±0.04μs 5.66±0.05μs 1.10 dtypes.Dtypes.time_pandas_dtype('Int64') + 12.7±0.07ms 14.0±0.1ms 1.10 join_merge.MergeAsof.time_on_uint64('nearest', None) + 1.97±0.5ms 2.18±0.5ms 1.10 rolling.VariableWindowMethods.time_method('Series', '1d', 'float', 'count') + 1.68±0.01ms 1.86±0.02ms 1.10 rolling.VariableWindowMethods.time_method('DataFrame', '50s', 'float', 'mean') + 1.07±0.01μs 1.18±0.02μs 1.10 tslibs.resolution.TimeResolution.time_get_resolution('m', 1, datetime.timezone.utc) + 1.42±0.01ms 1.57±0.02ms 1.10 rolling.Methods.time_method('DataFrame', ('expanding', {}), 'float', 'std') + 3.01±0.07ms 3.32±0.08ms 1.10 timeseries.ResampleSeries.time_resample('period', '5min', 'mean') + 97.8±0.9μs 108±1μs 1.10 groupby.GroupByMethods.time_dtype_as_group('uint', 'cummin', 'direct', 5) + 78.4±0.5μs 86.4±0.6μs 1.10 indexing.AssignTimeseriesIndex.time_frame_assign_timeseries_index + 4.05±0.08μs 4.47±0.2μs 1.10 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, datetime.timezone(datetime.timedelta(seconds=3600))) + 7.34±0.1ms 8.09±0.3ms 1.10 inference.ToDatetimeFromIntsFloats.time_sec_uint64 + 4.07±0.09μs 4.49±0.3μs 1.10 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 5000, datetime.timezone(datetime.timedelta(seconds=3600))) + 16.4±0.5ms 18.0±0.5ms 1.10 join_merge.Join.time_join_dataframe_index_multi(False) + 1.97±0.5ms 2.17±0.5ms 1.10 rolling.VariableWindowMethods.time_method('Series', '50s', 'int', 'count') + 45.5±0.4ms 50.1±0.8ms 1.10 rolling.Pairwise.time_groupby(({'window': 1000}, 'rolling'), 'corr', True) + 1.99±0.5ms 2.19±0.5ms 1.10 rolling.VariableWindowMethods.time_method('Series', '1h', 'float', 'count') + 1.95±0.5ms 2.15±0.5ms 1.10 rolling.VariableWindowMethods.time_method('Series', '1d', 'int', 'count') + 12.8±0.6ms 14.0±0.3ms 1.10 groupby.Cumulative.time_frame_transform('float64', 'cumsum') + 925±50μs 1.02±0.06ms 1.10 arithmetic.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 4, <built-in function eq>) + 1.77±0.06μs 1.95±0.07μs 1.10 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 1, datetime.timezone.utc) + 4.05±0.1μs 4.46±0.3μs 1.10 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 10000, datetime.timezone(datetime.timedelta(seconds=3600))) + 4.02±0.2μs 4.43±0.3μs 1.10 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4000, datetime.timezone(datetime.timedelta(seconds=3600))) + 32.9±4ms 36.2±6ms 1.10 gil.ParallelGroupbyMethods.time_loop(2, 'last') - 80.0±2μs 72.6±2μs 0.91 indexing.CategoricalIndexIndexing.time_getitem_list_like('monotonic_incr') - 75.2±0.8μs 68.3±0.7μs 0.91 tslibs.period.PeriodUnaryMethods.time_to_timestamp('min') - 1.40±0.02ms 1.27±0.01ms 0.91 reindex.DropDuplicates.time_frame_drop_dups_bool(True) - 16.4±0.3ms 14.9±0.2ms 0.91 rolling.Groupby.time_method('sum', ('expanding', {})) - 275±2ns 249±4ns 0.91 tslibs.timestamp.TimestampProperties.time_is_month_end(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) - 4.93±0.1μs 4.47±0.1μs 0.91 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc') - 16.5±0.3ms 14.9±0.2ms 0.91 rolling.Groupby.time_method('kurt', ('expanding', {})) - 79.8±1μs 72.4±2μs 0.91 indexing.CategoricalIndexIndexing.time_getitem_list_like('non_monotonic') - 55.6±0.4ms 50.4±3ms 0.91 io.stata.Stata.time_read_stata('tm') - 76.0±1ms 68.8±1ms 0.91 groupby.GroupByMethods.time_dtype_as_group('float', 'skew', 'transformation', 5) - 80.0±2μs 72.5±2μs 0.91 indexing.CategoricalIndexIndexing.time_getitem_list_like('monotonic_decr') - 16.4±0.4ms 14.9±0.3ms 0.91 rolling.Groupby.time_method('max', ('expanding', {})) - 275±1ns 249±4ns 0.91 tslibs.timestamp.TimestampProperties.time_is_month_end(datetime.timezone.utc, None) - 54.5±0.4ms 49.4±3ms 0.91 io.stata.Stata.time_read_stata('td') - 36.5±0.2ms 33.0±0.4ms 0.91 strings.Methods.time_join('str') - 12.2±0.2μs 11.0±0.2μs 0.90 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<QuarterEnd: startingMonth=3>) - 19.4±0.9ms 17.5±0.4ms 0.90 rolling.Groupby.time_method('kurt', ('rolling', {'window': '30s', 'on': 'C'})) - 5.08±0.09μs 4.59±0.07μs 0.90 indexing.CategoricalIndexIndexing.time_get_loc_scalar('monotonic_incr') - 54.5±0.7ms 49.3±1ms 0.90 frame_ctor.FromDicts.time_nested_dict_int64 - 51.8±3ms 46.8±3ms 0.90 strings.Cat.time_cat(3, None, None, 0.15) - 217±4μs 196±4μs 0.90 algos.isin.IsIn.time_isin_empty('string[python]') - 9.10±0.2μs 8.23±0.09μs 0.90 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(100, 8000) - 274±1ns 248±4ns 0.90 tslibs.timestamp.TimestampProperties.time_is_month_end(None, None) - 50.1±0.4ms 45.2±0.1ms 0.90 frame_methods.Count.time_count_level_multi(0) - 49.1±0.3ms 44.4±0.3ms 0.90 frame_methods.Count.time_count_level_multi(1) - 55.8±0.6ms 50.4±3ms 0.90 io.stata.Stata.time_read_stata('tq') - 18.7±2ms 16.9±0.8ms 0.90 categoricals.Constructor.time_regular - 1.31±0.01ms 1.19±0.01ms 0.90 groupby.GroupByMethods.time_dtype_as_group('int', 'cumprod', 'transformation', 5) - 34.8±0.2ms 31.4±0.1ms 0.90 strings.Methods.time_fullmatch('str') - 202±5μs 182±4μs 0.90 algos.isin.IsIn.time_isin_empty('str') - 2.37±0.02ms 2.14±0.02ms 0.90 stat_ops.FrameOps.time_op('var', 'Int64', 0) - 1.31±0.01ms 1.18±0.01ms 0.90 groupby.GroupByMethods.time_dtype_as_group('uint', 'cumprod', 'transformation', 5) - 8.36±0.2μs 7.53±0.1μs 0.90 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(100, 7000) - 278±2ns 251±4ns 0.90 tslibs.timestamp.TimestampProperties.time_is_month_end(tzlocal(), None) - 29.4±0.3μs 26.5±0.6μs 0.90 tslibs.timestamp.TimestampOps.time_tz_convert(tzlocal()) - 253±3ns 228±4ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), None) - 252±3ns 227±4ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(None, 'B') - 73.9±1μs 66.4±2μs 0.90 categoricals.CategoricalSlicing.time_getitem_list_like('monotonic_incr') - 253±3ns 228±5ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) - 253±3ns 228±4ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(datetime.timezone.utc, None) - 262±2ns 236±5ns 0.90 tslibs.timestamp.TimestampProperties.time_week(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') - 254±3ns 228±4ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(datetime.timezone(datetime.timedelta(seconds=3600)), None) - 33.5±0.2ms 30.1±0.2ms 0.90 strings.Methods.time_match('str') - 184±2ms 165±1ms 0.90 io.excel.WriteExcel.time_write_excel('xlwt') - 253±3ns 228±4ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(datetime.timezone.utc, 'B') - 2.63±0.1ms 2.36±0.1ms 0.90 frame_methods.Fillna.time_frame_fillna(False, 'bfill', 'datetime64[ns]') - 39.5±0.4μs 35.4±0.3μs 0.90 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 12.0±0.2μs 10.8±0.3μs 0.90 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BYearEnd: month=12>) - 254±3ns 228±3ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') - 253±4ns 227±4ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') - 256±3ns 230±5ns 0.90 tslibs.timestamp.TimestampProperties.time_dayofyear(tzlocal(), None) - 262±3ns 235±5ns 0.90 tslibs.timestamp.TimestampProperties.time_week(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') - 3.41±0.02μs 3.06±0.05μs 0.90 indexing.NonNumericSeriesIndexing.time_getitem_scalar('string', 'unique_monotonic_inc') - 16.1±0.2ms 14.5±0.1ms 0.90 stat_ops.FrameMultiIndexOps.time_op(0, 'skew') - 74.0±2μs 66.4±1μs 0.90 categoricals.CategoricalSlicing.time_getitem_list_like('non_monotonic') - 11.8±0.2μs 10.5±0.4μs 0.90 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<QuarterBegin: startingMonth=3>) - 1.28±0.2ms 1.15±0.07ms 0.90 series_methods.NanOps.time_func('prod', 1000000, 'int8') - 8.57±0.2ms 7.68±0.2ms 0.90 series_methods.NanOps.time_func('median', 1000000, 'int8') - 265±2ns 238±5ns 0.90 tslibs.timestamp.TimestampProperties.time_week(tzlocal(), None) - 55.8±0.5ms 49.9±3ms 0.90 io.stata.Stata.time_read_stata('th') - 263±2ns 235±5ns 0.90 tslibs.timestamp.TimestampProperties.time_week(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), None) - 253±3ns 226±4ns 0.89 tslibs.timestamp.TimestampProperties.time_dayofyear(None, None) - 1.33±0.01ms 1.19±0.01ms 0.89 groupby.GroupByMethods.time_dtype_as_group('int16', 'cumprod', 'transformation', 5) - 263±2ns 235±5ns 0.89 tslibs.timestamp.TimestampProperties.time_week(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') - 56.0±0.6μs 50.1±0.6μs 0.89 algos.isin.IsIn.time_isin_empty('string[pyarrow]') - 191±2μs 171±2μs 0.89 algos.isin.IsIn.time_isin_empty('object') - 6.57±0.4ms 5.87±0.2ms 0.89 arithmetic.IntFrameWithScalar.time_frame_op_with_scalar(<class 'numpy.int64'>, 5.0, <built-in function pow>) - 13.3±0.1μs 11.9±0.06μs 0.89 tslibs.resolution.TimeResolution.time_get_resolution('ns', 100, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 37.6±0.3μs 33.6±0.8μs 0.89 tslibs.timestamp.TimestampOps.time_normalize(tzlocal()) - 378±6μs 338±7μs 0.89 reindex.Reindex.time_reindex_dates - 12.0±0.2μs 10.7±0.3μs 0.89 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BusinessQuarterBegin: startingMonth=3>) - 74.2±2μs 66.3±2μs 0.89 categoricals.CategoricalSlicing.time_getitem_list_like('monotonic_decr') - 37.1±0.5μs 33.1±0.6μs 0.89 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') - 255±3ns 228±4ns 0.89 tslibs.timestamp.TimestampProperties.time_dayofyear(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') - 236±3ns 211±5ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') - 235±3ns 210±4ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') - 31.2±0.5ms 27.8±0.5ms 0.89 strings.Methods.time_pad('str') - 54.3±0.6ms 48.4±3ms 0.89 io.stata.Stata.time_read_stata('ty') - 262±3ns 234±5ns 0.89 tslibs.timestamp.TimestampProperties.time_week(datetime.timezone.utc, 'B') - 322±2μs 287±2μs 0.89 join_merge.Concat.time_concat_mixed_ndims(0) - 11.9±0.2μs 10.6±0.2μs 0.89 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BusinessQuarterEnd: startingMonth=3>) - 236±2ns 210±5ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), None) - 235±2ns 209±4ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(None, 'B') - 7.17±0.08ms 6.39±0.09ms 0.89 io.csv.ToCSVDatetime.time_frame_date_formatting - 264±3ns 236±5ns 0.89 tslibs.timestamp.TimestampProperties.time_week(tzlocal(), 'B') - 1.37±0.05μs 1.23±0.05μs 0.89 index_cached_properties.IndexCache.time_values('PeriodIndex') - 11.8±0.2μs 10.5±0.3μs 0.89 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<YearBegin: month=1>) - 5.30±0.05ms 4.72±0.05ms 0.89 reindex.DropDuplicates.time_frame_drop_dups_na(True) - 1.80±0.06μs 1.60±0.06μs 0.89 index_cached_properties.IndexCache.time_shape('PeriodIndex') - 235±3ns 209±4ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(datetime.timezone.utc, 'B') - 12.0±0.2μs 10.7±0.3μs 0.89 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BYearBegin: month=1>) - 57.0±1ms 50.8±1ms 0.89 indexing.MultiIndexing.time_loc_all_null_slices(False) - 2.60±0.1ms 2.32±0.1ms 0.89 frame_methods.Fillna.time_frame_fillna(False, 'pad', 'datetime64[ns]') - 236±2ns 210±4ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') - 12.0±0.3μs 10.7±0.4μs 0.89 multiindex_object.GetLoc.time_med_get_loc - 6.34±0.1μs 5.64±0.2μs 0.89 tslibs.timestamp.TimestampOps.time_tz_convert(datetime.timezone(datetime.timedelta(seconds=3600))) - 237±3ns 211±5ns 0.89 tslibs.timestamp.TimestampProperties.time_days_in_month(tzlocal(), 'B') - 262±2ns 233±4ns 0.89 tslibs.timestamp.TimestampProperties.time_week(None, 'B') - 262±2ns 233±6ns 0.89 tslibs.timestamp.TimestampProperties.time_week(datetime.timezone(datetime.timedelta(seconds=3600)), None) - 31.1±0.3ms 27.7±0.4ms 0.89 strings.Methods.time_center('str') - 257±3ns 228±5ns 0.89 tslibs.timestamp.TimestampProperties.time_dayofyear(tzlocal(), 'B') - 16.4±0.3μs 14.6±0.6μs 0.89 timeseries.AsOf.time_asof_single('Series') - 7.20±0.04ms 6.40±0.02ms 0.89 inference.ToTimedelta.time_convert_string_seconds - 263±3ns 234±5ns 0.89 tslibs.timestamp.TimestampProperties.time_week(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) - 246±1ms 219±1ms 0.89 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'median') - 262±3ns 233±4ns 0.89 tslibs.timestamp.TimestampProperties.time_week(datetime.timezone.utc, None) - 30.6±0.2ms 27.1±0.1ms 0.89 strings.Methods.time_get('str') - 591±3μs 524±4μs 0.89 indexing.NonNumericSeriesIndexing.time_getitem_list_like('period', 'unique_monotonic_inc') - 262±3ns 233±5ns 0.89 tslibs.timestamp.TimestampProperties.time_week(None, None) - 4.16±0.06ms 3.69±0.05ms 0.89 algorithms.Factorize.time_factorize(True, False, 'Int64') - 43.1±10ms 38.2±10ms 0.89 algos.isin.IsinAlmostFullWithRandomInt.time_isin(<class 'numpy.object_'>, 19, 'inside') - 8.13±0.1ms 7.20±0.2ms 0.89 indexing.NumericSeriesIndexing.time_getitem_scalar(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'nonunique_monotonic_inc') - 133±0.7μs 118±1μs 0.89 tslibs.period.PeriodProperties.time_property('M', 'end_time') - 11.0±0.2μs 9.73±0.2μs 0.89 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<QuarterEnd: startingMonth=3>) - 25.1±0.1ms 22.2±0.1ms 0.88 strings.Methods.time_len('str') - 235±3ns 208±5ns 0.88 tslibs.timestamp.TimestampProperties.time_days_in_month(None, None) - 598±3μs 529±3μs 0.88 indexing.NonNumericSeriesIndexing.time_getitem_list_like('period', 'non_monotonic') - 12.4±0.3μs 11.0±0.2μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<YearEnd: month=12>) - 11.7±0.2μs 10.4±0.6μs 0.88 tslibs.timestamp.TimestampOps.time_normalize(datetime.timezone(datetime.timedelta(seconds=3600))) - 1.85±0.03ms 1.64±0.02ms 0.88 reindex.DropDuplicates.time_frame_drop_dups_bool(False) - 10.9±0.2μs 9.60±0.3μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<YearBegin: month=1>) - 37.3±0.5μs 33.0±0.4μs 0.88 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.Int64Index'>, 'unique_monotonic_inc') - 7.31±0.2μs 6.46±0.1μs 0.88 tslibs.period.TimePeriodArrToDT64Arr.time_periodarray_to_dt64arr(100, 6000) - 4.22±0.1μs 3.72±0.07μs 0.88 libs.InferDtype.time_infer_dtype('empty') - 113±1μs 99.8±2μs 0.88 algos.isin.IsIn.time_isin_mismatched_dtype('string[pyarrow]') - 624±4μs 550±4μs 0.88 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'unique_monotonic_inc') - 236±3ns 208±6ns 0.88 tslibs.timestamp.TimestampProperties.time_days_in_month(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) - 120±0.4ms 106±1ms 0.88 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int64', 'var') - 292±1ms 258±3ms 0.88 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('datetime64[ns]', 'int64'), 'outer') - 37.4±0.5μs 32.9±0.4μs 0.88 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.Int64Index'>, 'nonunique_monotonic_inc') - 10.8±0.2μs 9.47±0.3μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<MonthEnd>) - 629±3μs 554±4μs 0.88 indexing.NonNumericSeriesIndexing.time_getitem_list_like('datetime', 'non_monotonic') - 37.4±0.5μs 32.9±0.4μs 0.88 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.UInt64Index'>, 'unique_monotonic_inc') - 37.5±0.6μs 33.0±0.4μs 0.88 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'nonunique_monotonic_inc') - 10.8±0.2μs 9.53±0.2μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BusinessMonthBegin>) - 11.0±0.1μs 9.67±0.2μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BusinessQuarterEnd: startingMonth=3>) - 27.2±0.1ms 23.9±0.2ms 0.88 strings.Contains.time_contains('str', True) - 236±3ns 208±5ns 0.88 tslibs.timestamp.TimestampProperties.time_days_in_month(datetime.timezone(datetime.timedelta(seconds=3600)), None) - 10.9±0.2μs 9.61±0.2μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BusinessQuarterBegin: startingMonth=3>) - 10.8±0.1μs 9.52±0.3μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<QuarterBegin: startingMonth=3>) - 10.7±0.1μs 9.42±0.3μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<MonthBegin>) - 40.1±0.6μs 35.2±0.5μs 0.88 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1, tzlocal()) - 10.9±0.2μs 9.58±0.2μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BusinessQuarterBegin: startingMonth=3>) - 212±3ns 186±4ns 0.88 tslibs.timestamp.TimestampProperties.time_is_leap_year(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') - 11.0±0.2μs 9.62±0.3μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<SemiMonthBegin: day_of_month=15>) - 236±3ns 207±5ns 0.88 tslibs.timestamp.TimestampProperties.time_days_in_month(datetime.timezone.utc, None) - 10.9±0.2μs 9.52±0.2μs 0.88 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BusinessQuarterEnd: startingMonth=3>) - 15.3±0.1μs 13.4±0.08μs 0.88 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 10.8±0.2μs 9.47±0.3μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<QuarterBegin: startingMonth=3>) - 10.9±0.2μs 9.58±0.3μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BYearBegin: month=1>) - 661±6μs 578±2μs 0.87 algorithms.Factorize.time_factorize(True, False, 'boolean') - 11.0±0.2μs 9.57±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<BusinessMonthEnd>) - 11.6±0.3ms 10.1±0.3ms 0.87 multiindex_object.GetLoc.time_small_get_loc_warm - 117±0.4ms 102±1ms 0.87 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int64', 'mean') - 15.2±0.1μs 13.2±0.1μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 9000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 37.5±0.7μs 32.7±0.4μs 0.87 indexing.NumericSeriesIndexing.time_iloc_list_like(<class 'pandas.core.indexes.numeric.Float64Index'>, 'unique_monotonic_inc') - 15.2±0.1μs 13.3±0.08μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 4000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 213±4ns 186±5ns 0.87 tslibs.timestamp.TimestampProperties.time_is_leap_year(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), None) - 2.53±0.03μs 2.21±0.03μs 0.87 period.Indexing.time_get_loc - 15.3±0.2μs 13.4±0.08μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 12000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 10.2±0.1μs 8.88±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BusinessMonthBegin>) - 24.6±0.6μs 21.4±0.7μs 0.87 tslibs.timestamp.TimestampOps.time_replace_tz(tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 12.1±0.3μs 10.5±0.3μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<SemiMonthBegin: day_of_month=15>) - 15.2±0.2μs 13.2±0.08μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 4006, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 11.1±0.2μs 9.70±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BYearBegin: month=1>) - 11.1±0.3μs 9.62±0.3μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BYearEnd: month=12>) - 1.37±0.01ms 1.20±0.01ms 0.87 categoricals.Concat.time_concat_non_overlapping_index - 10.3±0.1μs 8.98±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BusinessMonthEnd>) - 15.2±0.1μs 13.2±0.1μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 11000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 240±2ns 209±4ns 0.87 tslibs.timestamp.TimestampProperties.time_days_in_month(tzlocal(), None) - 15.0±0.1μs 13.1±0.08μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 10.2±0.1μs 8.83±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<MonthBegin>) - 199±6ms 173±6ms 0.87 index_object.Indexing.time_get_loc_non_unique_sorted('String') - 15.9±0.1μs 13.8±0.09μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 5000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 10.2±0.2μs 8.83±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<MonthEnd>) - 10.2±0.2μs 8.90±0.3μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<MonthEnd>) - 1.37±0.06μs 1.19±0.06μs 0.87 index_cached_properties.IndexCache.time_inferred_type('PeriodIndex') - 143±2μs 125±2μs 0.87 tslibs.period.PeriodProperties.time_property('min', 'end_time') - 11.1±0.2μs 9.61±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<SemiMonthEnd: day_of_month=15>) - 84.7±2μs 73.5±1μs 0.87 multiindex_object.GetLoc.time_large_get_loc - 6.93±0.2μs 6.02±0.2μs 0.87 index_object.Indexing.time_get_loc_non_unique_sorted('Int') - 11.3±0.3μs 9.76±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<YearEnd: month=12>) - 704±6μs 611±3μs 0.87 groupby.GroupByMethods.time_dtype_as_group('float', 'cumprod', 'transformation', 1) - 21.9±0.7ms 19.0±0.4ms 0.87 io.style.Render.time_tooltips_render(36, 12) - 15.1±0.1μs 13.1±0.1μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 8000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 11.0±0.2μs 9.52±0.3μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BYearEnd: month=12>) - 214±3ns 185±5ns 0.87 tslibs.timestamp.TimestampProperties.time_is_leap_year(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) - 10.3±0.2μs 8.96±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<BusinessMonthBegin>) - 10.2±0.1μs 8.82±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<MonthBegin>) - 11.3±0.2μs 9.77±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<QuarterEnd: startingMonth=3>) - 11.0±0.3μs 9.53±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<SemiMonthEnd: day_of_month=15>) - 15.1±0.2μs 13.1±0.09μs 0.87 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 6000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 212±3ns 184±5ns 0.87 tslibs.timestamp.TimestampProperties.time_is_leap_year(datetime.timezone(datetime.timedelta(seconds=3600)), None) - 9.49±0.2μs 8.21±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_add(<SemiMonthEnd: day_of_month=15>) - 11.3±0.2μs 9.81±0.2μs 0.87 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<YearEnd: month=12>) - 212±3ns 183±6ns 0.87 tslibs.timestamp.TimestampProperties.time_is_leap_year(None, 'B') - 225±2μs 195±1μs 0.86 join_merge.Concat.time_concat_empty_left(0) - 225±1μs 194±2μs 0.86 join_merge.Concat.time_concat_empty_right(0) - 9.39±0.1μs 8.11±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<YearBegin: month=1>) - 213±3ns 184±4ns 0.86 tslibs.timestamp.TimestampProperties.time_is_leap_year(datetime.timezone.utc, 'B') - 215±4ns 185±4ns 0.86 tslibs.timestamp.TimestampProperties.time_is_leap_year(tzlocal(), 'B') - 13.9±0.1μs 12.0±0.1μs 0.86 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 296±2ms 256±4ms 0.86 io.csv.ReadCSVEngine.time_read_bytescsv('python') - 9.28±0.2μs 8.00±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<MonthBegin>) - 9.43±0.1μs 8.14±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<SemiMonthBegin: day_of_month=15>) - 11.8±0.4μs 10.2±0.4μs 0.86 multiindex_object.GetLoc.time_string_get_loc - 10.9±0.1μs 9.36±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<YearBegin: month=1>) - 9.47±0.1μs 8.16±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<YearEnd: month=12>) - 10.9±0.3μs 9.43±0.3μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add_10(<SemiMonthBegin: day_of_month=15>) - 213±4ns 184±5ns 0.86 tslibs.timestamp.TimestampProperties.time_is_leap_year(datetime.timezone.utc, None) - 12.3±0.2ms 10.6±0.09ms 0.86 reindex.DropDuplicates.time_frame_drop_dups_na(False) - 216±4ns 186±5ns 0.86 tslibs.timestamp.TimestampProperties.time_is_leap_year(tzlocal(), None) - 10.3±0.1μs 8.83±0.3μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_subtract(<BusinessMonthEnd>) - 213±3ns 183±5ns 0.86 tslibs.timestamp.TimestampProperties.time_is_leap_year(None, None) - 9.83±0.7ms 8.45±0.1ms 0.86 timeseries.Iteration.time_iter_preexit(<function period_range at 0x7f68e010eaf0>) - 13.9±0.09μs 11.9±0.09μs 0.86 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 1000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 2.60±0.03μs 2.24±0.03μs 0.86 indexing.NonNumericSeriesIndexing.time_getitem_scalar('string', 'non_monotonic') - 12.1±0.2μs 10.4±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_subtract_10(<SemiMonthEnd: day_of_month=15>) - 214±3ns 184±5ns 0.86 tslibs.timestamp.TimestampProperties.time_is_leap_year(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') - 13.9±0.1ms 11.9±0.1ms 0.86 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'median') - 4.34±0.1ms 3.72±0.1ms 0.86 reindex.DropDuplicates.time_frame_drop_dups(True) - 24.2±0.1ms 20.7±0.1ms 0.86 strings.Methods.time_endswith('str') - 12.4±0.1μs 10.6±0.1μs 0.86 tslibs.resolution.TimeResolution.time_get_resolution('s', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 9.47±0.2μs 8.11±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<QuarterBegin: startingMonth=3>) - 14.0±0.1μs 12.0±0.09μs 0.86 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 9.54±0.2μs 8.16±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BYearEnd: month=12>) - 9.64±0.2μs 8.24±0.2μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BusinessQuarterEnd: startingMonth=3>) - 22.2±0.3ms 18.9±0.2ms 0.86 strings.Methods.time_slice('str') - 31.0±1ms 26.5±0.7ms 0.86 hash_functions.Float64GroupIndex.time_groupby - 9.33±0.1μs 7.98±0.1μs 0.86 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BusinessMonthBegin>) - 9.51±0.2μs 8.13±0.2μs 0.85 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BYearBegin: month=1>) - 216±4ns 184±5ns 0.85 tslibs.timestamp.TimestampProperties.time_is_leap_year(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') - 24.2±0.1ms 20.6±0.1ms 0.85 strings.Methods.time_startswith('str') - 9.50±0.1μs 8.12±0.09μs 0.85 tslibs.offsets.OffestDatetimeArithmetic.time_add(<QuarterEnd: startingMonth=3>) - 9.32±0.1μs 7.97±0.1μs 0.85 tslibs.offsets.OffestDatetimeArithmetic.time_add(<MonthEnd>) - 24.9±0.3ms 21.3±0.3ms 0.85 strings.Methods.time_title('str') - 13.9±0.1μs 11.9±0.1μs 0.85 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 1011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 11.9±0.3ms 10.2±0.3ms 0.85 multiindex_object.GetLoc.time_med_get_loc_warm - 14.0±0.1μs 11.9±0.08μs 0.85 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 10.6±0.1ms 9.07±0.09ms 0.85 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'sem') - 53.3±1ms 45.4±1ms 0.85 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('Int64', 'Int64'), 'right') - 9.50±0.1μs 8.10±0.1μs 0.85 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BusinessQuarterBegin: startingMonth=3>) - 9.33±0.2μs 7.95±0.2μs 0.85 tslibs.offsets.OffestDatetimeArithmetic.time_add(<BusinessMonthEnd>) - 14.6±0.3ms 12.5±0.3ms 0.85 indexing.ChainIndexing.time_chained_indexing('warn') - 2.56±0.1ms 2.18±0.1ms 0.85 frame_methods.Fillna.time_frame_fillna(False, 'bfill', 'timedelta64[ns]') - 12.4±0.1μs 10.6±0.1μs 0.85 tslibs.resolution.TimeResolution.time_get_resolution('D', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.43±0.05μs 1.22±0.05μs 0.85 index_cached_properties.IndexCache.time_values('DatetimeIndex') - 1.89±0.1μs 1.61±0.07μs 0.85 index_cached_properties.IndexCache.time_shape('DatetimeIndex') - 97.0±0.8μs 82.1±1μs 0.85 indexing.IndexSingleRow.time_iloc_row(True) - 9.09±2ms 7.70±2ms 0.85 algorithms.Factorize.time_factorize(False, False, 'Int64') - 12.3±0.2μs 10.4±0.1μs 0.85 tslibs.resolution.TimeResolution.time_get_resolution('h', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 21.3±0.3ms 18.0±0.3ms 0.85 strings.Methods.time_upper('str') - 24.4±0.8μs 20.6±0.6μs 0.85 tslibs.timestamp.TimestampOps.time_replace_tz(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 14.5±2ms 12.2±2ms 0.85 algorithms.Factorize.time_factorize(False, True, 'Int64') - 97.5±0.8μs 82.4±1μs 0.85 indexing.IndexSingleRow.time_iloc_row(False) - 621±5μs 525±3μs 0.84 groupby.GroupByMethods.time_dtype_as_group('uint', 'cumprod', 'transformation', 1) - 11.7±0.6ms 9.92±0.06ms 0.84 algos.isin.IsinWithArange.time_isin(<class 'numpy.object_'>, 8000, -2) - 618±4μs 522±3μs 0.84 groupby.GroupByMethods.time_dtype_as_group('int', 'cumprod', 'transformation', 1) - 12.4±0.1μs 10.5±0.1μs 0.84 tslibs.resolution.TimeResolution.time_get_resolution('m', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 11.7±0.6ms 9.81±0.1ms 0.84 algos.isin.IsinWithArange.time_isin(<class 'numpy.object_'>, 2000, -2) - 11.6±0.6ms 9.78±0.02ms 0.84 algos.isin.IsinWithArange.time_isin(<class 'numpy.object_'>, 1000, -2) - 5.52±0.2μs 4.65±0.3μs 0.84 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1, datetime.timezone(datetime.timedelta(seconds=3600))) - 105±1μs 88.1±0.7μs 0.84 indexing.IndexSingleRow.time_loc_row(False) - 22.7±0.2ms 19.1±0.1ms 0.84 strings.Methods.time_normalize('str') - 39.9±1ms 33.5±0.5ms 0.84 io.sql.WriteSQLDtypes.time_to_sql_dataframe_column('sqlite', 'time') - 1.42±0.05μs 1.19±0.06μs 0.84 index_cached_properties.IndexCache.time_inferred_type('DatetimeIndex') - 140±0.8ms 117±0.4ms 0.84 strings.Slice.time_vector_slice - 105±0.8μs 87.9±0.9μs 0.84 indexing.IndexSingleRow.time_loc_row(True) - 25.7±0.3ms 21.5±0.2ms 0.84 io.style.Render.time_apply_format_hide_render(36, 120) - 22.5±0.1ms 18.8±0.1ms 0.84 strings.Methods.time_replace('str') - 910±60ms 761±5ms 0.84 timeseries.Iteration.time_iter(<function period_range at 0x7f68e010eaf0>) - 696±30μs 581±20μs 0.83 timeseries.DatetimeIndex.time_unique('repeated') - 62.7±0.3ms 52.3±0.2ms 0.83 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'sum') - 574±6μs 478±3μs 0.83 groupby.GroupByMethods.time_dtype_as_field('uint', 'cumprod', 'transformation', 1) - 2.65±0.04μs 2.21±0.04μs 0.83 index_object.Indexing.time_get_loc_sorted('Int') - 8.16±0.2μs 6.78±0.2μs 0.83 timeseries.AsOf.time_asof_single_early('Series') - 2.65±0.04μs 2.20±0.03μs 0.83 index_object.Indexing.time_get_loc('Int') - 645±5μs 536±3μs 0.83 groupby.GroupByMethods.time_dtype_as_group('int16', 'cumprod', 'transformation', 1) - 17.2±0.3ms 14.3±0.3ms 0.83 io.style.Render.time_tooltips_render(24, 12) - 1.01±0.01ms 842±5μs 0.83 categoricals.Concat.time_append_non_overlapping_index - 576±4μs 477±3μs 0.83 groupby.GroupByMethods.time_dtype_as_field('int', 'cumprod', 'transformation', 1) - 53.6±2ms 44.3±1ms 0.83 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('Int64', 'Int64'), 'left') - 35.4±0.4ms 29.1±0.4ms 0.82 groupby.GroupByCythonAgg.time_frame_agg('float64', 'min') - 579±5μs 476±3μs 0.82 groupby.GroupByMethods.time_dtype_as_field('int16', 'cummax', 'transformation', 1) - 18.6±0.1ms 15.3±0.1ms 0.82 strings.Methods.time_lstrip('str') - 66.2±0.4ms 54.3±1ms 0.82 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'var') - 21.1±0.2ms 17.3±0.1ms 0.82 strings.Methods.time_isalnum('str') - 523±3μs 429±5μs 0.82 indexing.DatetimeIndexIndexing.time_get_indexer_mismatched_tz - 578±4μs 474±3μs 0.82 groupby.GroupByMethods.time_dtype_as_field('int16', 'cummin', 'transformation', 1) - 19.6±0.2ms 16.1±0.08ms 0.82 strings.Methods.time_zfill('str') - 7.55±0.1ms 6.18±0.08ms 0.82 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'sum') - 7.59±0.1ms 6.20±0.06ms 0.82 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'mean') - 7.66±0.8ms 6.25±0.2ms 0.82 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('ge') - 18.8±0.1ms 15.4±0.1ms 0.82 strings.Contains.time_contains('str', False) - 7.28±0.1ms 5.94±0.07ms 0.82 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'prod') - 7.77±0.1ms 6.34±0.09ms 0.82 stat_ops.FrameMultiIndexOps.time_op([0, 1], 'var') - 18.3±0.1ms 15.0±0.08ms 0.82 strings.Methods.time_strip('str') - 5.77±0.3ms 4.70±0.09ms 0.81 series_methods.NanOps.time_func('var', 1000000, 'Int64') - 18.4±0.1ms 15.0±0.05ms 0.81 strings.Methods.time_rstrip('str') - 18.3±0.2ms 14.9±0.1ms 0.81 strings.Methods.time_islower('str') - 18.2±0.1ms 14.9±0.1ms 0.81 strings.Methods.time_isalpha('str') - 14.2±0.2μs 11.6±0.3μs 0.81 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'nonunique_monotonic_inc') - 9.03±0.1ms 7.34±0.1ms 0.81 strings.Cat.time_cat(0, ',', '-', 0.15) - 7.95±0.1ms 6.47±0.3ms 0.81 groupby.Float32.time_sum - 8.90±0.2μs 7.16±0.1μs 0.80 inference.MaybeConvertObjects.time_maybe_convert_objects - 165±2μs 132±2μs 0.80 timeseries.DatetimeIndex.time_add_timedelta('dst') - 12.9±0.1μs 10.4±0.1μs 0.80 tslibs.resolution.TimeResolution.time_get_resolution('us', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 18.8±0.2ms 15.1±0.2ms 0.80 strings.Methods.time_istitle('str') - 6.57±0.06ms 5.27±0.06ms 0.80 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'float', 'sem') - 7.68±0.6ms 6.16±0.1ms 0.80 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('ne') - 17.5±0.3ms 14.0±0.3ms 0.80 strings.Methods.time_lower('str') - 17.5±0.1ms 14.0±0.1ms 0.80 strings.Methods.time_isupper('str') - 55.0±0.2ms 44.0±0.3ms 0.80 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'first') - 7.63±0.8ms 6.09±0.1ms 0.80 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('eq') - 8.46±0.1ms 6.75±0.1ms 0.80 strings.Cat.time_cat(0, None, None, 0.15) - 8.90±0.1ms 7.10±0.04ms 0.80 strings.Cat.time_cat(0, None, '-', 0.15) - 13.3±0.3μs 10.6±0.3μs 0.80 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'unique_monotonic_inc') - 63.2±0.3ms 50.3±1ms 0.80 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'mean') - 19.3±0.2ms 15.3±0.1ms 0.80 io.style.Render.time_apply_format_hide_render(24, 120) - 7.86±0.2ms 6.25±0.2ms 0.79 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('le') - 8.47±0.2ms 6.73±0.4ms 0.79 frame_methods.Fillna.time_frame_fillna(True, 'pad', 'datetime64[ns, tz]') - 525±10μs 417±9μs 0.79 index_cached_properties.IndexCache.time_is_monotonic_decreasing('MultiIndex') - 6.64±0.05ms 5.27±0.05ms 0.79 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'int', 'sem') - 8.70±0.1ms 6.91±0.1ms 0.79 strings.Cat.time_cat(0, ',', None, 0.15) - 9.97±0.2μs 7.91±0.2μs 0.79 indexing.NonNumericSeriesIndexing.time_getitem_scalar('datetime', 'non_monotonic') - 7.87±0.2ms 6.24±0.1ms 0.79 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('gt') - 16.2±0.2ms 12.8±0.1ms 0.79 strings.Methods.time_isnumeric('str') - 8.37±0.1ms 6.63±0.09ms 0.79 strings.Cat.time_cat(0, ',', None, 0.001) - 7.66±0.9ms 6.07±0.1ms 0.79 arithmetic.MixedFrameWithSeriesAxis.time_frame_op_with_series_axis1('lt') - 6.65±0.06ms 5.26±0.04ms 0.79 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'int', 'sem') - 8.13±0.1ms 6.44±0.09ms 0.79 strings.Cat.time_cat(0, None, None, 0.001) - 5.41±0.07μs 4.27±0.1μs 0.79 timeseries.DatetimeIndex.time_get('repeated') - 7.65±0.08ms 6.03±0.04ms 0.79 stat_ops.SeriesMultiIndexOps.time_op(0, 'skew') - 212±5ns 167±3ns 0.79 tslibs.timedelta.TimedeltaProperties.time_timedelta_nanoseconds - 6.62±0.05ms 5.22±0.04ms 0.79 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'float', 'sem') - 140±0.4ms 110±0.4ms 0.79 index_object.Indexing.time_get_loc_sorted('String') - 8.38±0.3ms 6.59±0.06ms 0.79 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'median') - 8.59±0.1ms 6.76±0.06ms 0.79 stat_ops.FrameMultiIndexOps.time_op(1, 'median') - 126±0.7ms 99.4±0.8ms 0.79 reindex.Reindex.time_reindex_multiindex_with_cache - 1.33±0.01s 1.04±0.01s 0.79 io.excel.WriteExcelStyled.time_write_excel_style('openpyxl') - 636±200μs 499±70μs 0.78 series_methods.NanOps.time_func('sum', 1000000, 'int8') - 8.40±0.08ms 6.59±0.07ms 0.78 stat_ops.FrameMultiIndexOps.time_op(0, 'median') - 8.15±0.1ms 6.39±0.1ms 0.78 strings.Cat.time_cat(0, None, '-', 0.001) - 1.43±0.02μs 1.12±0.02μs 0.78 timedelta.TimedeltaIndexing.time_get_loc - 1.04±0.02μs 813±20ns 0.78 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(0, datetime.timezone.utc) - 16.3±0.1ms 12.8±0.1ms 0.78 strings.Methods.time_isdecimal('str') - 55.1±0.3ms 43.1±0.3ms 0.78 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'prod') - 386±2μs 302±2μs 0.78 groupby.GroupByMethods.time_dtype_as_field('int16', 'rank', 'direct', 5) - 349±2μs 273±2μs 0.78 groupby.GroupByMethods.time_dtype_as_field('int16', 'rank', 'direct', 1) - 3.76±0.1ms 2.93±0.05ms 0.78 strftime.DatetimeStrftime.time_frame_datetime_formatting_custom(1000) - 5.49±0.1μs 4.28±0.2μs 0.78 timeseries.DatetimeIndex.time_get('tz_naive') - 47.0±0.3ms 36.6±0.3ms 0.78 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'max') - 12.3±0.2μs 9.58±0.1μs 0.78 tslibs.resolution.TimeResolution.time_get_resolution('ns', 100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 6.31±0.06ms 4.91±0.05ms 0.78 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'float', 'sem') - 407±5ns 317±4ns 0.78 tslibs.timestamp.TimestampProperties.time_dayofweek(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), 'B') - 6.82±0.03ms 5.30±0.03ms 0.78 libs.InferDtype.time_infer_dtype_skipna('py-null') - 8.53±0.1ms 6.61±0.1ms 0.78 strings.Cat.time_cat(0, ',', '-', 0.001) - 407±4ns 315±6ns 0.78 tslibs.timestamp.TimestampProperties.time_dayofweek(datetime.timezone(datetime.timedelta(seconds=3600)), None) - 406±3ns 315±4ns 0.78 tslibs.timestamp.TimestampProperties.time_dayofweek(None, 'B') - 407±4ns 315±5ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(datetime.timezone.utc, 'B') - 408±4ns 316±4ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, None) - 5.50±0.1μs 4.26±0.1μs 0.77 timeseries.DatetimeIndex.time_get('dst') - 16.5±0.1ms 12.8±0.1ms 0.77 strings.Methods.time_isdigit('str') - 409±5ns 316±5ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>, 'B') - 16.1±0.1ms 12.4±0.09ms 0.77 strings.Methods.time_isspace('str') - 6.35±0.06ms 4.91±0.06ms 0.77 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'int', 'sem') - 407±3ns 315±5ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(None, None) - 408±3ns 315±4ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(datetime.timezone(datetime.timedelta(seconds=3600)), 'B') - 750±4ns 579±4ns 0.77 index_object.Float64IndexMethod.time_get_loc - 410±5ns 316±4ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(tzlocal(), None) - 839±6μs 647±5μs 0.77 series_methods.ValueCountsEA.time_value_counts(1000, True) - 654±4ms 504±5ms 0.77 io.excel.ReadExcelNRows.time_read_excel('odf') - 409±5ns 315±4ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(tzfile('/usr/share/zoneinfo/Asia/Tokyo'), None) - 409±4ns 315±5ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(datetime.timezone.utc, None) - 6.37±0.06ms 4.90±0.06ms 0.77 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'int', 'sem') - 3.70±0.1ms 2.85±0.07ms 0.77 strftime.DatetimeStrftime.time_frame_date_formatting_custom(1000) - 14.5±0.2μs 11.2±0.1μs 0.77 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 5000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 412±5ns 317±4ns 0.77 tslibs.timestamp.TimestampProperties.time_dayofweek(tzlocal(), 'B') - 603±6μs 463±3μs 0.77 groupby.GroupByMethods.time_dtype_as_group('uint', 'sum', 'direct', 5) - 6.33±0.07ms 4.86±0.04ms 0.77 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'float', 'sem') - 1.45±0.03μs 1.12±0.04μs 0.77 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, tzlocal()) - 778±10μs 597±4μs 0.77 indexing.MultiIndexing.time_loc_all_scalars(True) - 13.8±0.2μs 10.6±0.1μs 0.77 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 11000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 611±3μs 469±3μs 0.77 groupby.GroupByMethods.time_dtype_as_group('int', 'sum', 'direct', 5) - 602±4μs 462±4μs 0.77 groupby.GroupByMethods.time_dtype_as_group('int16', 'sum', 'direct', 5) - 74.7±2μs 57.1±2μs 0.76 series_methods.NanOps.time_func('var', 1000, 'boolean') - 1.45±0.02μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, tzlocal()) - 1.46±0.02μs 1.12±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 7000, tzlocal()) - 6.42±0.06ms 4.91±0.04ms 0.76 stat_ops.FrameMultiIndexOps.time_op(0, 'sem') - 1.43±0.03μs 1.09±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4000, None) - 1.46±0.03μs 1.11±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, tzlocal()) - 7.73±0.07ms 5.89±0.04ms 0.76 stat_ops.SeriesMultiIndexOps.time_op(0, 'kurt') - 589±5μs 449±3μs 0.76 groupby.GroupByMethods.time_dtype_as_group('int', 'prod', 'direct', 5) - 13.7±0.2μs 10.4±0.1μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 8000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 7.48±0.2ms 5.69±0.04ms 0.76 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'var') - 13.6±0.2μs 10.4±0.1μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 7000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 13.7±0.1μs 10.4±0.1μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 9000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 585±6μs 445±2μs 0.76 groupby.GroupByMethods.time_dtype_as_group('uint', 'prod', 'direct', 5) - 13.9±0.1μs 10.5±0.08μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 12000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.46±0.04μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, tzlocal()) - 1.44±0.03μs 1.09±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, None) - 1.46±0.02μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, tzlocal()) - 7.49±0.1ms 5.69±0.07ms 0.76 strings.Cat.time_cat(0, None, '-', 0.0) - 7.78±0.08ms 5.91±0.07ms 0.76 strings.Cat.time_cat(0, ',', '-', 0.0) - 1.46±0.04μs 1.11±0.05μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 8000, tzlocal()) - 7.78±0.1ms 5.91±0.07ms 0.76 strings.Cat.time_cat(0, ',', None, 0.0) - 585±5μs 444±3μs 0.76 groupby.GroupByMethods.time_dtype_as_group('int16', 'prod', 'direct', 5) - 13.8±0.2μs 10.5±0.1μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 4000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.46±0.04μs 1.10±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 6000, tzlocal()) - 1.46±0.03μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, tzlocal()) - 1.45±0.03μs 1.10±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, None) - 1.47±0.03μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4000, tzlocal()) - 13.5±0.2μs 10.3±0.08μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 6000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 6.42±0.06ms 4.87±0.06ms 0.76 stat_ops.FrameMultiIndexOps.time_op(1, 'sem') - 1.46±0.03μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, tzlocal()) - 1.46±0.03μs 1.11±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, tzlocal()) - 1.44±0.03μs 1.09±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2011, None) - 1.46±0.03μs 1.11±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, tzlocal()) - 1.46±0.03μs 1.10±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 11000, tzlocal()) - 1.46±0.04μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 12000, tzlocal()) - 1.43±0.04μs 1.08±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, None) - 1.46±0.02μs 1.10±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 9000, tzlocal()) - 1.46±0.04μs 1.11±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 10000, tzlocal()) - 1.44±0.03μs 1.09±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, None) - 1.46±0.02μs 1.10±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, tzlocal()) - 1.46±0.02μs 1.10±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, tzlocal()) - 1.43±0.03μs 1.08±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, None) - 13.9±0.2μs 10.5±0.1μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 4006, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.43±0.03μs 1.08±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, None) - 1.47±0.04μs 1.11±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, tzlocal()) - 1.44±0.03μs 1.09±0.03μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, None) - 1.46±0.03μs 1.10±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 6000, tzlocal()) - 1.46±0.03μs 1.10±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2011, tzlocal()) - 1.46±0.04μs 1.10±0.04μs 0.76 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, tzlocal()) - 1.47±0.02μs 1.11±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, tzlocal()) - 47.0±0.3ms 35.5±0.4ms 0.75 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'min') - 1.44±0.03μs 1.09±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, None) - 1.46±0.03μs 1.10±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, tzlocal()) - 34.8±0.9ms 26.2±0.7ms 0.75 strftime.DatetimeStrftime.time_frame_date_formatting_custom(10000) - 1.47±0.04μs 1.11±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, tzlocal()) - 13.9±0.1μs 10.5±0.1μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 8.84±0.1ms 6.66±0.1ms 0.75 frame_methods.Apply.time_apply_ref_by_name - 1.44±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, None) - 1.46±0.03μs 1.10±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 8000, tzlocal()) - 1.45±0.04μs 1.09±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 9000, None) - 1.46±0.03μs 1.10±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, tzlocal()) - 1.45±0.03μs 1.09±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 8000, None) - 7.53±0.1ms 5.66±0.08ms 0.75 ctors.DatetimeIndexConstructor.time_from_list_of_str - 1.44±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, None) - 1.45±0.02μs 1.09±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 6000, None) - 1.47±0.03μs 1.10±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, tzlocal()) - 1.47±0.04μs 1.10±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 5000, tzlocal()) - 1.44±0.03μs 1.08±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 10000, None) - 1.43±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, None) - 12.4±0.1ms 9.27±0.1ms 0.75 io.style.Render.time_tooltips_render(12, 12) - 7.59±0.1ms 5.70±0.08ms 0.75 strings.Cat.time_cat(0, None, None, 0.0) - 1.45±0.03μs 1.09±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, None) - 7.24±0.3ms 5.43±0.07ms 0.75 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'mean') - 1.44±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 12000, None) - 1.44±0.03μs 1.08±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, None) - 645±5μs 483±3μs 0.75 groupby.GroupByMethods.time_dtype_as_group('float', 'sum', 'direct', 5) - 1.45±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 11000, None) - 13.0±0.2μs 9.74±0.1μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 3000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.45±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, None) - 1.45±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 6000, None) - 1.44±0.04μs 1.08±0.04μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, None) - 8.25±0.07ms 6.17±0.06ms 0.75 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'sem') - 7.53±0.2ms 5.63±0.04ms 0.75 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'std') - 13.0±0.1μs 9.73±0.1μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 2011, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.46±0.03μs 1.09±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, None) - 1.45±0.04μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 7000, None) - 557±4μs 416±3μs 0.75 indexing.MultiIndexing.time_xs_full_key(True) - 1.44±0.03μs 1.08±0.03μs 0.75 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 5000, None) - 1.45±0.04μs 1.08±0.03μs 0.74 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, None) - 1.45±0.04μs 1.08±0.03μs 0.74 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, None) - 7.12±0.2ms 5.30±0.08ms 0.74 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'prod') - 13.2±0.2ms 9.81±0.08ms 0.74 io.style.Render.time_apply_format_hide_render(36, 12) - 13.0±0.2μs 9.68±0.09μs 0.74 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 2000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 1.45±0.04μs 1.08±0.03μs 0.74 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 8000, None) - 7.36±0.2ms 5.48±0.06ms 0.74 stat_ops.SeriesMultiIndexOps.time_op([0, 1], 'sum') - 58.1±0.3ms 43.0±0.4ms 0.74 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'first') - 13.0±0.1μs 9.59±0.1μs 0.74 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 1000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 47.2±0.3ms 34.8±0.5ms 0.74 array.ArrowStringArray.time_setitem(True) - 627±7μs 462±3μs 0.74 groupby.GroupByMethods.time_dtype_as_group('float', 'prod', 'direct', 5) - 5.02±0.1μs 3.70±0.2μs 0.74 tslibs.timestamp.TimestampOps.time_replace_None(tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 13.0±0.2μs 9.58±0.1μs 0.74 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(100, 1011, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 65.0±0.4ms 47.8±1ms 0.74 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'sum') - 4.27±0.2μs 3.11±0.06μs 0.73 tslibs.timedelta.TimedeltaConstructor.time_from_components - 37.2±0.9ms 27.1±0.8ms 0.73 strftime.DatetimeStrftime.time_frame_datetime_formatting_custom(10000) - 1.34±0.04μs 977±30ns 0.73 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 9000, datetime.timezone.utc) - 1.34±0.03μs 973±30ns 0.73 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, datetime.timezone.utc) - 55.2±0.3ms 40.1±0.5ms 0.73 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int32', 'last') - 1.34±0.03μs 970±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4000, datetime.timezone.utc) - 600±20μs 435±20μs 0.72 indexing.MultiIndexing.time_xs_full_key(False) - 1.34±0.03μs 968±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, datetime.timezone.utc) - 1.34±0.03μs 970±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, datetime.timezone.utc) - 1.34±0.03μs 968±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, datetime.timezone.utc) - 1.35±0.02μs 974±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, datetime.timezone.utc) - 1.34±0.03μs 966±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2011, datetime.timezone.utc) - 1.34±0.03μs 966±20ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 12000, datetime.timezone.utc) - 1.34±0.03μs 970±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 11000, datetime.timezone.utc) - 1.35±0.02μs 971±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, datetime.timezone.utc) - 1.34±0.03μs 964±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 6000, datetime.timezone.utc) - 24.7±0.2ms 17.8±0.2ms 0.72 array.ArrowStringArray.time_setitem(False) - 1.33±0.02μs 962±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, datetime.timezone.utc) - 1.34±0.03μs 969±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, datetime.timezone.utc) - 1.34±0.03μs 967±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 7000, datetime.timezone.utc) - 1.34±0.03μs 963±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, datetime.timezone.utc) - 1.34±0.02μs 965±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, datetime.timezone.utc) - 1.35±0.03μs 968±20ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 5000, datetime.timezone.utc) - 1.35±0.03μs 969±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, datetime.timezone.utc) - 139±0.6ms 99.4±0.8ms 0.72 reindex.Reindex.time_reindex_multiindex_no_cache - 77.7±2μs 55.7±1μs 0.72 series_methods.NanOps.time_func('var', 1000, 'Int64') - 1.34±0.04μs 964±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 6000, datetime.timezone.utc) - 1.34±0.02μs 963±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, datetime.timezone.utc) - 1.35±0.03μs 965±40ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, datetime.timezone.utc) - 1.34±0.03μs 963±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 10000, datetime.timezone.utc) - 1.35±0.04μs 966±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, datetime.timezone.utc) - 1.35±0.02μs 963±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, datetime.timezone.utc) - 1.35±0.03μs 963±20ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, datetime.timezone.utc) - 1.35±0.03μs 966±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 8000, datetime.timezone.utc) - 1.35±0.03μs 965±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, datetime.timezone.utc) - 12.7±0.2ms 9.07±0.09ms 0.72 io.style.Render.time_apply_format_hide_render(12, 120) - 1.34±0.03μs 961±30ns 0.72 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, datetime.timezone.utc) - 880±30μs 629±30μs 0.72 indexing.MultiIndexing.time_loc_all_scalars(False) - 5.81±0.2μs 4.14±0.09μs 0.71 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(10000, datetime.timezone.utc) - 1.35±0.04μs 960±20ns 0.71 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 8000, datetime.timezone.utc) - 6.12±0.07ms 4.36±0.05ms 0.71 multiindex_object.Isin.time_isin('int') - 58.3±0.4ms 41.5±2ms 0.71 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'last') - 30.6±0.7μs 21.7±0.4μs 0.71 algorithms.SortIntegerArray.time_argsort(1000) - 30.4±0.2ms 21.4±0.1ms 0.71 io.excel.ReadExcelNRows.time_read_excel('xlrd') - 2.03±0.03μs 1.43±0.03μs 0.71 tslibs.timestamp.TimestampOps.time_tz_convert(datetime.timezone.utc) - 110±0.4ms 76.4±0.6ms 0.70 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int64', 'first') - 110±0.5ms 76.1±0.6ms 0.69 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int64', 'last') - 201±3ms 139±7ms 0.69 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('int64', 'int64'), 'outer') - 27.3±0.2ms 18.8±0.2ms 0.69 ctors.DatetimeIndexConstructor.time_from_list_of_timestamps - 878±20μs 599±10μs 0.68 groupby.Categories.time_groupby_sort - 10.6±0.1ms 7.22±0.06ms 0.68 io.style.Render.time_apply_format_hide_render(24, 12) - 13.0±3ms 8.76±0.6ms 0.67 arithmetic.FrameWithFrameWide.time_op_different_blocks(<built-in function add>, (10000, 1000)) - 110±2ms 74.2±0.7ms 0.67 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int64', 'prod') - 68.9±0.5ms 46.3±0.6ms 0.67 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'var') - 4.90±0.3ms 3.27±0.3ms 0.67 replace.FillNa.time_fillna(False) - 893±20μs 593±10μs 0.66 groupby.Categories.time_groupby_ordered_sort - 10.9±0.2μs 7.22±0.1μs 0.66 series_methods.SeriesConstructor.time_constructor_fastpath - 855±20μs 564±10μs 0.66 groupby.Categories.time_groupby_extra_cat_sort - 3.56±0.04μs 2.34±0.02μs 0.66 tslibs.timestamp.TimestampOps.time_normalize(datetime.timezone.utc) - 117±0.9ms 75.6±0.6ms 0.65 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Int64', 'sum') - 5.14±0.2μs 3.33±0.1μs 0.65 tslibs.timestamp.TimestampOps.time_replace_None(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 37.6±1ms 24.3±3ms 0.65 series_methods.ValueCountsEA.time_value_counts(100000, True) - 2.20±0.06μs 1.42±0.02μs 0.64 tslibs.timestamp.TimestampOps.time_tz_localize(None) - 66.1±0.4ms 42.5±0.7ms 0.64 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'mean') - 38.7±1ms 24.7±3ms 0.64 series_methods.ValueCountsEA.time_value_counts(100000, False) - 3.57±0.05μs 2.26±0.03μs 0.63 tslibs.timestamp.TimestampOps.time_normalize(None) - 13.8±0.8ms 8.72±0.1ms 0.63 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1000000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.67±0.09ms 2.90±0.04ms 0.62 stat_ops.SeriesMultiIndexOps.time_op(1, 'median') - 4.52±0.04ms 2.81±0.04ms 0.62 stat_ops.SeriesMultiIndexOps.time_op(0, 'median') - 4.93±0.1ms 3.05±0.03ms 0.62 algorithms.Factorize.time_factorize(False, True, 'boolean') - 10.4±0.3μs 6.45±0.5μs 0.62 timeseries.DatetimeIndex.time_get('tz_aware') - 4.71±0.07ms 2.90±0.3ms 0.62 algorithms.DuplicatedMaskedArray.time_duplicated(True, False, 'Int64') - 283±4μs 174±2μs 0.61 groupby.GroupByMethods.time_dtype_as_field('int16', 'min', 'direct', 5) - 282±4μs 172±3μs 0.61 groupby.GroupByMethods.time_dtype_as_field('int16', 'first', 'direct', 5) - 7.35±0.1ms 4.45±0.02ms 0.61 io.csv.ToCSVDatetimeBig.time_frame(1000) - 3.06±0.05ms 1.84±0.04ms 0.60 series_methods.ValueCountsEA.time_value_counts(10000, True) - 3.66±0.04ms 2.20±0.03ms 0.60 stat_ops.FrameMultiIndexOps.time_op(0, 'mean') - 3.49±0.03ms 2.09±0.03ms 0.60 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'float', 'count') - 3.91±0.03ms 2.34±0.05ms 0.60 stat_ops.FrameMultiIndexOps.time_op(1, 'var') - 278±4μs 167±2μs 0.60 groupby.GroupByMethods.time_dtype_as_field('int', 'sum', 'direct', 5) - 6.50±0.1ms 3.89±0.01ms 0.60 categoricals.ValueCounts.time_value_counts(True) - 3.88±0.05ms 2.32±0.04ms 0.60 stat_ops.FrameMultiIndexOps.time_op(0, 'var') - 3.47±0.02ms 2.07±0.02ms 0.60 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 10}), 'int', 'count') - 6.52±0.1ms 3.89±0.01ms 0.60 categoricals.ValueCounts.time_value_counts(False) - 269±4μs 160±2μs 0.60 groupby.GroupByMethods.time_dtype_as_field('int', 'prod', 'direct', 5) - 3.73±0.03ms 2.22±0.02ms 0.60 stat_ops.FrameMultiIndexOps.time_op(1, 'mean') - 287±4μs 171±2μs 0.60 groupby.GroupByMethods.time_dtype_as_field('int16', 'max', 'direct', 5) - 270±4μs 160±3μs 0.59 groupby.GroupByMethods.time_dtype_as_field('uint', 'prod', 'direct', 5) - 2.55±0.1ms 1.51±0.5ms 0.59 algorithms.SortIntegerArray.time_argsort(100000) - 3.48±0.03ms 2.06±0.02ms 0.59 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'int', 'count') - 250±4μs 148±2μs 0.59 groupby.GroupByMethods.time_dtype_as_field('int16', 'min', 'direct', 1) - 278±3μs 165±3μs 0.59 groupby.GroupByMethods.time_dtype_as_field('uint', 'sum', 'direct', 5) - 247±4μs 146±2μs 0.59 groupby.GroupByMethods.time_dtype_as_field('int16', 'first', 'direct', 1) - 57.8±0.4ms 34.2±1ms 0.59 groupby.GroupByCythonAggEaDtypes.time_frame_agg('Float64', 'prod') - 3.51±0.02ms 2.08±0.03ms 0.59 rolling.Methods.time_method('DataFrame', ('rolling', {'window': 1000}), 'float', 'count') - 3.69±0.04ms 2.17±0.03ms 0.59 stat_ops.FrameMultiIndexOps.time_op(0, 'sum') - 4.33±0.03ms 2.55±0.02ms 0.59 stat_ops.SeriesMultiIndexOps.time_op(1, 'sem') - 3.73±0.05ms 2.19±0.02ms 0.59 stat_ops.FrameMultiIndexOps.time_op(1, 'sum') - 4.36±0.05ms 2.55±0.01ms 0.58 stat_ops.SeriesMultiIndexOps.time_op(0, 'sem') - 103±2ms 60.0±2ms 0.58 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('Int64', 'Int64'), 'inner') - 3.39±0.02ms 1.97±0.03ms 0.58 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'float', 'count') - 3.35±0.03ms 1.95±0.03ms 0.58 rolling.Methods.time_method('Series', ('rolling', {'window': 1000}), 'int', 'count') - 3.86±0.04ms 2.24±0.04ms 0.58 stat_ops.FrameMultiIndexOps.time_op(1, 'std') - 3.41±0.02ms 1.98±0.03ms 0.58 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'float', 'count') - 242±3μs 140±2μs 0.58 groupby.GroupByMethods.time_dtype_as_field('uint', 'sum', 'direct', 1) - 3.79±0.05ms 2.20±0.03ms 0.58 stat_ops.FrameMultiIndexOps.time_op(0, 'std') - 252±4μs 146±2μs 0.58 groupby.GroupByMethods.time_dtype_as_field('int16', 'max', 'direct', 1) - 3.37±0.03ms 1.94±0.02ms 0.58 rolling.Methods.time_method('Series', ('rolling', {'window': 10}), 'int', 'count') - 235±4μs 136±2μs 0.58 groupby.GroupByMethods.time_dtype_as_field('int', 'prod', 'direct', 1) - 3.48±0.04ms 2.01±0.02ms 0.58 stat_ops.FrameMultiIndexOps.time_op(0, 'prod') - 236±5μs 136±3μs 0.58 groupby.GroupByMethods.time_dtype_as_field('uint', 'prod', 'direct', 1) - 243±4μs 140±2μs 0.58 groupby.GroupByMethods.time_dtype_as_field('int', 'sum', 'direct', 1) - 690±9ms 397±2ms 0.58 io.csv.ToCSVDatetimeBig.time_frame(100000) - 258±4μs 148±3μs 0.58 groupby.GroupByMethods.time_dtype_as_group('float', 'sum', 'direct', 1) - 250±4μs 144±2μs 0.58 groupby.GroupByMethods.time_dtype_as_group('int', 'sum', 'direct', 1) - 7.93±0.1ms 4.56±0.04ms 0.58 io.style.Render.time_apply_format_hide_render(12, 12) - 68.5±1ms 39.3±0.1ms 0.57 io.csv.ToCSVDatetimeBig.time_frame(10000) - 3.49±0.08ms 2.00±0.05ms 0.57 strftime.BusinessHourStrftime.time_frame_offset_repr(1000) - 251±4μs 144±3μs 0.57 groupby.GroupByMethods.time_dtype_as_group('uint', 'sum', 'direct', 1) - 251±3μs 144±3μs 0.57 groupby.GroupByMethods.time_dtype_as_group('int16', 'sum', 'direct', 1) - 1.09±0.01ms 624±6μs 0.57 series_methods.ValueCountsEA.time_value_counts(1000, False) - 3.62±0.09ms 2.07±0.05ms 0.57 strftime.BusinessHourStrftime.time_frame_offset_str(1000) - 275±5μs 156±3μs 0.57 groupby.GroupByMethods.time_dtype_as_field('int16', 'last', 'direct', 5) - 243±5μs 138±3μs 0.57 groupby.GroupByMethods.time_dtype_as_group('int', 'prod', 'direct', 1) - 243±4μs 138±3μs 0.57 groupby.GroupByMethods.time_dtype_as_group('uint', 'prod', 'direct', 1) - 243±5μs 137±3μs 0.57 groupby.GroupByMethods.time_dtype_as_group('int16', 'prod', 'direct', 1) - 3.45±0.04ms 1.95±0.02ms 0.57 stat_ops.FrameMultiIndexOps.time_op(1, 'prod') - 250±5μs 141±2μs 0.57 groupby.GroupByMethods.time_dtype_as_group('float', 'prod', 'direct', 1) - 4.48±0.4ms 2.53±0.01ms 0.56 algorithms.Factorize.time_factorize(False, False, 'boolean') - 245±7μs 137±3μs 0.56 groupby.GroupByMethods.time_dtype_as_field('int16', 'last', 'direct', 1) - 53.7±0.4ms 29.9±0.5ms 0.56 index_cached_properties.IndexCache.time_values('MultiIndex') - 3.38±0.05ms 1.87±0.04ms 0.55 series_methods.ValueCountsEA.time_value_counts(10000, False) - 1.62±0.04μs 895±10ns 0.55 tslibs.timedelta.TimedeltaConstructor.time_from_np_timedelta - 78.6±1ms 43.5±0.6ms 0.55 multiindex_object.GetLoc.time_large_get_loc_warm - 6.75±0.2μs 3.73±0.04μs 0.55 libs.InferDtype.time_infer_dtype_skipna('empty') - 7.37±0.2μs 4.07±0.1μs 0.55 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(100, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 34.2±0.8ms 18.5±0.3ms 0.54 strftime.BusinessHourStrftime.time_frame_offset_repr(10000) - 35.7±0.7ms 19.2±0.4ms 0.54 strftime.BusinessHourStrftime.time_frame_offset_str(10000) - 3.87±0.05ms 2.07±0.03ms 0.54 stat_ops.SeriesMultiIndexOps.time_op(0, 'var') - 40.2±0.3μs 21.2±0.2μs 0.53 frame_methods.XS.time_frame_xs(0) - 3.90±0.06ms 2.06±0.02ms 0.53 stat_ops.SeriesMultiIndexOps.time_op(1, 'var') - 37.4±1ms 19.8±0.8ms 0.53 multiindex_object.SetOperations.time_operation('monotonic', 'string', 'symmetric_difference', None) - 38.3±1ms 20.2±0.4ms 0.53 multiindex_object.SetOperations.time_operation('non_monotonic', 'string', 'symmetric_difference', None) - 3.83±0.07ms 2.01±0.02ms 0.53 stat_ops.SeriesMultiIndexOps.time_op(0, 'std') - 37.8±0.7ms 19.8±0.5ms 0.52 multiindex_object.SetOperations.time_operation('monotonic', 'ea_int', 'symmetric_difference', None) - 37.9±1ms 19.8±0.5ms 0.52 multiindex_object.SetOperations.time_operation('non_monotonic', 'ea_int', 'symmetric_difference', None) - 334±2ms 174±2ms 0.52 groupby.Transform.time_transform_lambda_max_tall - 87.0±6ms 44.6±5ms 0.51 multiindex_object.SetOperations.time_operation('non_monotonic', 'int', 'union', None) - 37.6±1ms 19.2±0.7ms 0.51 multiindex_object.SetOperations.time_operation('non_monotonic', 'string', 'symmetric_difference', False) - 154±1μs 78.5±0.7μs 0.51 tslibs.period.PeriodConstructor.time_period_constructor('D', True) - 154±1μs 78.4±1μs 0.51 tslibs.period.PeriodConstructor.time_period_constructor('D', False) - 3.62±0.05ms 1.85±0.02ms 0.51 stat_ops.SeriesMultiIndexOps.time_op(1, 'mean') - 3.91±0.08ms 1.99±0.03ms 0.51 stat_ops.SeriesMultiIndexOps.time_op(1, 'std') - 3.67±0.05ms 1.86±0.04ms 0.51 stat_ops.SeriesMultiIndexOps.time_op(0, 'sum') - 3.59±0.08ms 1.81±0.02ms 0.50 stat_ops.SeriesMultiIndexOps.time_op(0, 'mean') - 6.98±0.1ms 3.51±0.07ms 0.50 algorithms.DuplicatedMaskedArray.time_duplicated(True, False, 'Float64') - 3.65±0.08ms 1.83±0.02ms 0.50 stat_ops.SeriesMultiIndexOps.time_op(1, 'sum') - 87.8±6ms 43.9±1ms 0.50 multiindex_object.SetOperations.time_operation('monotonic', 'int', 'union', None) - 1.06±0.02ms 529±7μs 0.50 replace.FillNa.time_fillna(True) - 38.6±1ms 19.1±0.8ms 0.50 multiindex_object.SetOperations.time_operation('monotonic', 'ea_int', 'symmetric_difference', False) - 4.33±0.07ms 2.14±0.03ms 0.49 algorithms.DuplicatedMaskedArray.time_duplicated(True, 'last', 'Float64') - 38.6±1ms 19.0±0.7ms 0.49 multiindex_object.SetOperations.time_operation('monotonic', 'string', 'symmetric_difference', False) - 5.22±0.09μs 2.57±0.2μs 0.49 tslibs.timestamp.TimestampOps.time_tz_convert(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 1.66±0.02μs 820±20ns 0.49 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1, datetime.timezone.utc) - 3.34±0.05ms 1.64±0.03ms 0.49 stat_ops.SeriesMultiIndexOps.time_op(0, 'prod') - 88.7±5ms 43.5±5ms 0.49 multiindex_object.SetOperations.time_operation('non_monotonic', 'ea_int', 'union', None) - 88.9±1ms 43.4±0.7ms 0.49 multiindex_object.SetOperations.time_operation('monotonic', 'ea_int', 'union', None) - 3.07±0.03ms 1.50±0.02ms 0.49 frame_methods.Lookup.time_frame_fancy_lookup - 1.73±0.03μs 835±10ns 0.48 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(100, datetime.timezone.utc) - 10.7±3ms 5.12±0.1ms 0.48 arithmetic.FrameWithFrameWide.time_op_same_blocks(<built-in function add>, (10000, 1000)) - 25.6±0.2ms 12.3±0.1ms 0.48 io.sas.SAS.time_read_sas7bdat - 338±3μs 162±2μs 0.48 indexing.SortedAndUnsortedDatetimeIndexLoc.time_loc_unsorted - 94.7±3ms 45.3±3ms 0.48 algorithms.Factorize.time_factorize(False, True, 'string[pyarrow]') - 3.42±0.05ms 1.62±0.03ms 0.47 stat_ops.SeriesMultiIndexOps.time_op(1, 'prod') - 351±3μs 166±2μs 0.47 algos.isin.IsIn.time_isin_categorical('boolean') - 1.72±0.01ms 810±3μs 0.47 indexing.CategoricalIndexIndexing.time_getitem_list('non_monotonic') - 1.72±0.01ms 810±3μs 0.47 indexing.CategoricalIndexIndexing.time_getitem_list('monotonic_decr') - 1.72±0.01ms 808±3μs 0.47 indexing.CategoricalIndexIndexing.time_getitem_list('monotonic_incr') - 1.71±0.01ms 802±4μs 0.47 categoricals.CategoricalSlicing.time_getitem_list('monotonic_decr') - 1.71±0.01ms 802±5μs 0.47 categoricals.CategoricalSlicing.time_getitem_list('non_monotonic') - 1.71±0.01ms 801±4μs 0.47 categoricals.CategoricalSlicing.time_getitem_list('monotonic_incr') - 5.81±0.03ms 2.72±0.02ms 0.47 libs.InferDtype.time_infer_dtype_skipna('py-object') - 6.28±0.1μs 2.91±0.2μs 0.46 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 3.39±0.03ms 1.57±0.01ms 0.46 join_merge.Merge.time_merge_dataframe_empty_left(False) - 3.23±0.05ms 1.49±0.04ms 0.46 algorithms.DuplicatedMaskedArray.time_duplicated(True, 'last', 'Int64') - 5.73±0.2μs 2.63±0.2μs 0.46 tslibs.timestamp.TimestampOps.time_tz_convert(tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 76.1±6ms 34.7±4ms 0.46 multiindex_object.SetOperations.time_operation('non_monotonic', 'string', 'union', False) - 103±6ms 47.0±5ms 0.45 multiindex_object.SetOperations.time_operation('non_monotonic', 'string', 'union', None) - 28.0±0.2ms 12.7±0.2ms 0.45 ctors.DatetimeIndexConstructor.time_from_list_of_datetimes - 76.8±7ms 34.8±5ms 0.45 multiindex_object.SetOperations.time_operation('monotonic', 'string', 'union', False) - 103±7ms 46.5±0.8ms 0.45 multiindex_object.SetOperations.time_operation('monotonic', 'string', 'union', None) - 6.19±0.2μs 2.79±0.2μs 0.45 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 327±2μs 146±2μs 0.45 algos.isin.IsIn.time_isin_categorical('bool') - 85.1±1ms 38.0±1ms 0.45 algorithms.Factorize.time_factorize(True, True, 'string[pyarrow]') - 214±4μs 95.3±2μs 0.45 groupby.GroupByMethods.time_dtype_as_group('float', 'cumprod', 'direct', 1) - 27.5±0.2ms 12.2±0.04ms 0.44 ctors.DatetimeIndexConstructor.time_from_list_of_dates - 233±4μs 103±1μs 0.44 groupby.GroupByMethods.time_dtype_as_field('uint', 'cumprod', 'direct', 5) - 213±4μs 93.6±1μs 0.44 groupby.GroupByMethods.time_dtype_as_field('uint', 'cumprod', 'direct', 1) - 4.98±0.07ms 2.19±0.03ms 0.44 algorithms.DuplicatedMaskedArray.time_duplicated(True, 'first', 'Float64') - 213±4μs 93.4±1μs 0.44 groupby.GroupByMethods.time_dtype_as_group('uint', 'cumprod', 'direct', 1) - 213±4μs 93.4±1μs 0.44 groupby.GroupByMethods.time_dtype_as_group('int', 'cumprod', 'direct', 1) - 214±4μs 93.3±1μs 0.44 groupby.GroupByMethods.time_dtype_as_group('int16', 'cumprod', 'direct', 1) - 5.78±0.02ms 2.51±0.02ms 0.44 libs.InferDtype.time_infer_dtype_skipna('bytes') - 213±4μs 92.7±1μs 0.43 groupby.GroupByMethods.time_dtype_as_field('int', 'cumprod', 'direct', 1) - 234±4μs 102±1μs 0.43 groupby.GroupByMethods.time_dtype_as_field('int', 'cumprod', 'direct', 5) - 3.84±0.07ms 1.67±0.02ms 0.43 io.sas.SAS.time_read_xpt - 5.91±0.2μs 2.56±0.2μs 0.43 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 6.05±0.2μs 2.60±0.2μs 0.43 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 298±4μs 126±2μs 0.42 groupby.GroupByMethods.time_dtype_as_group('float', 'cumprod', 'direct', 5) - 5.72±0.1μs 2.39±0.2μs 0.42 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 218±4μs 90.9±1μs 0.42 groupby.GroupByMethods.time_dtype_as_field('int16', 'cummax', 'direct', 1) - 295±5μs 123±2μs 0.42 groupby.GroupByMethods.time_dtype_as_group('int16', 'cumprod', 'direct', 5) - 299±5μs 124±2μs 0.42 groupby.GroupByMethods.time_dtype_as_group('int', 'cumprod', 'direct', 5) - 241±4μs 99.8±1μs 0.41 groupby.GroupByMethods.time_dtype_as_field('int16', 'cummax', 'direct', 5) - 296±4μs 122±2μs 0.41 groupby.GroupByMethods.time_dtype_as_group('uint', 'cumprod', 'direct', 5) - 5.95±0.2μs 2.46±0.2μs 0.41 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 41.6±1ms 17.1±0.4ms 0.41 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('int64', 'int64'), 'right') - 315±2μs 130±3μs 0.41 indexing.SortedAndUnsortedDatetimeIndexLoc.time_loc_sorted - 218±5μs 89.0±1μs 0.41 groupby.GroupByMethods.time_dtype_as_field('int16', 'cummin', 'direct', 1) - 240±4μs 97.7±0.9μs 0.41 groupby.GroupByMethods.time_dtype_as_field('int16', 'cummin', 'direct', 5) - 42.0±1ms 16.8±0.3ms 0.40 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('int64', 'int64'), 'left') - 85.0±7ms 33.8±5ms 0.40 multiindex_object.SetOperations.time_operation('monotonic', 'int', 'union', False) - 85.6±2ms 33.8±5ms 0.39 multiindex_object.SetOperations.time_operation('non_monotonic', 'ea_int', 'union', False) - 19.0±1ms 7.45±0.07ms 0.39 frame_methods.Duplicated.time_frame_duplicated_subset - 5.10±0.2μs 1.99±0.1μs 0.39 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 37.4±0.9ms 14.6±0.3ms 0.39 multiindex_object.SetOperations.time_operation('non_monotonic', 'ea_int', 'symmetric_difference', False) - 3.82±0.1ms 1.49±0.04ms 0.39 algorithms.DuplicatedMaskedArray.time_duplicated(True, 'first', 'Int64') - 5.11±0.2μs 1.99±0.1μs 0.39 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.09±0.2μs 1.97±0.1μs 0.39 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 7.09±0.2μs 2.73±0.1μs 0.39 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(100, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.11±0.2μs 1.95±0.1μs 0.38 tslibs.resolution.TimeResolution.time_get_resolution('D', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 35.0±1ms 13.3±0.2ms 0.38 multiindex_object.SetOperations.time_operation('non_monotonic', 'int', 'symmetric_difference', None) - 35.3±1ms 13.4±0.2ms 0.38 multiindex_object.SetOperations.time_operation('monotonic', 'int', 'symmetric_difference', None) - 84.2±6ms 31.8±4ms 0.38 multiindex_object.SetOperations.time_operation('non_monotonic', 'int', 'union', False) - 5.15±0.1μs 1.93±0.1μs 0.37 tslibs.resolution.TimeResolution.time_get_resolution('h', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.20±0.1μs 1.95±0.2μs 0.37 tslibs.resolution.TimeResolution.time_get_resolution('m', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.72±0.2μs 1.74±0.1μs 0.37 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('time', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 5.22±0.2μs 1.93±0.1μs 0.37 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 86.2±2ms 31.7±1ms 0.37 multiindex_object.SetOperations.time_operation('monotonic', 'ea_int', 'union', False) - 4.86±0.1μs 1.79±0.1μs 0.37 tslibs.resolution.TimeResolution.time_get_resolution('D', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.84±0.1μs 1.77±0.1μs 0.37 tslibs.resolution.TimeResolution.time_get_resolution('m', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.87±0.1μs 1.79±0.1μs 0.37 tslibs.resolution.TimeResolution.time_get_resolution('ns', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 34.9±1ms 12.7±0.2ms 0.36 multiindex_object.SetOperations.time_operation('non_monotonic', 'int', 'symmetric_difference', False) - 4.87±0.1μs 1.77±0.1μs 0.36 tslibs.resolution.TimeResolution.time_get_resolution('s', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.87±0.1μs 1.77±0.1μs 0.36 tslibs.resolution.TimeResolution.time_get_resolution('us', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.88±0.1μs 1.77±0.1μs 0.36 tslibs.resolution.TimeResolution.time_get_resolution('h', 0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.21±0.2μs 1.89±0.1μs 0.36 tslibs.resolution.TimeResolution.time_get_resolution('us', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.17±0.1μs 1.86±0.1μs 0.36 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.83±0.2μs 1.73±0.1μs 0.36 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('datetime', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.75±0.1μs 1.69±0.1μs 0.36 tslibs.tslib.TimeIntsToPydatetime.time_ints_to_pydatetime('timestamp', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 35.6±1ms 12.7±0.2ms 0.36 multiindex_object.SetOperations.time_operation('monotonic', 'int', 'symmetric_difference', False) - 35.7±5ms 12.6±4ms 0.35 reindex.DropDuplicates.time_frame_drop_dups_int(False) - 7.21±0.06ms 2.54±0.03ms 0.35 groupby.Categories.time_groupby_ordered_nosort - 131±4ms 45.8±0.2ms 0.35 frame_methods.ToDict.time_to_dict_datetimelike('index') - 4.81±0.2μs 1.66±0.08μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('us', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 3.45±0.1μs 1.18±0.01μs 0.34 tslibs.timedelta.TimedeltaConstructor.time_from_datetime_timedelta - 4.88±0.2μs 1.66±0.09μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('m', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.85±0.2μs 1.65±0.08μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('ns', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.48±0.07μs 1.51±0.08μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('s', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.91±0.1μs 1.66±0.07μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('s', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.89±0.2μs 1.65±0.07μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('h', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.49±0.1μs 1.51±0.06μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('D', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.89±0.2μs 1.65±0.08μs 0.34 tslibs.resolution.TimeResolution.time_get_resolution('D', 1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 5.07±0.1μs 1.71±0.1μs 0.34 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.29±0.1ms 1.44±0.01ms 0.34 strftime.DatetimeStrftime.time_frame_datetime_formatting_default_with_float(1000) - 4.52±0.2μs 1.51±0.07μs 0.33 tslibs.resolution.TimeResolution.time_get_resolution('us', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 5.03±0.2μs 1.68±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 9000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.53±0.1μs 1.51±0.07μs 0.33 tslibs.resolution.TimeResolution.time_get_resolution('m', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.53±0.09μs 1.51±0.07μs 0.33 tslibs.resolution.TimeResolution.time_get_resolution('h', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 5.11±0.2μs 1.70±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.49±0.1μs 1.49±0.08μs 0.33 tslibs.resolution.TimeResolution.time_get_resolution('ns', 0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 33.3±0.7μs 11.1±0.7μs 0.33 tslibs.timestamp.TimestampOps.time_normalize(<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 5.11±0.2μs 1.70±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.13±0.2μs 1.70±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.10±0.2μs 1.69±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 5000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.15±0.2μs 1.70±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 6000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.07±0.2μs 1.67±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.12±0.2μs 1.69±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.06±0.2μs 1.67±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 10000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.16±0.2μs 1.70±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 8000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.10±0.1μs 1.67±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.13±0.2μs 1.68±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.14±0.2μs 1.68±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.17±0.1μs 1.69±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.18±0.2μs 1.69±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 8000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.15±0.2μs 1.68±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.11±0.1μs 1.67±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.17±0.2μs 1.69±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 11000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.16±0.1μs 1.68±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.15±0.1μs 1.67±0.1μs 0.33 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.14±0.2μs 1.67±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 6000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.16±0.1μs 1.67±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 7000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.14±0.2μs 1.67±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2011, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.14±0.1μs 1.67±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.18±0.2μs 1.68±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.17±0.2μs 1.68±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 7.64±0.06ms 2.48±0.04ms 0.32 groupby.Categories.time_groupby_nosort - 144±4ms 46.5±0.2ms 0.32 frame_methods.ToDict.time_to_dict_datetimelike('records') - 5.15±0.2μs 1.67±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.21±0.1μs 1.68±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 12000, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 5.18±0.2μs 1.67±0.1μs 0.32 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 3.78±0.1ms 1.21±0.01ms 0.32 strftime.DatetimeStrftime.time_frame_datetime_formatting_default(1000) - 3.94±0.02μs 1.26±0.01μs 0.32 index_object.Range.time_sort_values_des - 34.2±0.9μs 10.8±0.7μs 0.31 tslibs.timestamp.TimestampOps.time_normalize(tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 45.9±0.6ms 14.3±0.2ms 0.31 join_merge.JoinMultiindexSubset.time_join_multiindex_subset - 4.68±0.1μs 1.45±0.09μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 8000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.68±0.1μs 1.45±0.08μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.68±0.1μs 1.45±0.09μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 6000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.65±0.2μs 1.43±0.09μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 12000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.70±0.1μs 1.45±0.09μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 5000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.69±0.1μs 1.44±0.08μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.71±0.2μs 1.44±0.09μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.68±0.2μs 1.43±0.08μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 41.8±1ms 12.8±0.08ms 0.31 strftime.DatetimeStrftime.time_frame_datetime_formatting_default_with_float(10000) - 4.70±0.1μs 1.44±0.09μs 0.31 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 33.7±0.1ms 10.3±0.1ms 0.31 index_object.SetOperations.time_operation('monotonic', 'ea_int', 'intersection') - 6.84±0.07ms 2.09±0.05ms 0.31 groupby.Categories.time_groupby_extra_cat_nosort - 4.69±0.09μs 1.43±0.1μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 12000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.70±0.09μs 1.43±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 9000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.69±0.2μs 1.43±0.1μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 3000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.69±0.2μs 1.43±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 9000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.73±0.2μs 1.44±0.07μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.70±0.2μs 1.43±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.68±0.2μs 1.42±0.08μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 6000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.71±0.1μs 1.43±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.72±0.2μs 1.43±0.07μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.73±0.1μs 1.43±0.07μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 5000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.71±0.06μs 1.43±0.08μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 91.2±2ms 27.6±0.6ms 0.30 multiindex_object.SetOperations.time_operation('monotonic', 'ea_int', 'intersection', None) - 4.75±0.1μs 1.44±0.07μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 2000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.73±0.2μs 1.43±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 1011, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.71±0.1μs 1.42±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 7000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.72±0.1μs 1.42±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 1000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.74±0.1μs 1.43±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 11000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.77±0.2μs 1.44±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 11000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.73±0.09μs 1.42±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 4006, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.78±0.1μs 1.44±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(1, 10000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.75±0.1μs 1.42±0.09μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 8000, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 4.96±0.05ms 1.48±0.02ms 0.30 categoricals.Rank.time_rank_string_cat_ordered - 4.40±0.1ms 1.31±0.2ms 0.30 reindex.DropDuplicates.time_frame_drop_dups_int(True) - 4.80±0.1μs 1.42±0.08μs 0.30 tslibs.period.TimeDT64ArrToPeriodArr.time_dt64arr_to_periodarr(0, 4006, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 90.1±2ms 26.2±0.6ms 0.29 multiindex_object.SetOperations.time_operation('monotonic', 'int', 'intersection', None) - 137±4ms 39.4±0.3ms 0.29 frame_methods.ToDict.time_to_dict_datetimelike('dict') - 21.1±0.3ms 6.02±0.1ms 0.28 index_object.UnionWithDuplicates.time_union_with_duplicates - 36.9±0.9ms 10.4±0.08ms 0.28 strftime.DatetimeStrftime.time_frame_datetime_formatting_default(10000) - 135±4ms 38.0±0.2ms 0.28 frame_methods.ToDict.time_to_dict_datetimelike('split') - 6.51±0.2μs 1.83±0.1μs 0.28 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 121±4ms 34.1±0.3ms 0.28 frame_methods.ToDict.time_to_dict_datetimelike('list') - 4.97±0.05ms 1.39±0.02ms 0.28 categoricals.Rank.time_rank_int_cat_ordered - 304±2ms 84.0±4ms 0.28 multiindex_object.SetOperations.time_operation('monotonic', 'datetime', 'union', None) - 305±3ms 83.6±0.4ms 0.27 multiindex_object.SetOperations.time_operation('non_monotonic', 'datetime', 'union', None) - 91.6±2ms 24.5±0.3ms 0.27 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('int64', 'int64'), 'inner') - 6.17±0.2μs 1.61±0.09μs 0.26 tslibs.tz_convert.TimeTZConvert.time_tz_convert_from_utc(1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 2.17±0.02ms 564±3μs 0.26 join_merge.Append.time_append_mixed - 46.2±2ms 11.7±0.7ms 0.25 indexing.MultiIndexing.time_loc_slice_plus_null_slice(False) - 296±2ms 74.5±2ms 0.25 multiindex_object.SetOperations.time_operation('monotonic', 'datetime', 'union', False) - 296±3ms 73.8±2ms 0.25 multiindex_object.SetOperations.time_operation('non_monotonic', 'datetime', 'union', False) - 15.4±0.3μs 3.81±0.2μs 0.25 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 18.3±0.4μs 4.48±0.4μs 0.24 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(0, datetime.timezone(datetime.timedelta(seconds=3600))) - 15.1±0.3μs 3.68±0.2μs 0.24 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 29.8±0.1ms 7.16±0.1ms 0.24 index_object.SetOperations.time_operation('monotonic', 'ea_int', 'union') - 14.4±0.2μs 3.41±0.1μs 0.24 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(0, tzfile('/usr/share/zoneinfo/Asia/Tokyo')) - 4.01±0.01ms 939±4μs 0.23 libs.InferDtype.time_infer_dtype_skipna('np-object') - 24.9±0.8ms 5.79±0.2ms 0.23 algorithms.DuplicatedMaskedArray.time_duplicated(False, 'last', 'Float64') - 13.8±0.1ms 3.19±0.04ms 0.23 multiindex_object.Difference.time_difference('int') - 19.6±0.3μs 4.52±0.4μs 0.23 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1, datetime.timezone(datetime.timedelta(seconds=3600))) - 14.7±0.2ms 3.40±0.03ms 0.23 multiindex_object.Difference.time_difference('ea_int') - 30.8±2ms 7.09±2ms 0.23 algorithms.DuplicatedMaskedArray.time_duplicated(False, False, 'Float64') - 14.2±0.2μs 3.17±0.1μs 0.22 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(0, <DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>) - 6.74±0.07ms 1.49±0.01ms 0.22 indexing.MultiIndexing.time_loc_all_slices(True) - 64.3±0.4ms 13.9±0.01ms 0.22 timeseries.Iteration.time_iter_preexit(<function timedelta_range at 0x7f68e0104670>) - 21.8±0.3μs 4.57±0.4μs 0.21 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(100, datetime.timezone(datetime.timedelta(seconds=3600))) - 182±6ms 38.2±0.4ms 0.21 indexing.MultiIndexing.time_loc_all_lists(True) - 1.53±0.4ms 313±10μs 0.20 indexing.MultiIndexing.time_loc_partial_key_scalar(False) - 3.13±0.06s 639±1ms 0.20 timeseries.Iteration.time_iter(<function timedelta_range at 0x7f68e0104670>) - 1.53±0.4ms 307±10μs 0.20 indexing.MultiIndexing.time_xs_level_0(False) - 16.6±0.1ms 3.34±0.03ms 0.20 multiindex_object.Difference.time_difference('string') - 3.70±0.08ms 728±3μs 0.20 strftime.DatetimeStrftime.time_frame_datetime_formatting_default_date_only(1000) - 147±1ms 28.9±0.4ms 0.20 multiindex_object.SetOperations.time_operation('monotonic', 'string', 'intersection', None) - 3.69±0.1ms 724±3μs 0.20 strftime.DatetimeStrftime.time_frame_date_formatting_default(1000) - 28.3±1ms 5.46±0.3ms 0.19 algorithms.DuplicatedMaskedArray.time_duplicated(False, 'first', 'Float64') - 151±1ms 28.9±0.4ms 0.19 multiindex_object.SetOperations.time_operation('non_monotonic', 'string', 'intersection', None) - 21.8±0.1ms 3.85±0.1ms 0.18 algorithms.DuplicatedMaskedArray.time_duplicated(False, 'last', 'Int64') - 3.57±0.07ms 630±2μs 0.18 strftime.DatetimeStrftime.time_frame_date_to_str(1000) - 72.9±1ms 12.8±0.2ms 0.18 multiindex_object.SetOperations.time_operation('non_monotonic', 'string', 'intersection', False) - 152±1ms 26.5±0.3ms 0.17 io.excel.ReadExcelNRows.time_read_excel('openpyxl') - 1.71±0.07ms 298±3μs 0.17 indexing.MultiIndexing.time_loc_partial_key_scalar(True) - 58.8±0.2ms 10.2±0.5ms 0.17 hash_functions.Unique.time_unique('Float64') - 1.68±0.09ms 292±3μs 0.17 indexing.MultiIndexing.time_xs_level_0(True) - 1.90±0.01ms 328±2μs 0.17 join_merge.Append.time_append_homogenous - 73.0±1ms 12.6±0.2ms 0.17 multiindex_object.SetOperations.time_operation('monotonic', 'string', 'intersection', False) - 31.8±0.1ms 5.30±0.02ms 0.17 hash_functions.Unique.time_unique_with_duplicates('Float64') - 162±1ms 26.7±0.5ms 0.17 multiindex_object.SetOperations.time_operation('non_monotonic', 'ea_int', 'intersection', None) - 160±1ms 25.5±0.6ms 0.16 multiindex_object.SetOperations.time_operation('non_monotonic', 'int', 'intersection', None) - 34.7±1ms 5.51±0.02ms 0.16 strftime.DatetimeStrftime.time_frame_datetime_formatting_default_date_only(10000) - 26.7±2ms 4.23±0.9ms 0.16 algorithms.DuplicatedMaskedArray.time_duplicated(False, False, 'Int64') - 34.8±0.9ms 5.48±0.02ms 0.16 strftime.DatetimeStrftime.time_frame_date_formatting_default(10000) - 25.4±1ms 3.99±0.1ms 0.16 algorithms.DuplicatedMaskedArray.time_duplicated(False, 'first', 'Int64') - 597±6μs 93.3±2μs 0.16 multiindex_object.GetLocs.time_small_get_locs - 59.2±0.7ms 9.17±0.2ms 0.15 period.PeriodIndexConstructor.time_from_ints_daily('D', False) - 59.3±0.6ms 9.08±0.2ms 0.15 period.PeriodIndexConstructor.time_from_ints_daily('D', True) - 35.8±0.9ms 5.47±0.01ms 0.15 strftime.DatetimeStrftime.time_frame_date_to_str(10000) - 81.8±1ms 12.3±0.2ms 0.15 multiindex_object.SetOperations.time_operation('non_monotonic', 'ea_int', 'intersection', False) - 2.03±0.03μs 289±5ns 0.14 index_object.Range.time_sort_values_asc - 145±0.3ms 20.5±0.5ms 0.14 groupby.Cumulative.time_frame_transform('Float64', 'cumsum') - 1.39±0.4ms 196±6μs 0.14 indexing.MultiIndexing.time_loc_partial_key_slice(False) - 774±8μs 107±2μs 0.14 multiindex_object.GetLocs.time_med_get_locs - 71.6±1ms 9.85±0.6ms 0.14 indexing.MultiIndexing.time_loc_all_slices(False) - 90.8±2ms 12.4±0.3ms 0.14 multiindex_object.SetOperations.time_operation('monotonic', 'ea_int', 'intersection', False) - 25.8±0.2ms 3.48±0.1ms 0.14 hash_functions.Unique.time_unique_with_duplicates('Int64') - 80.1±1ms 10.8±0.2ms 0.13 multiindex_object.SetOperations.time_operation('non_monotonic', 'int', 'intersection', False) - 63.1±0.3ms 7.90±0.07ms 0.13 multiindex_object.Values.time_datetime_level_values_copy - 1.64±0.08ms 205±2μs 0.12 indexing.MultiIndexing.time_loc_partial_key_slice(True) - 58.5±0.3ms 7.28±0.3ms 0.12 hash_functions.Unique.time_unique('Int64') - 12.5±0.1ms 1.56±0.01ms 0.12 join_merge.Merge.time_merge_dataframe_empty_right(False) - 88.7±2ms 11.0±0.2ms 0.12 multiindex_object.SetOperations.time_operation('monotonic', 'int', 'intersection', False) - 201±1ms 24.6±0.3ms 0.12 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('datetime64[ns]', 'int64'), 'inner') - 102±4ms 12.4±0.8ms 0.12 indexing.MultiIndexing.time_loc_null_slice_plus_slice(False) - 725±20ms 87.1±3ms 0.12 groupby.Transform.time_transform_lambda_max_wide - 160±0.4ms 18.9±0.5ms 0.12 groupby.Cumulative.time_frame_transform('Int64', 'cumsum') - 13.6±0.08ms 1.57±0.01ms 0.12 join_merge.Merge.time_merge_dataframe_empty_left(True) - 5.61±0.07ms 645±5μs 0.12 indexing.MultiIndexing.time_loc_slice_plus_null_slice(True) - 28.1±0.08ms 3.09±0.01ms 0.11 frame_ctor.FromScalar.time_frame_from_scalar_ea_float64 - 157±2ms 17.1±0.3ms 0.11 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('datetime64[ns]', 'int64'), 'right') - 191±0.7ms 20.7±0.2ms 0.11 groupby.Cumulative.time_frame_transform_many_nulls('Float64', 'cumsum') - 30.9±0.2ms 3.27±0.04ms 0.11 multiindex_object.Difference.time_difference('datetime') - 158±1ms 16.6±0.3ms 0.11 join_merge.MergeMultiIndex.time_merge_sorted_multiindex(('datetime64[ns]', 'int64'), 'left') - 672±3ms 69.2±0.8ms 0.10 reindex.Reindex.time_reindex_multiindex_no_cache_dates - 145±2ms 13.8±0.2ms 0.10 multiindex_object.SetOperations.time_operation('non_monotonic', 'datetime', 'symmetric_difference', None) - 145±2ms 13.7±0.2ms 0.09 multiindex_object.SetOperations.time_operation('monotonic', 'datetime', 'symmetric_difference', None) - 1.83±0.02ms 169±0.8μs 0.09 series_methods.SeriesConstructor.time_constructor_no_data - 145±2ms 13.1±0.2ms 0.09 multiindex_object.SetOperations.time_operation('non_monotonic', 'datetime', 'symmetric_difference', False) - 198±0.7ms 17.8±0.4ms 0.09 groupby.Cumulative.time_frame_transform_many_nulls('Int64', 'cumsum') - 870±3ms 77.8±0.8ms 0.09 multiindex_object.Unique.time_unique_dups(('Int64', <NA>)) - 146±2ms 13.0±0.2ms 0.09 multiindex_object.SetOperations.time_operation('monotonic', 'datetime', 'symmetric_difference', False) - 5.53±0.1ms 487±3μs 0.09 join_merge.JoinEmpty.time_inner_join_left_empty - 841±2ms 73.0±1ms 0.09 multiindex_object.Unique.time_unique_dups(('int64', 0)) - 307±0.8ms 26.4±0.7ms 0.09 multiindex_object.SetOperations.time_operation('monotonic', 'datetime', 'intersection', None) - 6.33±0.1ms 486±2μs 0.08 join_merge.JoinEmpty.time_inner_join_right_empty - 378±2ms 25.9±0.6ms 0.07 multiindex_object.SetOperations.time_operation('non_monotonic', 'datetime', 'intersection', None) - 23.9±0.3ms 1.55±0.01ms 0.06 join_merge.Merge.time_merge_dataframe_empty_right(True) - 312±2ms 19.6±0.6ms 0.06 rolling.TableMethod.time_ewm_mean('single') - 76.0±0.5ms 4.70±0.05ms 0.06 multiindex_object.Isin.time_isin('datetime') - 1.40±0s 83.2±1ms 0.06 multiindex_object.Unique.time_unique(('Int64', <NA>)) - 1.41±0.01s 81.3±1ms 0.06 multiindex_object.Unique.time_unique(('int64', 0)) - 83.5±0.3ms 4.80±0.5ms 0.06 multiindex_object.SortValues.time_sort_values('int64') - 84.8±0.3ms 4.76±0.5ms 0.06 multiindex_object.SortValues.time_sort_values('Int64') - 519±30ms 28.6±0.6ms 0.06 indexing.MultiIndexing.time_loc_all_lists(False) - 22.8±0.5ms 1.20±0.03ms 0.05 multiindex_object.GetLocs.time_large_get_locs - 7.62±0.09ms 386±2μs 0.05 array.ArrowStringArray.time_setitem_list(False) - 287±5μs 13.4±0.7μs 0.05 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(10000, datetime.timezone(datetime.timedelta(seconds=3600))) - 243±3ms 11.0±0.2ms 0.05 multiindex_object.SetOperations.time_operation('non_monotonic', 'datetime', 'intersection', False) - 307±0.7ms 11.2±0.2ms 0.04 multiindex_object.SetOperations.time_operation('monotonic', 'datetime', 'intersection', False) - 1.60±0.01ms 39.3±0.5μs 0.02 index_cached_properties.IndexCache.time_is_all_dates('MultiIndex') - 1.61±0.01ms 38.7±3μs 0.02 index_cached_properties.IndexCache.time_is_all_dates('IntervalIndex') - 36.4±1ms 843±50μs 0.02 tslibs.tz_convert.TimeTZConvert.time_tz_localize_to_utc(1000000, datetime.timezone(datetime.timedelta(seconds=3600))) - 50.8±2ms 1.11±0.01ms 0.02 indexing.MultiIndexing.time_loc_null_slice_plus_slice(True) - 18.8±0.2ms 384±3μs 0.02 array.ArrowStringArray.time_setitem_list(True) - 83.6±0.6ms 1.68±0.01ms 0.02 groupby.GroupByMethods.time_dtype_as_field('int16', 'diff', 'transformation', 5) - 79.5±0.7ms 1.58±0.01ms 0.02 groupby.GroupByMethods.time_dtype_as_field('uint', 'diff', 'transformation', 5) - 79.4±0.4ms 1.55±0.01ms 0.02 groupby.GroupByMethods.time_dtype_as_field('float', 'diff', 'transformation', 5) - 83.4±0.6ms 1.57±0.01ms 0.02 groupby.GroupByMethods.time_dtype_as_field('int', 'diff', 'transformation', 5) - 177±0.3ms 3.12±0.01ms 0.02 frame_ctor.FromScalar.time_frame_from_scalar_ea_float64_na - 98.8±1ms 1.41±0.01ms 0.01 groupby.GroupByMethods.time_dtype_as_group('int16', 'diff', 'transformation', 5) - 99.4±1ms 1.42±0.01ms 0.01 groupby.GroupByMethods.time_dtype_as_group('int', 'diff', 'transformation', 5) - 99.4±1ms 1.40±0.01ms 0.01 groupby.GroupByMethods.time_dtype_as_group('uint', 'diff', 'transformation', 5) - 84.7±0.6ms 1.17±0.02ms 0.01 series_methods.ClipDt.time_clip - 1.58±0.01ms 20.0±0.3μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('UInt64Index') - 1.60±0.01ms 20.1±0.5μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('DatetimeIndex') - 1.61±0.01ms 20.0±0.4μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('PeriodIndex') - 1.58±0.01ms 19.3±0.6μs 0.01 series_methods.ToFrame.time_to_frame('datetime64[ns]', None) - 144±1ms 1.73±0.01ms 0.01 groupby.GroupByMethods.time_dtype_as_field('datetime', 'diff', 'transformation', 5) - 1.57±0.01ms 18.3±0.4μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('TimedeltaIndex') - 1.57±0.01ms 18.1±0.4μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('Float64Index') - 1.57±0.01ms 17.9±0.4μs 0.01 series_methods.ToFrame.time_to_frame('int64', None) - 1.57±0.01ms 17.2±0.4μs 0.01 series_methods.ToFrame.time_to_frame('Int64', None) - 1.58±0.01ms 17.3±0.5μs 0.01 series_methods.ToFrame.time_to_frame('category', None) - 58.1±0.1ms 606±30μs 0.01 array.IntegerArray.time_from_integer_array - 4.55±0.07ms 47.3±3μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('CategoricalIndex') - 155±2ms 1.47±0.01ms 0.01 groupby.GroupByMethods.time_dtype_as_group('float', 'diff', 'transformation', 5) - 152±2ms 1.38±0.01ms 0.01 groupby.GroupByMethods.time_dtype_as_group('datetime', 'diff', 'transformation', 5) - 154±0.6ms 1.37±0.02ms 0.01 frame_methods.ToRecords.time_to_records_multiindex - 79.3±0.7ms 663±4μs 0.01 groupby.GroupByMethods.time_dtype_as_field('int16', 'diff', 'transformation', 1) - 75.7±0.7ms 563±4μs 0.01 groupby.GroupByMethods.time_dtype_as_field('uint', 'diff', 'transformation', 1) - 1.55±0.01ms 11.0±0.5μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('Int64Index') - 1.55±0.01ms 10.9±0.5μs 0.01 index_cached_properties.IndexCache.time_is_all_dates('RangeIndex') - 75.4±0.5ms 530±3μs 0.01 groupby.GroupByMethods.time_dtype_as_field('float', 'diff', 'transformation', 1) - 79.5±0.5ms 558±4μs 0.01 groupby.GroupByMethods.time_dtype_as_field('int', 'diff', 'transformation', 1) - 119±1ms 742±8μs 0.01 indexing.MultiIndexing.time_loc_all_bool_indexers(True) - 122±1ms 728±10μs 0.01 indexing.MultiIndexing.time_loc_all_bool_indexers(False) - 116±0.8ms 622±4μs 0.01 groupby.GroupByMethods.time_dtype_as_group('int16', 'diff', 'transformation', 1) - 1.25±0s 6.67±0.09ms 0.01 array.ArrowStringArray.time_setitem_slice(True) - 117±1ms 605±4μs 0.01 groupby.GroupByMethods.time_dtype_as_group('int', 'diff', 'transformation', 1) - 117±0.7ms 605±3μs 0.01 groupby.GroupByMethods.time_dtype_as_group('uint', 'diff', 'transformation', 1) - 139±1ms 704±5μs 0.01 groupby.GroupByMethods.time_dtype_as_field('datetime', 'diff', 'transformation', 1) - 294±2ms 1.36±0.04ms 0.00 rolling.GroupbyEWMEngine.time_groupby_mean('numba') - 83.3±0.5ms 356±3μs 0.00 groupby.GroupByMethods.time_dtype_as_field('int16', 'diff', 'direct', 5) - 79.5±0.8ms 335±6μs 0.00 groupby.GroupByMethods.time_dtype_as_field('int16', 'diff', 'direct', 1) - 98.1±1ms 387±3μs 0.00 groupby.GroupByMethods.time_dtype_as_group('int', 'diff', 'direct', 5) - 97.1±1ms 375±3μs 0.00 groupby.GroupByMethods.time_dtype_as_group('int16', 'diff', 'direct', 5) - 97.8±1ms 374±2μs 0.00 groupby.GroupByMethods.time_dtype_as_group('uint', 'diff', 'direct', 5) - 184±1ms 681±4μs 0.00 groupby.GroupByMethods.time_dtype_as_group('float', 'diff', 'transformation', 1) - 187±2ms 585±5μs 0.00 groupby.GroupByMethods.time_dtype_as_group('datetime', 'diff', 'transformation', 1) - 75.8±0.9ms 227±5μs 0.00 groupby.GroupByMethods.time_dtype_as_field('uint', 'diff', 'direct', 1) - 79.3±0.8ms 237±3μs 0.00 groupby.GroupByMethods.time_dtype_as_field('uint', 'diff', 'direct', 5) - 2.72±0.01s 7.82±0.09ms 0.00 groupby.ApplyNonUniqueUnsortedIndex.time_groupby_apply_non_unique_unsorted_index - 83.2±0.6ms 234±2μs 0.00 groupby.GroupByMethods.time_dtype_as_field('int', 'diff', 'direct', 5) - 143±1ms 402±3μs 0.00 groupby.GroupByMethods.time_dtype_as_field('datetime', 'diff', 'direct', 5) - 140±1ms 389±7μs 0.00 groupby.GroupByMethods.time_dtype_as_field('datetime', 'diff', 'direct', 1) - 79.7±0.9ms 219±4μs 0.00 groupby.GroupByMethods.time_dtype_as_field('int', 'diff', 'direct', 1) - 79.1±0.4ms 203±2μs 0.00 groupby.GroupByMethods.time_dtype_as_field('float', 'diff', 'direct', 5) - 75.3±0.7ms 191±3μs 0.00 groupby.GroupByMethods.time_dtype_as_field('float', 'diff', 'direct', 1) - 152±2ms 363±3μs 0.00 groupby.GroupByMethods.time_dtype_as_group('float', 'diff', 'direct', 5) - 152±2ms 356±2μs 0.00 groupby.GroupByMethods.time_dtype_as_group('datetime', 'diff', 'direct', 5) - 115±0.8ms 225±5μs 0.00 groupby.GroupByMethods.time_dtype_as_group('int16', 'diff', 'direct', 1) - 117±0.8ms 225±4μs 0.00 groupby.GroupByMethods.time_dtype_as_group('int', 'diff', 'direct', 1) - 117±0.8ms 225±5μs 0.00 groupby.GroupByMethods.time_dtype_as_group('uint', 'diff', 'direct', 1) - 183±2ms 212±5μs 0.00 groupby.GroupByMethods.time_dtype_as_group('float', 'diff', 'direct', 1) - 187±1ms 215±5μs 0.00 groupby.GroupByMethods.time_dtype_as_group('datetime', 'diff', 'direct', 1) - 665±2ms 228±4μs 0.00 rolling.TableMethod.time_ewm_mean('table') - 1.18±0s 345±2μs 0.00 array.ArrowStringArray.time_setitem_slice(False) brock@Falcon:~/pd/pandas/asv_bench$ Connection to falcon.local closed by remote host. Connection to falcon.local closed. brock@EnterpriseB fixmes58 %

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1st New Contributor Meeting - October 19th
by Noa Tamir Oct. 11, 2022

Oct. 11, 2022

Hi 👋 We’re happy to invite you to the first pandas New Contributor Meeting. 🎉 The first meeting will take place next week, October 19th (Wednesday) at 4:00 PM UTC [1] and it will be scheduled to repeat monthly after that. 🥳 This meeting is for any new contributors, who want to meet more experienced contributors and maintainers, in order to get support with getting started as a pandas contributors. Or if you started contributing recently, perhaps you’d like to discuss your ongoing pull requests (PRs), or anything else you might want to discuss – you decide what’s on the agenda! To join us, please check our meeting calendar [2], which has meeting times, with links to the agenda [3], and the meeting zoom link [4]. 👋 you all are invited 💬 everyone can present (add yourself to the hackMD agenda) 👀 anyone can sit in and listen We’re looking forward to meeting with you! Cheers, Marco (he/him), Richard (he/him), and Noa (she/they) PS- if you’re a more experienced contributor or maintainer, and want to join to help new contributors, you are also welcome to join us! [1[ ⌚ 4pm UTC in your local time: https://dateful.com/convert/utc?t=4pm [2] 📆 Meeting calendar: https://pandas.pydata.org/docs/dev/development/meeting.html [3] 🗒 Agenda: https://hackmd.io/@pandas-dev/HJgQt1Tei [4] 📹 Zoom link (October 19th (Wednesday) at 4:00 PM UTC): https://us06web.zoom.us/j/85437327422?pwd=WDZaVXo2ZlJ4dDBPa092R3NSY01tdz09

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pandas slack
by Noa Tamir Oct. 8, 2022

Oct. 8, 2022

Hello folks 👋 pandas is happy to announce we now have a slack for developers, maintainers and potential contributors. This is not a space for user questions, rather for discussions about: - How to contribute, including onboarding to different roles as people become more active - Internal team announcements - Mirroring public announcement, or sharing private information like who is planning to attend a conference, a meeting, etc. - A space to share ideas about the project - Coordinating project work and activity as needs arise or change You are welcome to join! Email us at slack(a)pandas.paydata.org and let us know that you read and agree to our [code of conduct](https://pandas.pydata.org/community/coc.html) 😉 If you have ideas for improvements, feel free to share! As a side note, this is not meant to replace the mailing list – all important announcements and conversations should still happen here. Cheers, Noa she/היא/sie

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