Mailman 3 January 2020 - Pandas-dev

ANN: Pandas 1.0.0
by Tom Augspurger Jan. 30, 2020

Jan. 30, 2020

Hi all, I'm pleased to announce the release of pandas 1.0.0. This is a major release from 0.25.3, and includes a number of API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. Highlights include - A redesigned website and documentation theme - Using Numba in rolling.apply <https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#us…> - A new DataFrame method for converting to Markdown <https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#co…> - A new scalar for missing values <https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#ex…> - Dedicated extension types for string <https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#de…> and nullable boolean <https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html#bo…> data See the whatsnew <https://pandas.pydata.org/pandas-docs/version/1.0.0/whatsnew/v1.0.0.html> for a list of all the changes. We've also written a blog post <https://dev.pandas.io/pandas-blog/pandas-10.html> reflecting on the journey to 1.0 and what it means for our project. The release can be installed from PyPI python -m pip install --upgrade pandas Or with conda from the defaults or conda-forge channels. conda install pandas Thanks to the more than 300 contributors <https://pandas.pydata.org/pandas-docs/version/1.0/whatsnew/v1.0.0.html#cont…> to this release. Please report any issues with the release on the pandas issue tracker. <https://github.com/pandas-dev/pandas/issues> Tom

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Merging after the RC
by Tom Augspurger Jan. 13, 2020

Jan. 13, 2020

On the call yesterday, we discussed branching strategies after we tag the RC. We're trying to keep the workflow roughly what it was before (with some terms changed). Briefly 1. Don't merge API-breaking changes to master. Those will need to wait until the next *major* release (2.0.0) and we aren't ready to branch that yet. 2. We'll treat master as the next *minor* release. So performance improvements, refactors, bug fixes, new features, will all be merged to master, as long as they aren't API breaking changes. 3. Bugfixes fixing regressions that should be backported should be assigned the milestone for the next bugfix release (e.g. 1.0.0, 1.0.1, 1.1.1). Use your best judgement when deciding whether something is a bugfix or breaking API. And it may have been mentioned briefly, but what are people's thoughts on what should be merged during the RC? IMO, it should be just PRs fixing regressions from 0.25.x. Everything else can just go in the next minor release, and needn't be backported. I'm hoping to tag the RC later today. Tom

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Question about pd.NA
by Daniel Saxton Jan. 13, 2020

Jan. 13, 2020

Hi all, First off just wanted to say the new pd.NA value and enhancements to Boolean operations are incredibly cool new features, so congratulations on that. One minor question: (-1) ** pd.NA is always -1 as implemented, but should this also be pd.NA since the "unknown" NA value could be even or odd (or possibly some weird non-integer value)? Thanks, Daniel

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ANN: Pandas 1.0.0rc0 released
by Tom Augspurger Jan. 10, 2020

Jan. 10, 2020

Hi all, I'm pleased to announce that pandas 1.0.0rc0 is now available. This is the first release candidate for 1.0.0. If all goes well, we'll release pandas 1.0.0 in about two weeks. Highlights include - A new scalar for missing values <https://dev.pandas.io/docs/whatsnew/v1.0.0.html#experimental-na-scalar-to-d…> - Dedicated extension types for string <https://dev.pandas.io/docs/whatsnew/v1.0.0.html#dedicated-string-data-type> and nullable boolean <https://dev.pandas.io/docs/whatsnew/v1.0.0.html#boolean-data-type-with-miss…> data - Using Numba in rolling.apply <https://dev.pandas.io/docs/whatsnew/v1.0.0.html#using-numba-in-rolling-apply> - A redesigned website and documentation theme <https://pandas.pydata.org/pandas-docs/version/1.0.0/> See the whatsnew <https://dev.pandas.io/docs/whatsnew/v1.0.0.html> for a list of all the changes. The release can be installed from PyPI python -m pip install --upgrade --pre pandas==1.0.0rc0 Or from conda-forge conda create -n pandas=1.0.0rc0 -c conda-forge/label/rc -c conda-forge pandas==1.0.0rc0 Please report any issues with the release candidate on the pandas issue tracker <https://github.com/pandas-dev/pandas/issues>.

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Fwd: [NumFOCUS Projects] Job: Open Source Developer Advocate
by Joris Van den Bossche Jan. 9, 2020

Jan. 9, 2020

---------- Forwarded message --------- From: Nicole Foster <nicole(a)numfocus.org> Date: Wed, 8 Jan 2020 at 22:25 Subject: [NumFOCUS Projects] Job: Open Source Developer Advocate To: Fiscally Sponsored Project Representatives <projects(a)numfocus.org>, Affiliated Projects <affiliated(a)numfocus.org> Hi Everyone, We recently posted an ad for an Open Source Developer Advocate <https://www.indeedjobs.com/numfocus/jobs/344b7c30fe13ddb6d8ee>position with NumFOCUS. We would be thrilled to have a member of our community work with us here at NumFOCUS so we ask that you please share this job posting with anyone you know that might be a good fit. Please feel free to reach out if you have any questions. Thank you for your time and consideration as we work to fill this role. Best, -- Nicole Foster Executive Operations Administrator, NumFOCUS nicole(a)numfocus.org 512-831-2870 <http://www.numfocus.org/> <https://twitter.com/NumFOCUS> <https://www.facebook.com/NumFOCUS/> -- You received this message because you are subscribed to the Google Groups "Fiscally Sponsored Project Representatives" group. To unsubscribe from this group and stop receiving emails from it, send an email to projects+unsubscribe(a)numfocus.org. To view this discussion on the web visit https://groups.google.com/a/numfocus.org/d/msgid/projects/CAJLwxPF5ezbsAEWk… <https://groups.google.com/a/numfocus.org/d/msgid/projects/CAJLwxPF5ezbsAEWk…> .

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Monthly Dev Meeting
by Tom Augspurger Jan. 7, 2020

Jan. 7, 2020

Hi all, The next monthly dev call is tomorrow (Wednesday, January 8th) at 18:00 UTC. We invite all to come. https://dev.pandas.io/docs/development/meeting.html We'll use this Zoom link: https://zoom.us/j/942410248 The agenda is at https://docs.google.com/document/d/1tGbTiYORHiSPgVMXawiweGJlBw5dOkVJLY-lico… if you have topics to discuss. Tom

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pandas tz conversion issue
by Seeking That Jan. 1, 2020

Jan. 1, 2020

Hi python pandas bdate_range tz_convert() seems to have problems as it prints the information incorrectly. Please clarity. The python script and the output is shown below: Two issues that can be highlighted here are: 1) Setting the timezone correctly to US/Pacific prints the dates correctly. But the conversion causes the date calculations to be incorrect. 2. Minor issue just related to display. Though the API hasn't changed, the last call has more information hh-mm-ss-xx-xx which is not there for the rest of the calls with same format signature. Thanks SK import pandas as pd c5 = pd.bdate_range(start='1/1/2018', end = '1/31/2018') print(c5) c5 = c5.tz_localize('UTC') print(c5) c5 = c5.tz_convert('US/Pacific') print(c5) c6 = pd.bdate_range(start='1/1/2018', end = '1/31/2018') print(c6) c6 = c6.tz_localize('US/Pacific') print(c6) ------ DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04', '2018-01-05', '2018-01-08', '2018-01-09', '2018-01-10', '2018-01-11', '2018-01-12', '2018-01-15', '2018-01-16', '2018-01-17', '2018-01-18', '2018-01-19', '2018-01-22', '2018-01-23', '2018-01-24', '2018-01-25', '2018-01-26', '2018-01-29', '2018-01-30', '2018-01-31'], dtype='datetime64[ns]', freq='B') DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04', '2018-01-05', '2018-01-08', '2018-01-09', '2018-01-10', '2018-01-11', '2018-01-12', '2018-01-15', '2018-01-16', '2018-01-17', '2018-01-18', '2018-01-19', '2018-01-22', '2018-01-23', '2018-01-24', '2018-01-25', '2018-01-26', '2018-01-29', '2018-01-30', '2018-01-31'], dtype='datetime64[ns, UTC]', freq='B') DatetimeIndex(['2017-12-31', '2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04', '2018-01-07', '2018-01-08', '2018-01-09', '2018-01-10', '2018-01-11', '2018-01-14', '2018-01-15', '2018-01-16', '2018-01-17', '2018-01-18', '2018-01-21', '2018-01-22', '2018-01-23', '2018-01-24', '2018-01-25', '2018-01-28', '2018-01-29', '2018-01-30'], dtype='datetime64[ns, US/Pacific]', freq='B') DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04', '2018-01-05', '2018-01-08', '2018-01-09', '2018-01-10', '2018-01-11', '2018-01-12', '2018-01-15', '2018-01-16', '2018-01-17', '2018-01-18', '2018-01-19', '2018-01-22', '2018-01-23', '2018-01-24', '2018-01-25', '2018-01-26', '2018-01-29', '2018-01-30', '2018-01-31'], dtype='datetime64[ns]', freq='B') DatetimeIndex(['2018-01-01 00:00:00-08:00', '2018-01-02 00:00:00-08:00', '2018-01-03 00:00:00-08:00', '2018-01-04 00:00:00-08:00', '2018-01-05 00:00:00-08:00', '2018-01-08 00:00:00-08:00', '2018-01-09 00:00:00-08:00', '2018-01-10 00:00:00-08:00', '2018-01-11 00:00:00-08:00', '2018-01-12 00:00:00-08:00', '2018-01-15 00:00:00-08:00', '2018-01-16 00:00:00-08:00', '2018-01-17 00:00:00-08:00', '2018-01-18 00:00:00-08:00', '2018-01-19 00:00:00-08:00', '2018-01-22 00:00:00-08:00', '2018-01-23 00:00:00-08:00', '2018-01-24 00:00:00-08:00', '2018-01-25 00:00:00-08:00', '2018-01-26 00:00:00-08:00', '2018-01-29 00:00:00-08:00', '2018-01-30 00:00:00-08:00', '2018-01-31 00:00:00-08:00'], dtype='datetime64[ns, US/Pacific]', freq='B')

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