Mailman 3 February 2023 - Pandas-dev

pandas new infrastructure (OVH donation)
by Marc Garcia Sept. 21, 2024

Sept. 21, 2024

Hi all, pandas has received a donation from OVHcloud <https://www.ovhcloud.com/> to support the project infrastructure, with OVHcloud public cloud credits (an initial amount of 10,000 EUR for a period of one year). OVH is open to sponsor longer term and also other projects of the ecosystem (or NumFOCUS as a whole), but we started with this to have feedback at a smaller scale first. The credits will be used initially for: - Hosting of the pandas website - Running the pandas benchmarks - Speeding up the project CI I detail next what I have in mind to set up for each. If anyone is interested in getting involved, or has ideas, comments... please let me know. I'll publish updates here as there is progress on this. Website: I'm planning to experiment on splitting the website in two (it'll be transparent for users). The website and the stable docs which receive most of the traffic can probably be stored in Cloudflare pages. We're already using Cloudflare as a CDN, so instead of using it as a cache, we can publish the documents there. The rest of the docs (old versions and the dev version) can be hosted in bucket storage of the OVHcloud. Response times may be a bit slower, but our website is bigger than the Cloudflare quota, and having old docs rarely accessed in a CDN seems unnecessary anyway. - Benchmarks: OVHcloud instances have guaranteed hardware, and we'll be checking if this is enough for the results of the benchmarks to be consistent over runs, or if there is too much variability and we need dedicated hardware. If consistency is good enough that would be great, since our benchmarks mostly use one core, and using dedicated hardware is likely to be a decent waste of resources, since most servers will likely have 16 cores or more. We'll discuss with OVH if dedicated hardware is needed, as at the moment their public cloud doesn't offer it (there is an alpha for providing dedicated instances, but we need to check with them). - Faster CI: Our GitHub runners are small, and most builds take around one hour or more to finish. We should be able to use bigger OVH instances for our existing CI pretty easily, via their OpenStack API and CIrun.

5 9

February 2023 bi-monthly community meeting (Wednesday February 8, UTC 18:00)
by Joris Van den Bossche Sept. 11, 2024

Sept. 11, 2024

Hi all, A late reminder that the next bi-monthly (twice a month) dev call is today in a bit more than 1 hour (Wednesday, February 8) at 18:00 UTC. Our calendar is at https://pandas.pydata.org/docs/development/meeting.html#calendar to check your local time. The pandas Community Meeting is a regular sync meeting for the project's maintainers which is open to the community. All are welcome to attend! Video Call: https://us06web.zoom.us/j/84484803210?pwd=TjUxNmcyNHcvcG9SNGJvbE53Y21GZz09 Meeting notes: https://docs.google.com/document/u/1/d/1tGbTiYORHiSPgVMXawiweGJlBw5dOkVJLY-… Joris

1 1

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?

6 11

ANN: pandas 2.0.0 RC0
by Marc Garcia Feb. 21, 2023

Feb. 21, 2023

We are happy to announce the *release candidate* of pandas 2.0.0. It can be installed from our conda-forge and PyPI packages via mamba, conda and pip, for example: mamba install -c conda-forge/label/pandas_rc pandas==2.0.0rc0 python -m pip install --upgrade --pre pandas==2.0.0rc0 Users having pandas code in production and maintainers of libraries with pandas as a dependency are *strongly* recommended to run their test suites with the release candidate, and report any breaking change to our issue tracker <https://github.com/pandas-dev/pandas/issues/new/choose> before the official 2.0.0 release. You can find the documentation of pandas 2.0.0 here <https://pandas.pydata.org/pandas-docs/version/2.0/index.html>, and the list of changes in 2.0.0, in the release notes page <https://pandas.pydata.org/pandas-docs/version/2.0/whatsnew/v2.0.0.html>. We expect to release the final version of pandas 2.0.0 in around two weeks, but the final date will depend on the issues reported to the release candidate.

1 0

Unable to install pandas on my work computer
by Surya Sriram Feb. 15, 2023

Feb. 15, 2023

Hi, I was trying to install python pandas package from Pycharm on my work computer, but I'm unable to install it. I'm attaching the error message below. I don't have adminstrator rights on my computer, I can't open CMD on my computer either. Is there any other way I could install packages?

1 0

DataFrame.pivot positional deprecations
by Jonathan Crall Feb. 11, 2023

Feb. 11, 2023

Hi all, Please tell me if there is a better place to raise this, but I'm seeing a lot of: FutureWarning: In a future version of pandas all arguments of DataFrame.pivot will be keyword-only. I'm wondering: what is the rationale behind removing the positional arguments here? They seem perfectly natural to me. I'd like to put my two cents in and suggest that maybe moving to keyword only is not the best idea in this case because pivot is very useful in interactive sessions, but keyword only args will make it more cumbersome to type and access. If there is a very good reason for removing positional arguments I'm open to updating my code, but I'd like to see what that rationale and discussion was. If the rationale does not have a solid foundation then my suggestion is perhaps this change should be removed from the roadmap. -- -Dr. Jon Crall (him)

1 0

EA Naming Conventions
by Brock Mendel Feb. 8, 2023

Feb. 8, 2023

For historical reasons we've built up an EA namespace without much internal logic in terms of what is public/private. While this isn't _that_ big of a deal, it'd be nice to make this more coherent. I see two useful options: 1) Use the traditional "an underscore means this should only be called from within self". Very few methods on the base class satisfy that characteristic, including the constructor _from_sequence. One benefit of moving to this is it would make "official" that we shouldn't be using _values_for_foo from outside EA methods. 2) Use underscores to signal to 3rd party authors whether or not there exists a working (not necessarily performant) implementation on the base class. In this scenario authors would _have_ to implement private methods, while implementing public methods would be optional. Thoughts?

2 1

SciPy 2023 Call for Proposals
by lthomas＠enthought.com Feb. 3, 2023

Feb. 3, 2023

SciPy 2023 Call for Proposals

1 0

pandas-vet
by Roman Yurchak Feb. 2, 2023

Feb. 2, 2023

Hi, There was interesting work done in https://github.com/deppen8/pandas-vet for enforcing automated checks on pandas code. I was wondering if the core teams had some opinions on the enforced rules and could comment to what extent there is a consensus on those, whether they are consistent with what's recommended in the pandas docs. Particularly on things, like pivot_table vs unstack, .array vs .values, and melt vs stack. Currently working on a largish legacy code with lots of pandas code, so IMO something like pyupgrade for pandas could really be great. Also now that pandas-vet is implemented in ruff, I feel it has the potential to become mainstream in a few years. Just checking whether there is some consensus on what could / should be enforced for pandas linting. For the rule "'inplace = True' should be avoided; it has inconsistent behavior": if there is an issue, this could be fixed in some future major release, right ? Thanks, Roman

2 1