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raphaelvallat / pingouin

Statistical package in Python based on Pandas
https://pingouin-stats.org/
GNU General Public License v3.0
1.64k stars 139 forks source link

Roadmap for release 0.6.0 #279

Open raphaelvallat opened 2 years ago

raphaelvallat commented 2 years ago

The following issues should be addressed:

The following PR should be merged:

The following dependencies should be updated:

The following deprecation should be made:

Federico2111 commented 2 years ago

Seems like a good new release. Is there any time line? When will these upgrades be made? Thanks

raphaelvallat commented 2 years ago

Hi @Federico2111,

I have had no time to work on Pingouin in the last few months, and I anticipate this will continue at least until Q1 2023. I therefore cannot promise a timeline for this new release.

musicinmybrain commented 1 year ago

The following dependencies should be updated:

* [ ]  Scikit-learn <1.1.2 (revert temporary fix in [Use scikit-learn<1.1.0 #278](https://github.com/raphaelvallat/pingouin/pull/278))

This can be checked off, since https://github.com/raphaelvallat/pingouin/pull/300 is merged and released in 0.5.3.

Federico2111 commented 1 year ago

Any update about the progress of this new release? Any help needed?

raphaelvallat commented 1 year ago

Thanks @Federico2111 — unfortunately at the moment I only have time for urgent bug fixes, not for implementing new features. So it's unlikely that version 0.6.0 is coming anytime soon; however I'd like to release version 0.5.4 with some minor improvements and bugfixes (e.g. CI tests) in the coming weeks.

Federico2111 commented 1 year ago

Thanks @raphaelvallat. By CI tests, you mean also the parametric Confidence Interval around eta squared that I had suggested? https://github.com/raphaelvallat/pingouin/issues/253

raphaelvallat commented 1 year ago

No sorry I meant the unit tests (aka continuous integration or CI), see GitHub Actions: https://github.com/raphaelvallat/pingouin/actions

Federico2111 commented 9 months ago

Any update? :-)

raphaelvallat commented 9 months ago

I recently released a minor version that included bugfixes and some improvements: https://github.com/raphaelvallat/pingouin/releases/tag/v0.5.4

I cannot say when the next release will be, but likely not in the coming weeks. Feel free to submit PRs for what you consider to be the most important/urgent tasks. Thanks

FlorinAndrei commented 9 months ago

@raphaelvallat What's happening with the site https://pingouin-stats.org/ ? I see the text, but all the styling is broken. I've tried Shift-reload, no luck. Using latest Chrome on Win10.

raphaelvallat commented 9 months ago

@FlorinAndrei https://github.com/raphaelvallat/pingouin/issues/400, I'll investigate and try to fix soon

Federico2111 commented 9 months ago

Thanks @raphaelvallat My suggestion was #253 which is to add the parametric confidence interval around the eta squared effect size. I provided some documentation about it. This feature would complete the pingouin.compute_esci library, where parametric ci's are calculated for other effect sizes, but not for eta squared: https://pingouin-stats.org/build/html/generated/pingouin.compute_esci.html

turkalpmd commented 9 months ago

I have implemented some of the adjustment methods mentioned in this article (https://scholarworks.umass.edu/pare/vol20/iss1/8/) in Python. If deemed appropriate, I can create a PR.

raphaelvallat commented 9 months ago

I have implemented some of the adjustment methods mentioned in this article (https://scholarworks.umass.edu/pare/vol20/iss1/8/) in Python. If deemed appropriate, I can create a PR.

@turkalpmd Can you please first open an issue to describe exactly what new or updated methods could be implemented based on this paper?

raphaelvallat commented 9 months ago

@Federico2111 I'm trying to move away from a system in which I implement external requests for features, towards a more sustainable model where people actually implement and submit modifications in pull requests. Furthermore, this is not a highly-requested feature so I have not considered it a high-priority item. Have you made your own implementation of this feature with Python?

turkalpmd commented 9 months ago

I have implemented some of the adjustment methods mentioned in this article (https://scholarworks.umass.edu/pare/vol20/iss1/8/) in Python. If deemed appropriate, I can create a PR.

@turkalpmd Can you please first open an issue to describe exactly what new or updated methods could be implemented based on this paper?

Here, I've opened the issue you mentioned, @raphaelvallat

Federico2111 commented 9 months ago

Hi @raphaelvallat, I have not implemented that feature (#253) in my Python scripts. If it is not implemented in the pingouin library, I would consider studying the literature and writing the code in my scripts. Currently pingouin.compute_esci calculates the parametric confidence intervals around the most commonly used effect sizes in one-way anova. Eta squared is the most commonly used effect size in two-way anova, which is why I think it would complete the features of the library and would be a beneficial addition.

Federico2111 commented 1 month ago

Any news or timeline? Can we help in some way?

remrama commented 1 month ago

Hi @Federico2111, Pingouin is mostly dependent on community efforts to push new features/fixes through. So regarding a timeline, this version will get pushed when the checklist at the top of this Roadmap/Issue is complete. As you can see, there is more work to do.

Can we help in some way?

Yes, see the checklist at the top for detailed descriptions of where help is needed.