# 2023-01-30 NumPy Documentation Team meeting
- Time: 12 pm UTC
- Join via Zoom: https://us06web.zoom.us/j/85016474448?pwd=TWEvaWJ1SklyVEpwNXUrcHV1YmFJQT09 (To dial in, find your local number: https://us06web.zoom.us/u/ksv5WeoUL)
- [NumPy community events calendar](https://scientific-python.org/calendars/)
- [Documentation issues](https://github.com/numpy/numpy/labels/04%20-%20Documentation)
- [Documentation brainstorming document](https://hackmd.io/RdtnQZpLRZqgNRe4gaJ0SA) - anything that is not yet ready for an issue or PR or needs a discussion
- [Documentation team meetings notes archive](https://github.com/numpy/archive/tree/main/docs_team_meetings)
- [Community meetings notes archive](https://github.com/numpy/archive/tree/main/community_meetings)
- [Triage meetings notes archive](https://github.com/numpy/archive/tree/master/triage_meetings)
- Next meeting: 2023-02-13 @ 4 pm UTC
### Useful links
- Getting started with building documentation: https://numpy.org/devdocs/dev/howto_build_docs.html
- How to contribute to the NumPy documentation: https://numpy.org/devdocs/dev/howto-docs.html
### Code of Conduct
We want to take a moment to remind you that this meeting is meant to be welcoming and inclusive. It's important for us to have a healthy community. Like all NumPy spaces, and everyone participating in them, this meeting will follow our [Code of Conduct](https://numpy.org/code-of-conduct/). If you haven't read it yet, please take some time to do so later on as it already applies to you. For now, in short, please be kind and generous towards one another.
If you see violations, take a screenshot, intervene in a respectful manner, and report it to the CoC Committee via email. For more information, refer to the Reporting Guidelines section on https://numpy.org/code-of-conduct/.
**Present:** Mukulika, Melissa, Matti, Lex Maximov, Rohit Goswami
**Notes taken by:**
## Follow-up from last meeting / discussions
- [name=inessa] Presentation topics for NumPy Newcomers’ Hour
To suggest a topic for future presentations, leave a comment in this tracking issue: https://github.com/numpy/archive/issues/58.
- [name=Inessa & Melissa] [Documentation user stories](https://github.com/numpy/numpy/issues/22089)
*Feel free to add yours!*
- Inessa: issues related to the NumPy educational content:
If you’d like to work on any of them, leave a comment on GitHub (below the relevant issue).
- Tracking inactive PRs
- Add them to this GitHub project: https://github.com/orgs/numpy/projects/6
- [name=rossbar] Dealing with data for NumPy tutorials
* Currently running a mirror (from my personal github account) containing data for numpy tutorials.
- At the very least, this should move outside of my personal github account
- Look into S3 buckets?
- Talk to Numfocus about allocating a bucket
* Data as a submodule?
- Doesn't scale to large datasets, but probably more convenient than what we currently do
- Similar to what SciPy is implementing
- [Initial setup for scipy.datasets](https://github.com/scipy/scipy/pull/15607)
- Each dataset is a repo under the scipy organization. For example, https://github.com/scipy/dataset-ascent
- [Documentation on scipy.datasets](https://scipy.github.io/devdocs/reference/datasets.html)
- A quick look at [open doc PRs](https://github.com/numpy/numpy/pulls?q=is%3Aopen+is%3Apr+label%3A%2204+-+Documentation%22):
- Maybe add ref_guide check to a specific CI job for easier review
- Add it to CircleCI or make a separate job
- Action item: Open an issue about it
- Consider adding numpy-tutorials to the main NumPy readme (?) to redirect CI contributions to a more suitable/necessary place.
## New Topics
- [name=Mukulika ]Interest for participating in Google Season of Docs 2023
- The new season has been [announced](https://groups.google.com/g/season-of-docs-announce/c/-wfcYZ9UYwc/m/gotnfJ0OCgAJ?pli=1).
- Read about last season's successful projects [here](https://developers.google.com/season-of-docs/docs/2022/participants).
- Mukulika, Melissa available for mentoring
- [name=Melissa] [DOC: Add images illustrating how-to-io.rst #17556 ](https://github.com/numpy/numpy/pull/17556)
- Use Mermaid to generate illustrations
- Melissa will open a draft PR for consideration
- [name=Lev] "NumPy Showcase" for the [Pandas Illustrated](https://betterprogramming.pub/pandas-illustrated-the-definitive-visual-guide-to-pandas-c31fa921a43) article.
- Use cases where NumPy is more suitable than Pandas (idea from [this](https://www.reddit.com/r/Python/comments/10mezt9/comment/j688rp7/?utm_source=reddit&utm_medium=web2x&context=3) reddit comment):
- multidimensional fancy indexing is missing from Pandas;
- `df.replace` is surprizingly slow;
- no random numbers generators in Pandas;
- Image processing and homogenous data operations are better suited for NumPy
- [name=Rohit] Section on `git bisect` for hard to track bugs?
- Probably under the [advanced debugging section](https://numpy.org/doc/stable/dev/development_advanced_debugging.html)?
- Suggest links outside, maybe just a few lines [name=Matti,Melissa]
- Maybe the Github main document
- Something on test isolation / don't rebuild NumPy
- Or `meson` build where possible :)
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