Presubmission Inquiry for Great Tables

[rich-iannone]

Submitting Author: Richard Iannone (@rich-iannone)
Package Name: Great Tables
One-Line Description of Package: Make awesome display tables using Python.
Repository Link (if existing): https://github.com/posit-dev/great-tables

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Code of Conduct & Commitment to Maintain Package

• I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
• I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.

Description

The Great Tables package is all about creating tables for the purpose of presentation. You can use
Pandas or Polars DataFrames as inputs, and the Great Tables API allows you to:

• structure the data using column spanners and row groups, and add header and footer information
• format the data with a wide range of powerful formatting methods
• style the table to make it aesthetically pleasing or to highlight important information
• integrate the table display into notebooks, Quarto documents or web pages, and export the table
  as HTML or a variety of image formats

Community Partnerships

We partner with communities to support peer review with an additional layer of
checks that satisfy community requirements. If your package fits into an
existing community please check below:

• Astropy:My package adheres to Astropy community standards
• Pangeo: My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

Scope

• Please indicate which category or categories this package falls under:

Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

- [ ] Data retrieval
- [ ] Data extraction
- [ ] Data processing/munging
- [ ] Data deposition
- [ ] Data validation and testing
- [x] Data visualization
- [ ] Workflow automation
- [ ] Citation management and bibliometrics
- [ ] Scientific software wrappers
- [ ] Database interoperability

Domain Specific

• Geospatial
• Education

Community Partnerships

If your package is associated with an
existing community please check below:

• Astropy:My package adheres to Astropy community standards

• Pangeo: My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook

• Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

  The package can be seen as a data visualization package, but it is perhaps more in the direction
  of data presentation/publication (i.e., not datavis in the traditional sense).

• Who is the target audience and what are the scientific applications of this package?

  The target audience is anyone who needs to present data in the tabular format. There is a
  particular focus on science and engineering applications as many of the formatting methods are
  geared toward this audience (e.g., scientific notation, significant figures, units notation,
  chemistry notation, etc.).

• Are there other Python packages that accomplish similar things? If so, how does yours differ?

  There are only a few packages that deal with tabular data presentation. The Pandas styler API is
  probably the best known of these, but it is limited in its capabilities. A big part of Great
  Tables is the ability to structure a table to a more traditional table format (one you'd commonly
  see in journals or reports) instead of interactive tables that are more common in web apps (i.e.,
  displaying hundreds or thousands of rows of data). The formatting capabilities of Great Tables
  are also much more extensive than Pandas styler or other packages.

• Any other questions or issues we should be aware of:

P.S. Have feedback/comments about our review process? Leave a comment here

[Batalex]

Hey @rich-iannone,
As a big fan of great-tables, I'm thrilled to welcome you to pyOpenSci!

All that being said, I want to set the proper expectations from the start. I would like to run this presubmission by our editorial board because:

• on the one hand, data visualization packages are especially tricky to review, and we usually focus on domain-specific packages rather than core ones.
• on the other hand, I think that great-tables is a key component of the scientific tool set, and everyone would benefit from this collaboration. The fact that the codebase is way more manageable than the other core packages we excluded from our scope policy (like ipython or numpy) is a big plus.

Stay tuned!

[Batalex]

OK, I think we are in the clear regarding the scope question! Would you mind opening a new submission issue referencing this presubmission enquiry? Thank you.

[Batalex]

Superseded by #202.