Submission: sptidy (R)

[anodaini]

Submitting Author: Jacob McFarlane @JacobMcFarlane, Asma Al-Odaini (@anodaini), Xudong Yang @xudongyang2, Heidi Ye @heidi-ye Repository: sptidy Version submitted: 0.2.0 Editor: TBD Reviewers: TBD

Archive: TBD Version accepted: TBD

---

• Paste the full DESCRIPTION file inside a code block below:

Package: sptidy
Title: Tidy-up linear regression and kmeans model outputs
Version: 0.0.0.9000
Authors@R: 
    c(person(given = "Jacob",
           family = "McFarlane",
           role = c("aut", "cre"),
           email = "jacob@jakenow.net"),
    person(given = "Asma",
           family = "Al-Odaini",
           role = c("aut")),
    person(given = "Peter",
           family = "Yang",
           role = c("aut")),
    person(given = "Heidi",
           family = "Ye",
           role = c("aut"))
           )
Description: Sptidy implements a tidy and augment function for base R’s linear regression and Tidymodel’s kmeans clustering to ease model selection and assessment tasks. This package is a simplified reimplementation of the existing tidy and augments functions in the Broom package. Sptidy’s family of tidy functions returns a dataframe that summarizes important model information, while the augment function expands the original dataframe to include additional model specific information by observation. This package is meant to complement Sktidy, a Python package that was created to tidy up the scikit-learn package.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Suggests: 
    testthat (>= 3.0.0),
    covr
Config/testthat/edition: 3
URL: https://github.com/UBC-MDS/sptidy
BugReports: https://github.com/UBC-MDS/sptidy/issues
Imports: 
    tibble,
    dplyr,
    broom

Scope

• Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):

  • [ ] data retrieval
  • [x] data extraction
  • [x] data munging
  • [ ] data deposition
  • [ ] workflow automation
  • [ ] version control
  • [ ] citation management and bibliometrics
  • [ ] scientific software wrappers
  • [ ] field and lab reproducibility tools
  • [ ] database software bindings
  • [ ] geospatial data
  • [ ] text analysis

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

  The package falls under data extraction because it retrieves data from the models and presents it in a structured way. In addition, it falls under data munging because it transforms the data into a more accessible and appropriate form.

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

  The target audience would be people that want to use a lightweight package that outputs a tidy dataframe of the kmeans and lm models from the stats package.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

  The sptidy packages implements functionality that closely resembles the broom's package tidy() and augment() functions for the lm and kmeans model.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

• If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

Technical checks

Confirm each of the following by checking the box.

• [x] I have read the guide for authors and rOpenSci packaging guide.

This package:

• [x] does not violate the Terms of Service of any service it interacts with.
• [ ] has a CRAN and OSI accepted license.
• [x] contains a README with instructions for installing the development version.
• [x] includes documentation with examples for all functions, created with roxygen2.
• [x] contains a vignette with examples of its essential functions and uses.
• [x] has a test suite.
• [x] has continuous integration, including reporting of test coverage using services such as Travis CI, Coveralls and/or CodeCov.

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• [ ] Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

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- [ ] The package is novel and will be of interest to the broad readership of the journal. - [ ] The manuscript describing the package is no longer than 3000 words. - [ ] You intend to archive the code for the package in a long-term repository which meets the requirements of the journal (see [MEE's Policy on Publishing Code](http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)2041-210X/journal-resources/policy-on-publishing-code.html)) - (*Scope: Do consider MEE's [Aims and Scope](http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)2041-210X/aims-and-scope/read-full-aims-and-scope.html) for your manuscript. We make no guarantee that your manuscript will be within MEE scope.*) - (*Although not required, we strongly recommend having a full manuscript prepared when you submit here.*) - (*Please do not submit your package separately to Methods in Ecology and Evolution*)

Code of conduct

• [x] I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

[larahabashy]

Package Review

Please check off boxes as applicable, and elaborate in the comments below. Your review is not limited to these topics, as described in the reviewer guide

• Briefly describe any working relationship you have (had) with the package authors.
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Documentation

The package includes all the following forms of documentation:

• [x] A statement of need clearly stating problems the software is designed to solve and its target audience in README
• [x] Installation instructions: for the development version of the package and any non-standard dependencies in README
• [x] Vignette(s) demonstrating major functionality that runs successfully locally
• [x] Function Documentation: for all exported functions
• [x] Examples (that run successfully locally) for all exported functions
• [x] Community guidelines including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

• [x] Installation: Installation succeeds as documented.
• [x] Functionality: Any functional claims of the software been confirmed.
• [x] Performance: Any performance claims of the software been confirmed.
• [x] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
• [x] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines

Estimated hours spent reviewing: 2.5

• [x] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

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Review Comments

Hi team! Great job on this package, it provides a really good simplification of model summary outputs. I really liked how you kept your documentation consistent and clear. I just had a few small comments and suggestions on the package, but overall, I think you all did an amazing job!

README

• In the file titled README.md, I couldn't find a link to the package website on GitHub pages
• The vignette should also be visible on the package website under the Articles tab
• I suggest linking the vignette under the Overview section in the readme
• I also could not find a list of package authors
• The tests are passing but there is no button for test coverage
• There's a typo under the Usage section: kmenas()

Code of Conduct

• I found a typo in the CODE_OF_CONDUCT.md file. Also, under the Enforcement section, there is a "[INSERT CONTACT METHOD]", I'm not sure if that was intentional.

• To keep spelling consistent, I suggest changing behavior to behaviour

  Overall, the functionality and key points of the package are spot on! Very smooth and easy to use, and I had no issues running the code. Great job!