Submitting Author: Ivy Zhang (@ssyayayy), Anita Li (@AnitaLi-0371), Elanor Boyle-Stanley (@eboylestanley), Junghoo Kim (@jkim222383)
Package Name: coRPysprofiling
One-Line Description of Package: coRPysprofiling performs EDA and EDV on text
Repository Link: https://github.com/UBC-MDS/coRPysprofiling/releases/tag/0.1.4
Version submitted: 0.1.4
Editor: Tiffany Timbers(@ttimbers )
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
Version accepted: TBD
Description
coRPysprofiling is an open-source library designed to bring exploratory data analysis and visualization to the domain of natural language processing. Functions in the package will be used to provide some elementary statistics and visualizations for a single text corpus or provide functions to compare multiple corpora with each other.
Scope
Please indicate which [category or categories][PackageCategories] this package falls under:
[X] Data retrieval
[ ] Data extraction
[ ] Data munging
[ ] Data deposition
[ ] Reproducibility
[ ] Geospatial
[ ] Education
[X] Data visualization*
Explain how the and why the package falls under these categories (briefly, 1-2 sentences):
The core functionalities for coRPysprofiling are to provide elementary statistics and visualizations for a single text corpus, and to compare multiple corpora with each other. It can also download and load pretrained word2vector models from github repository.
Who is the target audience and what are scientific applications of this package?
The target audience can be talent acquisition specialists who want to quickly retrieve valuable information from resume texts or compare text from two resumes.
Are there other Python packages that accomplish the same thing? If so, how does yours differ?
To our knowledge, while wordcloud library generates wordcloud visualization for a given corpus, there is no general-purpose library for exploratory analysis and visualization of a text corpus in the Python ecosystem. There are several advanced libraries for comparing similarities between different corpora: most notably, gensim provides similarity comparison between large corpora using word embeddings. We believe that coRPysprofiling will provide some useful functionality for exploratory analysis and visualization and help bridge the gap between elementary text analysis to more sophisticated approaches utilizing word embeddings.
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
For details about the pyOpenSci packaging requirements, see our [packaging guide][PackagingGuide]. Confirm each of the following by checking the box. This package:
[X] does not violate the Terms of Service of any service it interacts with.
[X] has an [OSI approved license][OsiApprovedLicense].
[X] contains a README with instructions for installing the development version.
[X] includes documentation with examples for all functions.
[X] contains a vignette with examples of its essential functions and uses.
[X] has a test suite.
[X] has continuous integration, such as Travis CI, AppVeyor, CircleCI, and/or others.
Publication options
[ ] Do you wish to automatically submit to the [Journal of Open Source Software][JournalOfOpenSourceSoftware]? If so:
JOSS Checks
- [ ] The package has an **obvious research application** according to JOSS's definition in their [submission requirements][JossSubmissionRequirements]. Be aware that completing the pyOpenSci review process **does not** guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
- [ ] The package is not a "minor utility" as defined by JOSS's [submission requirements][JossSubmissionRequirements]: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
- [ ] The package contains a `paper.md` matching [JOSS's requirements][JossPaperRequirements] with a high-level description in the package root or in `inst/`.
- [ ] The package is deposited in a long-term repository with the DOI:
*Note: Do not submit your package separately to JOSS*
Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
[x] Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.
Code of conduct
[X] I agree to abide by [pyOpenSci's Code of Conduct][PyOpenSciCodeOfConduct] during the review process and in maintaining my package should it be accepted.
Draft
Submitting Author: Ivy Zhang (@ssyayayy), Anita Li (@AnitaLi-0371), Elanor Boyle-Stanley (@eboylestanley), Junghoo Kim (@jkim222383) Package Name: coRPysprofiling One-Line Description of Package: coRPysprofiling performs EDA and EDV on text Repository Link: https://github.com/UBC-MDS/coRPysprofiling/releases/tag/0.1.4 Version submitted: 0.1.4 Editor: Tiffany Timbers(@ttimbers ) Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
Version accepted: TBD
Description
Scope
Please indicate which [category or categories][PackageCategories] this package falls under:
Explain how the and why the package falls under these categories (briefly, 1-2 sentences):
Who is the target audience and what are scientific applications of this package?
Are there other Python packages that accomplish the same thing? If so, how does yours differ?
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
For details about the pyOpenSci packaging requirements, see our [packaging guide][PackagingGuide]. Confirm each of the following by checking the box. This package:
Publication options
JOSS Checks
- [ ] The package has an **obvious research application** according to JOSS's definition in their [submission requirements][JossSubmissionRequirements]. Be aware that completing the pyOpenSci review process **does not** guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS. - [ ] The package is not a "minor utility" as defined by JOSS's [submission requirements][JossSubmissionRequirements]: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria. - [ ] The package contains a `paper.md` matching [JOSS's requirements][JossPaperRequirements] with a high-level description in the package root or in `inst/`. - [ ] The package is deposited in a long-term repository with the DOI: *Note: Do not submit your package separately to JOSS*Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?
This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.
Code of conduct