Submission: datascience.eda.R

Submitting Author: Mai Le (@lephanthuymai) Other Authors: Aditya Bhatraju(@adibns), Charles Suresh (@charlessuresh), Rahul Kuriyedath (@rahulkuriyedath) Repository: https://github.com/UBC-MDS/datascience.eda.R Version submitted: https://github.com/UBC-MDS/datascience.eda.R/releases/tag/0.3.0 Editor: TBD Reviewers: TBD

Archive: TBD Version accepted: TBD

Paste the full DESCRIPTION file inside a code block below:

Package: datascience.eda
Title: Common Functions for EDA
Version: 0.3.0
Authors@R: 
    c(person(given = "Mai",
           family = "Le",
           role = "aut",
           email = "lephanthuymai@gmail.com"),
    person(given = "Charles",
           family = "Suresh",
           role = c("aut", "cre"),
           email = "emailcharlesjosh@gmail.com"),
    person(given = "Aditya",
       family = "Bhatraju",
       role = "aut",
       email = "adityabns@outlook.com"),
    person(given = "Rahul",
      family = "Kuriyedath",
      role = "aut",
      email = "rahul.kuriyedath@gmail.com"))
Description: This package includes functions assisting data scientists with various common tasks during the exploratory data analysis stage of a data science project. Its functions will help the data scientist to do preliminary analysis on common column types like numeric columns, categorical columns and text columns; it will also conduct several experimental clusterings on the dataset.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Suggests: 
    testthat (>= 3.0.0),
    rmarkdown,
    covr
Config/testthat/edition: 2
Imports: 
    stats,
    dbscan,
    dplyr,
    imputeR,
    graphics,
    ggbiplot (>= 0.55),
    ggplot2,
    palmerpenguins,
    NLP,
    RColorBrewer,
    tidyverse,
    tm,
    wordcloud,
    vdiffr,
    stringr,
    sacred (>= 0.1.0),
    purrr,
    forcats,
    GGally,
    reshape2,
    tibble,
    MASS,
    knitr
Remotes: 
    git@github.com:JohnCoene/sacred.git,
    git@github.com:vqv/ggbiplot.git
VignetteBuilder: knitr

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
- [ ] data munging
- [ ] data deposition
- [x] data validation and testing
- [x] workflow automation
- [ ] version control
- [ ] citation management and bibliometrics
- [ ] scientific software wrappers
- [ ] field and lab reproducibility tools
- [ ] database software bindings
- [ ] geospatial data
- [x] text analysis
Explain how and why the package falls under these categories (briefly, 1-2 sentences):

datascience.eda package provides functions to automate most of preliminary exploratory data analysis tasks (workflow automation), some of the highlight functionalities are creating data clusters to be used in feature engineering (data extraction), identifying the proportion of missing data for categorical columns (data testing), retrieving top words in text columns (text analysis).

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

The target audience of this package is data scientists, it will help to improve the efficiency of the EDA process

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

There are various packages providing functions to be used in EDA, most of them focus on identifying the anomalies of numeric columns, the exact functionalities vary from ours, furthermore, there is no EDA-related package in our awareness that provides functions to handle text columns and data clustering.

(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.
[x] 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.

Publication options

[ ] Do you intend for this package to go on CRAN?
[ ] Do you intend for this package to go on Bioconductor?
[ ] Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

MEE Options

- [ ] 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.

Package Review

Please check off boxes as applicable, and elaborate in 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.
[x] As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

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 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).

For packages co-submitting to JOSS

[ ] The package has an obvious research application according to JOSS's definition

The package contains a paper.md matching JOSS's requirements with:

[ ] A short summary describing the high-level functionality of the software

[ ] Authors: A list of authors with their affiliations

[ ] A statement of need clearly stating problems the software is designed to solve and its target audience.

[ ] References: with DOIs for all those that have one (e.g. papers, datasets, software).

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

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

Review Comments

Hi Mai, Aditya, Charles, and Rahul. datascience.eda.R looks great! I'm impressed by the amount of work you all put into this package in such a short period of time. Below are some of my comments and feedback regarding the package:

The .R files were well documented and commented when necessary, which makes it very easy to follow and read
The README and instructions were written in a clear and simple manner, I understood how to use the functions and their respective purposes after the first read!
explore_numeric_columns: When running this function on the penguins dataset, I only expected 7 plots as per the example in the README. There were 7 additional tables in the output, and 6 of them were identical. This gets a bit messy especially when I knit the file.
explore_numeric_columns: The correlation heatmap is a great idea to visualize the correlation between numerical features, but there might be a bug in the plot. Referring back to the example in the README, the correlation between features shouldn't all be grey. (I got a different result using GGally::ggcorr)
explore_categorical_columns: Not sure if this is possible, but It might be a good idea to include this step inside the function (for all categoricals) as opposed to making the user do it manually:
```
df <- data.frame(lapply(penguins[, c('species','island')], as.character),
stringsAsFactors=FALSE) %>% tibble()
```

Overall, you all did a great job on this package, It was very well thought out and in-depth. This package definitely speeds up the EDA process and I can see other data scientists using it!

UBC-MDS / software-review-2021