Package Review --- `AustraliaCOVID19`

Sun, 25 Oct 2020 00:00:00 +0000

Overview of the package — `AustraliaCOVID19`

The package written by Yiwen Liu is called AustraliaCOVID19.

User can install the released version of AustraliaCOVID19 from GitHub with:

# install.packages("devtools")
devtools::install_github("etc5523-2020/r-package-assessment-yliu0320")

What does the package do

The goal of AustraliaCOVID19 is to see the coronavirus data of daily cases and cumulative cases of different types in different states of Australia between 2020-01-12 to 2020-10-02. Besides,the shiny app in this package will give people the whole information about the data with the interactive plots and table.

Possible improvements

1. pkgdown website

The package does have a pkgdown website and pass the pkgdown check in Action tab, but author forgets to set the GitHub Pages setting to correct source. Anyway, I create the pkgdown website by myself. The website is clear and gives some example of how to use the Shiny App. The possible improvements could be don’t forget to change the GitHub setting next time 😄.

2. documentation and README.md

They are all clear and readable. The possible improvement could be enriching them in the future by adding more details.

3. refactor

Refactor functions are simple but effective, which are good. The possible improvement could be that Yiwen can try to refactor some more complicated functions in the future.

4. `test_that` function

There is only on unit test. I hope there should be more in the future.

test_that("check the date range", {
  expect_error(dateselection(starttime>endtime))
  
})

5. Shiny app

All plots within the Shiny app are interactive and functional. And the Shiny has clear UI and understandable plots. The possible improvement could be adding more tabs in the Shiny app, in order to make the whole Shiny app page fit to user’s screen.

What I learned from reviewing the package

It is funny to review other’s package. I understand it’s not enough to just ensure the package passing all the test. I also realise the importance of documentation. Good documentation can promote the package, teach users how to use the package, and inspire others while poor documentation will confuse users.

Package Review

Please check off boxes as applicable, and elaborate in comments below.

Documentation

The package includes all the following forms of documentation:

Installation instructions: for the package is found in README
Vignette(s) demonstrating major functionality that runs successfully locally
Function Documentation: for all exported functions in R help
Examples for all exported functions in R Help that run successfully locally

Functionality

Installation: Installation succeeds as documented.
Functionality: Any functional claims of the software been confirmed.
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.

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