Submission Group 27: covizr (R)

name: covizr about: R package for easily visualizing COVID-19 statistics

Submitting Author Name: Rong Li Submitting Author Github Handle: !--author1-->@lirnish<!--end-author1-- Other Package Authors Github handles: @rrrohit1, @thomassiu, @ytz Repository: https://github.com/UBC-MDS/covizr Version submitted: 1.0.0 Submission type: Standard Editor: Rohit Rawat (@rrrohit1), Rong Li (@lirnish), Thomas Siu (@thomassiu), Ting Zhe Yan (@ytz) Reviewers: Sukhleen Kaur (@sukhleen999), Philson Chan (@PhilsChan), Kingslin Lv (@Kingslin0810)

Language: en

Paste the full DESCRIPTION file inside a code block below:

Package: covizr
Title: Easy access to Covid-19 data from Our World in Data and generates COVID-19 charts
Version: 1.0.0
Authors@R: c(
person("Rohit", "Rawat", email = "rrrohit28@gmail.com", role = c("aut")),
person("Rong", "Li", email = "lirnishui@gmail.com", role = c("aut")),
person("Thomas", "Siu", email = "thomas.siu@gmail.com", role = c("aut")),
person("Ting Zhe", "Yan", email = "tingzhe@gmail.com", role = c("aut", "cre")))    
Description: covizr is a R package that provides easy access to Covid-19 data from Our World in Data, as well as functions to generate relevant Covid-19 charts and summaries easily. We aim to make covizpy simple and easy to use. Our goal is to enable anyone with basic Python programming knowledge to access and visualize Covid-19 data, and make their own informed decisions and conclusions.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
Imports: 
dplyr,
ggplot2,
here,
lubridate,
magrittr,
readr,
rlang,
scales,
stringr,
testthat
Suggests: 
knitr,
covr,
rmarkdown
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.):
- [x] data retrieval
- [ ] data extraction
- [ ] 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):

(Other category: Data visualization) Our package extracts covid data from an online source, and visualizes the data using bar plot and line plot.
Who is the target audience and what are scientific applications of this package?

The target audience is the researchers, journalists, and data analysts who need to understand and communicate COVID-19 related issues.
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 is an existing package covid19 that allows users to download and generate Covid-19 charts. However, we utilized another data source that includes different metrics, and we also provide simpler functions that allow users to answer questions regarding the COVID-19 pandemic as quickly as possible.
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Not applicable
If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

Not applicable
Explain reasons for any pkgcheck items which your package is unable to pass.

Not applicable

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
[ ] 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.
[ ] Functionality: Any functional claims of the software been confirmed.
[ ] 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 hours

[ ] 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

Hello group 27, again congratulations and well done on this R package; similar to my comments for your python package, your repo is well organized and structured for anyone with basic R programming skills to visually read covid-19 data summary. The written documentation is clear for me to follow as well. I have a few notes for improvement, and some of these are the same comments to your python package:

In your README I would suggest to include a section of Relevance to the R Ecosystem given there is a similar package like covid19
Suggest you include a R-CMD-check state badge on README. Here is the tutorial and you are ready to add it now.
Suggest to list get_data at first under Features
Suggest to include a Documentation section in your README such as ?covizr::get_data for users to easily access.
For plot_summary is sum the only aggerated function to input? I feel the Roxygen can be more explicitly to mention whether there are any other aggerated functions for the input.
Again, in the Roxygen it would be helpful to clarify of how functions are interacting as of location. I am a little bit unclear and don't think to have a good solution other than updating the documentation.
When I run check() I got below NOTEs; I got similar note of "no visible binding for global variables" and was able to solve it by creating a file Gloabls.R. Detailed solution can be found here
```
> checking top-level files ... NOTE
Non-standard file/directory found at top level:
'img'
```

checking R code for possible problems ... NOTE get_data: no visible binding for global variable 'iso_code' plot_summary: no visible binding for global variable 'value' Undefined global functions or variables: iso_code value

In addition to above comments, there are some missed check boxes above that you might still work on like Vigenttes. Again, great work everyone, please reach out if you have any questions. Thank you.

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
[ ] 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.
[ ] 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 hours

[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

The package overall looks neat and pretty. Similar to the python package, the charts are clear and visualize the data well. Unfortunately, I have encountered some technical problem occasionally so that I might not test it thoroughly. Below are some of my comments:

When I first execute get_data, an error popped up as follow:

> library(covizr)
> df <- get_data(date_from="2022-01-01", date_to="2022-01-21")
Error in value[[3L]](cond) : The link to the data is broken.                                                                                                              0s
In addition: Warning messages:
1: In base::nchar(wide_chars$test, type = "width") :
restarting interrupted promise evaluation
2: In base::nchar(wide_chars$test, type = "width") :
internal error -3 in R_decompress1

Although the error message suggested the link is broken, I could download the csv file directly from the link in your source code at the moment. However, the problem vanishes after a few hours. I think it would be valuable for you to keep a record of such problem.

In the usage section of the README file, an equal sign was used for the assignment of output of get_data, which is not recommended by the tidyverse style.
For the plotting functions, when there is no data in df within the date range specified by date_from and date_to, an empty plot would be shown. My personal suggestion would be throwing an error or showing customized warning in order to remind the users they might input a wrong range of dates.
Similar to my 4th point in your python package, you could consider specifying the accepted values for the argument "fun", or make it accept function object as well. Or I think you might consider delete the argument if there is no other sensible options of aggregate functions.
I have tried execute the following code, which is expected to give me the sum of new cases in 7 days by continent.
```
> df <- get_data()
> plot_summary(df, var="continent", val="new_cases", fun="sum", top_n=10)
```
However, only 1 bar representing Oceania is visualized as shown below. I think there might be some logic error within the function.
For plot_spec and plot_metric, I think it is a good idea to add the subtitle indicating the date range representated by the chart, just like how plot_summary did. I think it would make the package more unified, and increase the readablilty of the charts.

In general, you guys have done a great job and your package could certainly help a lot of people in lowering the barrier of data visualization. Wish you all the best!

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).

Functionality

[x] Installation: Installation succeeds as documented.
[ ] 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 hours

[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

The R package is equally good as the Python one and the instructions are easy to follow. The plots are concise yet informative and the package structure is is well defined which is reflective of the immense effort put in by the team!

Some pointers that might be considered for further improvement are:

When I run the code below, I get the following error. I believe the function should return an error message specific to the incorrect date format as it is in the Python package. It would be even better if multiple date formats can be accepted.
```
> plot_summary(df, var="location", val="new_cases", fun="sum", date_from="202-01-01", date_to="2022-01-15", top_n=10)
```
The 'location' argument of the plot_spec function should handle erroneous input values by throwing an error.
```
> df = get_data(date_from="2022-01-01", date_to="2022-01-21", location = c('Turkey', 'abdcde'))
```
In the function plot_metric, the title of the plot does not adapt to the input for the 'loc_val' argument if multiple countries are passed.
Finally, similar to my suggestion for the Python package, I recommend making the plots interactive for better insights into the data.

Overall, a great package and very well put together. Keep up the good work!

UBC-MDS / software-review-2022