Submission group 17: Rstockwatch (R)

Submitting Author Name:
Affrin Sultana @Affrin101, Pavel Levchenko @plevchen, Helin Wang @helingogo, Shi Yan Wang @sy25wang

Package Name: Rstockwatch One-Line Description of Package: Simple interface for checking stock price and volume change Repository: https://github.com/UBC-MDS/Rstockwatch Version submitted: v2.0.0

Submission type: Standard

Editor: @Affrin101, @plevchen, @helingogo, @sy25wang Reviewers: @PANDASANG1231, @vtaskaev1, @hjw0703, @Rowansiv

Archive: TBD Version accepted: TBD Language: en

Paste the full DESCRIPTION file inside a code block below:

Package: Rstockwatch
Title: Make simple visualization of stock data
Version: 0.0.0.9000
Authors@R: c(
person("Affrin", "Sultana", role = c("aut", "cre")), 
person("Helin", "Wang", role = c("aut", "cre")), 
person("Pavel", "Levchenko", role = c("aut", "cre")), 
person("Shi Yan", "Wang", role = c("aut", "cre"))
)
Author: Affrin Sultana, Helin Wang,Pavel Levchenko, Shi Yan Wang
Maintainer: Affrin Sultana <affrin@example.net>, Helin Wang <helin@example.net>, Pavel Levchenko <pavel@example.net>, Shi Yan Wang <shiyan@example.net>
Description: Main idea of the package is to provide a very simple interface for checking movements in stock prices in comparison to the market. This will be implemented by accessing public data from Yahoo Finance by selecting a ticker of the stock, range of start and end dates and benchmark for comparison, such as SP500 or NASDAQ. As a result of data processing with pystockwatch package, user will be able to see a plot with two lines showing percentage change since the start date and volumes of trading
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
Suggests: 
testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: 
ggplot2,
stringr,
tidyquant,
readxl,
reshape2,
dplyr

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
- [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 retrieves data data from yahoo finance and creates visualizations for stock price change and volume change for the specified time period
Who is the target audience and what are scientific applications of this package?

The package aims to provide simple and fast information to investors new to the market who are interested in specific stock option.
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 other packages working on stock analysis and visualization, however, pystockwatch provides more straightforward visualizations on one selected stock's price and volume change, and how it performs against the market benchmark.
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[x] includes documentation with examples for all functions, created with roxygen2.
[x] contains a vignette with examples of its essential functions and uses.
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The package includes all the following forms of documentation:

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[x] Installation: Installation succeeds as documented.
[x] Functionality: Any functional claims of the software been confirmed.
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Estimated hours spent reviewing: 1.5 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

Well done, Group 17, on an interesting and concise package! As you stated, its simplicity makes it relevant for an audience looking to perform quick computation and analysis based on stocks they may be tracking. Below are some recommendations and suggestions that point to possible minor improvements that could facilitate its usage and interpretability:

The README is clear in that it provides a clear summary of the package's purpose and scope. However, the Usage and Example section does not appear to display the expected corresponding sample output. I see that png plots are already attached in the root of the repo, so it's likely only matter of a linking them to the README. This will help the audience quickly get a sense of the expected output from each function.
The tests created for the functions are comprehensive in that they cover classical edge cases. It may also be useful to add tests that would flag any outlier values generated from their underlying computation (e.g., a percentage change above realistic thresholds that may possible indicate issues pertaining to the raw data).
The test file documentation could be made more consistent in its use of comments. For instance, a short summary comment block could help quickly grasp the general purpose of each test, while remaining comment format could be made to follow the same convention across all functions.
The volume_viz plot is a useful concept, but its output is a little difficult to make sense of at first glance. One suggestion could be to use a line plot instead of a bar plot for ease of interpretation of any trends.
Finally, it may be useful to also add a test to raise an error should the user happen to input an invalid ticker string, allowing for quick and easy debugging.

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

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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 package and any non-standard dependencies in README
[x] Vignette(s) demonstrating major functionality that runs successfully locally
[x] Function Documentation: for all user-facing functions
[x] Examples for all user-facing functions
[x] Community guidelines including contribution guidelines in the README or CONTRIBUTING.
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[x] The package name
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[x] Installation: Installation succeeds as documented.
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Estimated hours spent reviewing: 1 hour

Review Comments

The profit visualisation graph is well executed but can be difficult to read as it is quite small. It could be useful to think about making it interactive for a better user experience.
Similarly, the volume visualisation graph is quite hard to use as each bar blends into each other. I would suggest having borders around each bar to separate them so each one can be identified on its own.
The scale that is used on the volume visualisation graph leaves something to be desired. As someone with no background in computing may use this package, having the scale use numbers such as 1.0e+08 will not mean much to them. I would suggest changing the scale and in the axis title have a scaler such as (000's).
When messing around with the inputs and using a future year e.g. 2026, the error returned is not helpful in understanding what is wrong unlike when changing the month to a value greater than 12 where it tells me that it is an invalid start date. Potentially do the same when the year value is greater than the current year.
Well done on the vignettes. The site looks very clean and easy to read and provides all necessary information for using and installing the package.

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.
[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: 0.5 hour

[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

Guys, I really like your R package as I would identify myself as one of your potential users. There are some things you might take into consideration in the future:

The test coverage could be improved as it has only 89 percent coverage until now.
For the first plot in readme, I would suggest use direct labels to help users capture the legend more easily.
The second plot size in readme.md file could be adjusted(the histogram are too big and occupy a lot of space) to make them more clear and attractive to users.
If you could dive deeper into giving a certain probability as whether the stock price would increase in the short term based on some models would make the package more attractive.
I expect to see the output for each functions in readme file but some of them are not shown, it would be more clear to users if all the output are displayed.

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.
[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: 1 hour

[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 Whole project is very easy to use, and it is valueable for a finance professional to use. Well done!
One suggestion is that, for a financial user such as quant researcher, it will be better if the package can show all the open, high, low, close in the visualization
vol_viz works just the way financial institution visualize volume data. It is quite clear and professional, well done. But compared to python package the plot in doc seems to be more loose, is there any reasons?
For the volume's visualization, a clear title will even make your work better.
There are two functions' result is not shown in the readme. I understand those two are auxiliary functions, but it will be better if you show the dataframe anyway.

Anyway, it is a fantastic project considering there are only four functions here. Really nice work guys.

UBC-MDS / software-review-2022