Summary
This shiny app takes the speed in miles per hour of a car and estimates the distance in feet to stop, using data from the 1920s.Table of Contents
Overview
shiny applications are a great way to engage a reader. They allow a person to interact with an application by entering inputs. The applications require some organization and can range from the simple to extremely complex.
Background
There are a lot of places to find help in writing a first application in shiny. (The shiny package must be installed first!) Two places to start are Rstudio’s tutorials and Hadley Wickham’s new book, “Mastering Shiny.” The main idea behind this exercise was to design an app that took a viewer input and predicted the outcome using a mathmatical model.
Data and model
R comes loaded with some illustrative and easy datasets. For this app, the cars dataset was used and is among the simplest datasets to understand. From the help page, “the data give the speed of cars and the distances taken to stop. Note that the data were recorded in the 1920s.” Early automobiles were powered by small engines and the top speed in the dataset is 25 miles per hour.
Results
Here’s the application inserted into an <iframe> in my blog post:
Conclusion
The application’s simplicity is deceptive. The basic structure allows for future modeling that includes more variables and methods. Or in other words, it can be scaled to other problems that are more complex. Additionally, it allows a user to explore and see the data.
Acknowledgements
There were some incredibly complex, insightful and time-intensive shiny applications that were consulted for this post. Specifically, I want to acknowledge and thank the authors of the following apps:
References
Disclaimer
The views, analysis and conclusions presented within this paper represent the author’s alone and not of any other person, organization or government entity. While I have made every reasonable effort to ensure that the information in this article was correct, it will nonetheless contain errors, inaccuracies and inconsistencies. It is a working paper subject to revision without notice as additional information becomes available. Any liability is disclaimed as to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from negligence, accident, or any other cause. The author(s) received no financial support for the research, authorship, and/or publication of this article.
Reproducibility
─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
setting value
version R version 3.6.3 (2020-02-29)
os macOS Catalina 10.15.7
system x86_64, darwin15.6.0
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz America/Chicago
date 2021-05-07
─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────
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[1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library