Shiny App: An Efficient and Creative Communicator of Big Data
By Jiena Gu, Beef Cattle Institute, College of Veterinary Medicine, Kansas State University
Changing the world doesn’t mean everyone has to make a big discovery; it can be as simple as becoming a better communicator and finding more creative ways to pass the knowledge we have onto the people who need it!
Nowadays, we all live in a big data era, and data can come from every corner of our lives. How to be an effective story teller with big messy data is incredibly important for our lives. Traditionally, analyzing data and reporting the results are only the responsibilities of statisticians or analysts. However, with the development of technology, the process of storytelling with big data can be efficient and creative by using the Shiny package (a Web Application Framework package made for R).
Shiny App: Turning your Analyses into Interactive Web Applications
(no web development skills required!)
Here is a screenshot of one of my demo shiny apps. This plot shows the population density in Canada. Each point represents a city in Canada, and the size of the point represents the population density in that city.
Figure 1: Population Density in Canada
If the points are too dense to distinguish, users can zoom in to investigate more about the area they are interested in. Additionally, the users can mouse over a specific point to get more information about the city it represents. Here is the screenshot of the plot zoomed in:
Figure 2: Zoomed-In View of the Population Density of Canada
Since Shiny apps are written with R software (one of many statistical programming languages), you can use any of its available packages when you build your shiny apps, which means you can directly apply any statistical package or any statistical functions usable with R into your app instead of writing them by yourself. Also, you have the flexibility of designing the output of the results. Here is a regression analysis of an open source data set (the iris one).
Figure 3: Regression Analysis of the Iris Dataset
An Automatic Reporting System: Shiny App + Markdown Syntax
After the users get the analytical results or stories, they will usually want to save the results in an elegant report with the current date in PDF or any other kind of format. Therefore, it is important that an interactive web app for analytical purposes has an automatic reporting system.
In terms of a reporting system, you can set one up for your Shiny app through Markdown. Markdown (syntax) can turn your analytical results into high quality documents, reports, presentations and dashboards. You have options to control which plots should be put into your report and you can write down your comments for each plot. After finishing, you can download your whole report by simply clicking the “download” button.
Here is the screenshot of the PDF report from my demo app:
Figure 4: Demo Analytical Report
Figure 5 is part of the PDF report from the app.
Figure 5: Analytical Results (Demo Analytical Report of Canada Map)
The Application of Shiny Apps
In educational fields, Shiny apps have been applied widely for helping students gain a better and deeper understanding of mathematical and / or analytical fields. For example, by using the interactive functions of Shiny apps, students will gain experience of how parameters affect statistical distributions or graphs. It is better to learn math or statistics by “playing” with them instead of memorizing tedious formulae from textbooks.
In veterinary medical fields, Shiny apps with automatic reporting systems can help veterinarians or vet med-related businesses have a better and deeper understanding of their data and make better decisions by telling a story with their data.
In addition, the automatic reporting system can help users record their data stories or reports. In this way, users can save a lot of time when reporting or analyzing their data weekly or monthly.
The Beef Cattle Institute of K-State Vet Med is currently working on building an analytical dashboard with Shiny and Markdown for helping beef cattle industries to gain insights and make better decisions with beef cattle data. The Beef Cattle Institute will also provide analytics mobile apps to fit the needs of veterinarians and beef producers.
Giving Jiena Gu's Shiny Apps a Try...
Please click on the links below to try out the Shiny apps.
Jiena Gu's Awesome Data Scientist Shiny Apps:A Data Plot with a Voice-Activated Interface:
Acknowledgments: Thanks for the help from Wendy L. Michaels, Alyssa Toillion, Yihui Xie (from RStudio, Inc.), and the K-State Beef Cattle Institute.
About the Author
Jiena Gu is the project coordinator of the Beef Cattle Institute (K-State Vet Med). Originally from the Guangdong Province in China, Gu came to K-State with a degree in bioengineering. She received her master’s degree in statistics from Kansas State University after she finished her Graduate Certificate in Public Health. She is interested in storytelling with big data by using various tools such as data visualization and applied statistics. Her expertise is in big data analytics, applied statistics and create interactive applications with automatic reporting system. She may be reached at firstname.lastname@example.org.
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