What is Shiny app:
Shiny is an open package from RStudio, which provides a web application framework to create interactive web applications (visualization) called “Shiny apps”. The ease of working with Shiny has what popularized it among R users. These web applications seamlessly display R objects (like plots, tables etc.) and can also be made live to allow access to anyone.
Shiny provides automatic reactive binding between inputs and outputs which we will be discussing in the later parts of this article. It also provides extensive pre-built widgets which make it possible to build elegant and powerful applications with minimal effort.
Shiny app is built using two components
UI.R: This file creates the user interface in a shiny application. It provides interactivity to the shiny app by taking the input from the user and dynamically displaying the generated output on the screen.
Server:R: This file contains the series of steps to convert the input given by user into the desired output to be displayed.
Shiny App Structure
Shiny applications are divided into two parts: the User Interface (UI) and the Server. The UI is responsible for the app presentation, while the server is responsible for the app logic.
The UI controls what is being displayed on the application page and how the components are laid out. This may include text and other markdown elements, graphics, widgets that take in user input, or plots. You will also use the UI to define a navigation bar with multiple tabs in this tutorial.
The Server controls the data that will be displayed through the UI. The server will be where you load in and wrangle data, then define your outputs (i.e. plots) using input from the UI.
Both of these parts can be defined in one file, but it is good practice to separate these into two files to simplify any future changes or maintenance on the app.
Shiny Apps and Data Presentation
Data are usually collected in a raw format and, no matter how well processed and analyzed, results should be presented in a plain and simple way in order to make them accessible for everyone. Unfortunately, the potential of effective data presentation is all too often not fully exploited. Yet, presentation is crucial as it illustrates the actual outcome of research. If not effectively visualized, we waste a great opportunity to build credibility, attract and sustain the interest of readers, and make large amounts of information easily accessible. Here, we introduce Shiny Apps as a powerful and highly flexible tool for interactive data presentation in the world wide web.
Shiny is an R package that offers cost- and programming-free tools for building web applications using R. It was developed by Joe Chang to serve as a reactive web framework for R that allows calculations, display of R objects, and the presentation of results. Since Shiny Apps come with an extensive back-end setup, users do not need extensive web development skills to build and host standalone apps on a homepage. However, for those keen on bringing their apps to perfection, Shiny Apps allows for CSS, HTML and JavaScript extensions.Shiny Apps can be used either for data presentation, as a communication tool for results, or even as an interactive analytical tool.
Advantages and Disadvantages of Shiny
There are plenty of other data visualization tools out there. So, to help you compare what differentiates Shiny and what you can and cannot do with Shiny, let’s look at the advantages and disadvantages of using shiny.
Advantages :
- Efficient Response Time: The response time of shiny app is very small, making it possible to deliver real time output(s) for the given input.
- Complete Automation of the app: A shiny app can be automated to perform a set of operations to produce the desire output based on input.
- Knowledge of HTML, CSS or JavaScript not required: It requires absolutely no prior knowledge of HTML, CSS or JavaScript to create a fully functional shiny app.
- Advance Analytics: Shiny app is very powerful and can be used to visualize even the most complex of data like 3D plots, maps, etc.
- Cost effective: The paid versions of shinyapps.io and shiny servers provide a cost effective scalable solution for deployment of shiny apps online.
- Open Source: Building and getting a shiny app online is free of cost, if you wish to deploy your app on the free version of shinyapps.io
Disadvantages :
- Requires timely updates: As the functions used in the app gets outdated sometimes with newer package versions, it becomes necessary to update your shiny app time to time.
- No selective access and permissions: There’s no provision for blocking someone’s access to your app or proving selective access. Once the app is live on the web, it is freely accessible by everyone
- Restriction on traffic in free version: In free version of shinyapps.io, you only get 25 active hours of your app per month per account.
Conclusion
Data presentation is crucial for accessible scientific research. Even with accurate and comprehensive data that supports relevant findings, failure to present the data in an easily accessible way can result in wasted opportunities. Shiny Apps are a powerful and free-of-cost tool that allows scholars to provide readers with easy-to-use, interactive, and comprehensive insights into their research. For instance, scholars can use Shiny Apps to program an interactive online appendix and thereby offer readers full control to compare findings under different specifications of measurement and modeling.
However, the advantages of creating a functional web-application exclusively with R has some limitations. Considering the design and the placement of inputs (such as sliders) or outputs (such as graphics and tables), Shiny is limited. When combining Shiny with HTML, CSS, and JavaScript, however, it offers a good way to program professional web-apps. Shiny is particularly great for fast prototyping and fairly easy to use with little experience in programming. It comes with many different charting libraries and captures feedback and comments in a structured manner. It therefore offers an exciting toolbox that can be a valuable addition to scientific research.
#Embedded Courses in Bangalore #Embedded Courses in Hyderabad #Embedded Jobs for Freshers #Embedded C #Embedded Systems #Embedded Training in Hyderabad #Embedded Classes in Hyderabad #Embedded Systems Course in Hyderabad #Embedded Programming Courses in Hyderabad #Embedded Training in Bangalore #Embedded Classes in Bangalore #Embedded Systems Course in Bangalore #Embedded Programming Courses in Bangalore #Best Embedded Training Institute in Bangalore #Best Embedded Training Institute in Hyderabad #Embedded Training Institute in Bangalore #Embedded Training Institute in Hyderabad #Best Embedded Course in Bangalore #Best Embedded Course in Hyderabad #best iot training institute in Bangalore #best iot training institute in Hyderabad #iot training institute in bangalore #iot training institute in Hyderabad #best iot course in Bangalore #best iot course in hyderabad #Embedded Jobs in Bangalore #Embedded Jobs in Hyderabad #Iot jobs in Bangalore #IoT jobs in Hyderabad #Python Jobs in Bangalore #Python Jobs in Hyderabad #AIML #Artificial Intelligence #machine learning #Data Science Courses in Bangalore #Data Science Courses in Hyderabad #Data Science Courses #Best Data Science Training Institute #Best Data science Course #Best Python Course #Best Iot Course #Best Iot Training Institute in Bangalore #Best Iot Training Institute in Hyderabad #Iot Certification Course Bangalore #Iot Certification Course Hyderabad #Best Artificial Intelligence Training Institute Bangalore #Best Artificial Intelligence Training Institute Hyderabad #Best fullstack Training Institute in Bangalore #Best full stack Training Institute in Hyderabad #full stack Training Institute in Bangalore #full stack Training Institute in Hyderabad #Best full stack Course in Bangalore #Best full stack Course in Hyderabad