Learn how to use Shiny, a popular R package, to build highly interactive web applications—without needing any other programming languages. Using Shiny you can share your analyses as dashboards and visualizations to bring your data to life.

In this track, you’ll get hands-on with Gapminder, Star Wars, and NASA datasets, as you discover how to represent raw data using explorable visualizations including plots and word clouds. You’ll also improve your ability to make discoveries and communicate these visually to non-technical stakeholders—an invaluable skill for any data analyst or data scientist!

Learn how to use Shiny, a popular R package, to build highly interactive web applications and share your analyses as dashboards and visualizations.

with R

Shiny Fundamentals

To kick off the course you'll learn what a web app is and when you should build one, plus build a few apps of your own! You'll first learn to make text inputs and outputs in a few ways, including exploring the popularity of certain names over time.

Get Started with Shiny

In this chapter you will learn how to take advantage of different input and  output options in shiny. You''ll learn the syntax for taking inputs from users   and rendering different kinds of outputs, including text, plots, and tables.


Inputs, Outputs, and Layouts

In this chapter, you will learn about reactive programming. You will  learn about reactive sources, conductors and endpoints and how they come together to drive the magic behind Shiny. You will also learn how to utilize your understanding of reactivity to build performant Shiny apps.

Reactive Programming

It’s time to build your own Shiny apps. You’ll make several apps from scratch, including one that allows you to gather insights from the Mental Health in Tech Survey and another that uses recipe ingredients as its input to accurately categorize different cuisines of the world. Along the way, you’ll also learn about more advanced input and output widgets, such as input validation, word clouds, and interactive maps.

Build Shiny Apps

Recipes

UFO Sightings

Mental Health in Tech Survey

Shootings

Shiny is an R package that makes it easy to build highly interactive web apps directly in R. Using Shiny, data scientists can create interactive web apps that allow your team to dive in and explore your data as dashboards or visualizations. If you want to bring your data to life, Shiny is the way to go! Using data about baby names, food ingredients, and UFO sightings, you'll build a variety of different Shiny apps that leverage different inputs and outputs. You’ll also learn the basics of reactive expressions. By the end of this course, you’ll have the Shiny skills you need to build your first app in R.

Introduction to the Tidyverse

Intermediate R

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations. 

Building Web Applications with Shiny in R

Programming

In the first chapter, you'll review the essentials of Shiny development. You'll get reintroduced to the basic structure of a Shiny application, as well as some core Shiny concepts such as inputs, outputs, and reactivity. Completing this chapter will help refresh your Shiny knowledge and ensure you have the required skills to develop Shiny apps for real-life scenarios.

Shiny review

Imagine you're preparing a figure for a manuscript using R. You spend a lot of time recreating the same plot over and over again by rerunning the same code but changing small parameters each time. The size of the points, the color of the points, the plot title, the data shown on the plot—these criteria all have to be just right before publishing the figure. To save you from the hassle of rerunning the code many times, you will learn how to create a Shiny app to make a customizable plot.

Make the perfect plot using Shiny

Let’s say your supervisor is impressed by the plot you created with Shiny and now wants to get familiar with the dataset you used in the plot. They don't want to simply have a raw data file, they want an interactive environment where they can view the data, filter it, and download it. This chapter will guide you in creating such an application—a Shiny app for exploring the Gapminder dataset.

Explore a dataset interactively with Shiny

Your friend really likes word clouds and has written an R function to generate them. They want to share this function with all their friends, but not all of them know how to use R. You offer to help by building a Shiny app that uses their function to let people create their own word clouds. This will allow all their friends—even the ones who are unfamiliar with R—to generate word clouds using a point-and-click interface. This chapter will guide you through the steps required to build this app.

Create your own word cloud in Shiny

After learning the basics of using Shiny to build web applications, this course takes you to the next level by putting your newly acquired skills into practice. You'll get experience developing fun and realistic Shiny apps for different common use cases, such as using Shiny to explore a dataset, generate a customized plot, and even create a word cloud. With all this practice and new knowledge, you will be well-equipped to develop Shiny apps for your own use.

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

Case Studies: Building Web Applications with Shiny in R

Reporting

In this chapter you will learn the basic structure of a Shiny Dashboard and how to fill it with static content.

Building Static Dashboards

In this chapter you will learn how to add dynamic content to your Shiny Dashboard.

Building Dynamic Dashboards

In this chapter you will focus on customizing the style of your Shiny Dashboard.

Customizing Style

In this chapter you will participate in a case study, practicing the skills you have acquired in the previous chapters.

Case Study

NASA fireball dataset

Starwars dataset

Once you've started learning tools for building interactive web applications with shiny, this course will translate this knowledge into building dashboards. Dashboards, a common data science deliverable, are pages that collate information, often tracking metrics from a live-updating data source. You'll gain more expertise using shiny while learning to build and design these dynamic dashboards. In the process, you'll pick up tips to optimize performance as well as best practices to create a visually appealing product.

In this course you'll learn to build dashboards using the shinydashboard package.

Building Dashboards with shinydashboard

In this chapter you will learn how R Markdown and the flexdashboard package are used to create a dashboard, and how to customize the layout of components on your dashboard.

Dashboard Layouts

This chapter will introduce the many options for including data visualizations in your dashboard. You'll learn about how to optimize your plots for display on the web.

Data Visualization for Dashboards

In this chapter you will learn about other components that will allow you to create a complete dashboard. This includes ways to present everything from a single value to a complete dataset.

Dashboard Components

This chapter will demonstrate how you can use Shiny to make your dashboard interactive. You'll keep working with the San Francisco bike sharing data and build a dashboard for exploring this data set.

Adding Interactivity with Shiny

San Francisco bike share data

San Francisco bike share station data

Communication is a key part of the data science process. Dashboards are a popular way to present data in a cohesive visual display. In this course you'll learn how to assemble your results into a polished dashboard using the flexdashboard package. This can be as simple as adding a few lines of R Markdown to your existing code, or as rich as a fully interactive Shiny-powered experience. You will learn about the spectrum of dashboard creation tools available in R and complete this course with the ability to produce a professional quality dashboard.

In this course you'll learn how to create static and interactive dashboards using flexdashboard and shiny.

Learning Experience

Business Features

Academics

Shiny Fundamentals with R

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Join over .css-w0wpus-TrackShowPage{color:#03ef62;}7,980,000 learners and start Shiny Fundamentals with R today!

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Join over 7,980,000 learners and start Shiny Fundamentals with R today!