R Shiny Interactive Web Apps - Next Level Data Visualization

Name: R Shiny Interactive Web Apps - Next Level Data Visualization
Rating: 4.1 (1684 reviews)

Learn how to use R and Shiny to create compelling data visualizations and how to share them online.

Created byR-Tutorials Training

Last updated 7/2017

English

English [Auto],

What you'll learn

generate advanced shiny web apps
share apps over the internet or locally
embed pdfs, videos, images and text in a web app
create multi page shiny apps
add focus and zooming tools to shiny apps
generate shiny apps based on data tables
use pre defined layouts for styling
generate downloadable tables

Course content

4 sections • 30 lectures • 2h 53m total length

Welcome to R Shiny2:23
Learn to build interactive R Shiny web apps with input widgets, filters, and dynamic plots, master app structure, styling, and embedding web content.
Get ready for R Shiny11:51
Explore building interactive R Shiny apps for advanced data visualization, mastering dashboards, filters, parameters, and interactive charts and tables, with deployment options and practical project work.
The Basic Shiny Template7:54
Explore the basic shiny template and its server, input, output, and session components, along with user interface concepts, sliders, plots, and deployment naming conventions.
The Input Widget Gallery - Tools to Enable User Input6:32
Explore the R Shiny widget gallery to learn common input widgets for capturing user input. Use dates, text, numbers, files, checkboxes, radio buttons, sliders, and action buttons to drive outputs.
The Link List4:00
Navigate a comprehensive link list of tools and documentation for building Shiny apps. It highlights official Shiny documentation by RStudio, deployment options, input widgets, layout guides, and beginner resources.
Link Collection0:39

Section II3:14
Connect the user interface to the server in a Shiny app using reactive input and the render plot and plot output to build interactive GDP charts with multi-page layouts.
Section Script - Shiny Basics1:28
Integrating an Input Widget - The User interface Side5:53
Learn how to integrate text input and checkbox input in the user interface, using input IDs, labels, and default values to enable user interaction.
Connecting an Input Widget with the Server4:30
Connect user input to the server in a Shiny app using observe and updateTextInput to drive a reactive second box; learn render, reactive, and observe event.
Using Functions Render and Reactive - Reactivity6:32
Explore how a Shiny app combines reactive expressions and render functions to produce an interactive scatter plot controlled by a slider.
Planning Your App Layout4:24
Discover how to plan shiny app layouts that balance analytics with visuals, using fluid pages and a sidebar layout to create responsive, professional dashboards in R.
Multi Page Apps - Using Tabsets3:49
Explore how to build multi-page Shiny apps with tab sets, using tabsetPanel and tabPanel to create three tabs, a sidebar with a slider, and a responsive main panel.
HTML Tags in Shiny9:15
Learn how shiny translates your user interface into HTML and use direct tags, with tags, and the text dollar sign prefix to build R Shiny apps with HTML tags.
Style Your App with shinythemes3:22
Style your Shiny app with themes from Shiny Themes and CSS options like includeCSS, inline CSS with shinyJS, or head tag styling, then apply a theme such as darkly.

Section III3:37
Deploy Shiny apps on a dedicated server, use render data table and data table output for interactive tables with CSV downloads, and embed documentation with HTML tags.
Section Script - Advanced Shiny1:15
Publishing and Sharing6:27
Publish and share Shiny apps by deploying to Shiny apps.io or your own server, ensuring R and Shiny are available on the server and testing locally across viewers and browsers.
Shinyapps.io5:49
Deploy Shiny apps via Shiny App Store by connecting to GitHub or Google, installing RS Connect, and publishing with app.R, server.R, and UI.R while enabling authentication.
Integrating Tables with DT13:42
Explore integrating interactive data tables into Shiny with the DT package, handle function conflicts between Shiny and DT, and customize tables with currency formatting, colors, filters, and options.
Add Brush and Click Selection Tools to Your App12:33
Explore how to make Shiny plots responsive to user input with brush and click selections, linking interactive plots to tables using brushed points and nearPoints.
Downloadable Tables5:01
Learn to export brushed selections from a Shiny data table to a csv file using a download button and download handler in an interactive diamond dataset app.
Integrating all Sorts of Media10:05
Learn to embed media types—video, image, iframe, and text—from local and online sources in a Shiny app using tags and a text include function across a four-tab navbar.
Tools for Your Own Apps4:43
Explore the shiny gallery for use cases to build advanced shiny apps. Learn about interactive visualizations, widgets, layouts, reactive programming, and accessing underlying code or GitHub resources.

Take a Look at the Project Data - and download here3:28
Explore a mining stock dataset with 50 observations, market capitalization, symbols, and grade-based plots; compute a score with user weights and load a semicolon-separated csv into an R Shiny app.
Project Description - Your Homework8:16
Discover the mining stock scale app in R Shiny, using g1, g2, g3 grade factors and sliders to visualize valuations and export results to csv.
Project Solution - User Interface8:10
Create a three-tab shiny interface with sliders, a brush-enabled plot, and a data table plus download button, all styled with the sandstone theme and integrated documentation iframe.
Project Solution - Server10:57
Show how to build a Shiny server that loads a semicolon-delimited csv, uses ggplot2 and dt with shiny themes, and enables reactive data processing, brushing, and csv download.
Project Script0:40
Conclusion2:51
Conclude this shiny tutorial by reflecting on the journey and deployment options, including WordPress iFrame embedding and shinyapps.io hosting, while reinforcing concepts like tables, plots, download features, and input widgets.

Requirements

Basic R knowledge
General R data visualization skills (ggplot2, R base)
Computer with R and RStudio already installed

Description

R shiny allows you to present your data interactively – that means your app users can:

Set filters and columns in tables
Generate parameters for plots
Zoom and focus on specific areas of plots
Focus on selected portions of your data
Provide or upload files, text and all sorts of data
And much more

App users can do all of this without any R knowledge. You do the coding, your users get the info they are looking for!

In this course I will show you step by step how to master R Shiny. We will start out with the general shiny script – all scripts should have the same basic structure.

You will then learn how to make your app interactive by using input widgets. These features take user inputs which can be used to generate or modify the app content.

You will learn how to style your app for an appealing layout.

I will also show you how to use HTML tags to integrate or embed standard web content like youtube videos, pdfs, text, pictures and much more.

After that you will learn about advanced shiny apps that allow zooming and downloading

And you will learn how to integrate tables.

This course is not just pure theory. The last section is all about applying your new shiny skills. I prepared a course project which combines all the topics discussed in the course and more. This project is modeled after a real world financial app. You will get the project description and the raw data to test your skills.

Note that this course requires basic R skills. If you are totally new to R, check out some R intro material first and then revisit the course.

All the software downloads, add on packages as well as entry level hosting for shiny are totally free. I will show you what you need and where to get it. That includes hosting as well.

Take a look at shiny – your boss, colleagues, students, customers will be astonished what modern day data visualization can do.

Who this course is for:

Business analysts
Data scientists
Entrepreneurs
Students looking for modern data visualizations tools
Everybody interested in data science and visualization

R Shiny Interactive Web Apps - Next Level Data Visualization

What you'll learn

Explore related topics

Course content

Course Introduction6 lectures • 33min

The Basics of R Shiny9 lectures • 42min

Publishing and Advanced Concepts of Shiny9 lectures • 1hr 3min

Course Project - Get Your Feet Wet6 lectures • 34min

Requirements

Description

Who this course is for: