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R Data Visualization Recipes

You're reading from   R Data Visualization Recipes A cookbook with 65+ data visualization recipes for smarter decision-making

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Length 366 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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 Bianchi Lanzetta Bianchi Lanzetta
Author Profile Icon Bianchi Lanzetta
Bianchi Lanzetta
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Table of Contents (19) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Installation and Introduction FREE CHAPTER 2. Plotting Two Continuous Variables 3. Plotting a Discrete Predictor and a Continuous Response 4. Plotting One Variable 5. Making Other Bivariate Plots 6. Creating Maps 7. Faceting 8. Designing Three-Dimensional Plots 9. Using Theming Packages 10. Designing More Specialized Plots 11. Making Interactive Plots 12. Building Shiny Dashboards

Building a shiny dashboard


Your shiny web application can be drawn as a dashboard. Translating a column shiny app to a dashboard version requires only small amounts of effort when you have the shinydashboard package installed. This recipe's goal is to introduce you to how to combine shiny and shinydashboard packages to design a web application within the dashboard format.

Getting ready

Besides plotly, Ecdat, and dplyr packages, we will also need the shinydashboard package:

if(!require(shinydashboard)){install.packages('shinydashboard')}
if(!require(plotly)){install.packages('plotly')}
if(!require(Ecdat)){install.packages('Ecdat')}
if(!require(dplyr)){install.packages('dplyr')}

The shiny package is still a requirement. Once all these are ready, we can go on and design a dashboard.

How to do it...

Instead of using shiny functions, the dashboards made by this recipe will greatly rely on functions designated by the shinydashboard package instead. The logic beneath the shinydashboard package is very...

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