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© 2016

Learn ggplot2 Using Shiny App

  • Step-by-step instructions—a tutorial approach to make beautiful plots without R code

  • Over 400 screen shots and illustrations

  • Makes creating graphics with ggplot2 easy and accessible

Book

Part of the Use R! book series (USE R)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Keon-Woong Moon
    Pages 1-14
  3. Keon-Woong Moon
    Pages 15-20
  4. Keon-Woong Moon
    Pages 21-32
  5. Keon-Woong Moon
    Pages 33-41
  6. Keon-Woong Moon
    Pages 43-50
  7. Keon-Woong Moon
    Pages 51-54
  8. Keon-Woong Moon
    Pages 55-65
  9. Keon-Woong Moon
    Pages 67-75
  10. Keon-Woong Moon
    Pages 77-84
  11. Keon-Woong Moon
    Pages 85-90
  12. Keon-Woong Moon
    Pages 91-102
  13. Keon-Woong Moon
    Pages 103-109
  14. Keon-Woong Moon
    Pages 111-120
  15. Keon-Woong Moon
    Pages 121-127
  16. Keon-Woong Moon
    Pages 129-139
  17. Keon-Woong Moon
    Pages 141-150
  18. Keon-Woong Moon
    Pages 151-162
  19. Keon-Woong Moon
    Pages 163-178
  20. Keon-Woong Moon
    Pages 179-189

About this book

Introduction

This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding.

In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript.  

This manual—"integrating" R, ggplot2, and Shiny—introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to become familiar with ggplot2 code. The app makes it easy to apply themes, make multiplots (combining several plots into one plot), and download plots as PNG, PDF, or PowerPoint files with editable vector graphics. Users can also make plots on any computer or smart phone.

Learn ggplot2 Using Shiny App allows users to
  • Make publication-ready plots in minutes without coding
  • Download plots with desired width, height, and resolution
  • Plot and download plots in png, pdf, and PowerPoint formats, with or without R code and with editable vector graphics

Keon-Woong Moon, M.D., Ph.D.,
 is Professor of Cardiology at the Catholic University of Korea and serves as the Director of Cardiology at St. Vincent’s hospital. In 2014, he completed the Data Science Specialization course authorized by Johns Hopkins University offered through Coursera. Recently he developed four R packages (mycor, moonBook, ztable, and ggiraphExtra) for distribution on CRAN. He  has taught residents, fellows, and junior staff about R and ggplot2 for many years, and he is the author of two books in Korean: R Statistics and Graphs for Medical Papers (2015, Hannarae) and Web-Based Analysis without R in Your Computer (2015, Hannarae).

Keywords

R graphics visualization ggplot2 vector graphics powerpoint R code plot shiny app

Authors and affiliations

  1. 1.St. Vincent’s Hospital, The Catholic University of KoreaSuwonKorea (Republic of)

About the authors

Keon-Woong Moon, M.D., Ph.D., is Professor of Cardiology at the Catholic University of Korea and serves as the Director of Cardiology at St. Vincent’s hospital. In 2014, he completed the Data Science Specialization course authorized by Johns Hopkins University offered through Coursera. Recently he developed four R packages (mycor, moonBook, ztable, and ggiraphExtra) for distribution on CRAN. He  has taught residents, fellows, and junior staff about R and ggplot2 for many years, and he is the author of two books in Korean: R Statistics and Graphs for Medical Papers (2015, Hannarae) and Web-Based Analysis without R in Your Computer (2015, Hannarae).

Bibliographic information

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