Book Image

Mastering RStudio: Develop, Communicate, and Collaborate with R

4 (1)
Book Image

Mastering RStudio: Develop, Communicate, and Collaborate with R

4 (1)

Overview of this book

RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will help you to solve real-world data problems. This book begins by guiding you through the installation of RStudio and explaining the user interface step by step. From there, the next logical step is to use this knowledge to improve your data analysis workflow. We will do this by building up our toolbox to create interactive reports and graphs or even web applications with Shiny. To collaborate with others, we will explore how to use Git and GitHub and how to build your own packages to ensure top quality results. Finally, we put it all together in an interactive dashboard written with R.
Table of Contents (17 chapters)
Mastering RStudio – Develop, Communicate, and Collaborate with R
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Summary


In this chapter, you have learned how to take advantage of the useful shinydashboard packages, which extensively enhance the Shiny app framework to build professional dashboards. In the beginning, we dedicated ourselves fully to the general layout structure of a Shiny dashboard. You have learned how to set up the header, sidebars, and body. Furthermore, you learned how to create different data boxes and options to customize the whole appearance of a dashboard application.

In the second part of this chapter, we imagined that we work for a fictional company called FantasticFutureTec. It was our task to build a useful KPI dashboard for our company by using all of our current knowledge about R, RStudio, and the Shiny framework. We started this by thinking about the right data architecture and ETL processes to obtain the data from our sources. Next, we drew up a fast dashboard sketch to visualize our final ideas and the planned look and feel. Thereafter, it was hands-on work and we showed...