Book Image

Learning RStudio for R Statistical Computing

Book Image

Learning RStudio for R Statistical Computing

Overview of this book

Data is coming at us faster, dirtier, and at an ever increasing rate. The necessity to handle many, complex statistical analysis projects is hitting statisticians and analysts across the globe. This book will show you how to deal with it like never before, thus providing an edge and improving productivity. "Learning RStudio for R Statistical Computing" will teach you how to quickly and efficiently create and manage statistical analysis projects, import data, develop R scripts, and generate reports and graphics. R developers will learn about package development, coding principles, and version control with RStudio. This book will help you to learn and understand RStudio features to effectively perform statistical analysis and reporting, code editing, and R development. The book starts with a quick introduction where you will learn to load data, perform simple analysis, plot a graph, and generate automatic reports. You will then be able to explore the available features for effective coding, graphical analysis, R project management, report generation, and even project management. "Learning RStudio for R Statistical Computing" is stuffed with feature-rich and easy-to-understand examples, through step-by-step instructions helping you to quickly master the most popular IDE for R development.
Table of Contents (13 chapters)

R projects


In Chapter 1, Getting Started, we introduced the concept of a compendium—the set of scripts and data files that reproduce a statistical analyses as well as the report that is based on it. Managing growing sets of interdependent files, especially when multiple people are working on the same analyses, can be a hassle. RStudio's project management features make things a lot more manageable.

Tip

Always create an RStudio project, even for simple analyses—it makes managing your scripts a lot easier with virtually no extra effort.

Technically, an RStudio project is just a directory with the name of the project and a few files and folders created by RStudio for internal purposes. It typically holds your scripts, data, and reports, which you may manage through RStudio's file manager tab or through your operating system's file manager. The project directory can also contain subdirectories.

When a project is reopened, RStudio opens every file and data view that was open when the project was...