![]() We will use the RStudio IDE, which according to its developers “is a powerful productive user interface for R.” 6 RStudio is widely used, it is used increasingly in the R community, and it makes learning to use R a bit simpler. At minimum, an IDE typically consists of a source code editor and build automation tools. These interfaces are used to facilitate software development. Generally such interfaces are referred to as integrated development environments (IDE). Several enhanced interfaces for R have been developed. A new user can (relatively) quickly gain enough skills to obtain, manage, and analyze data in R.It has an incredible variety of contributed packages.R is under constant and open development by a diverse and expert core group.It is one of, if not the, most widely used software environments in data science.This book focuses on R for several reasons: Each has strengths and weaknesses, and often two or more are used in a single project. Various statistical and programming software environments are used in data science, including R, Python, SAS, C++, SPSS, and many others. 11.6 A Summary of Useful graphics Functions and Arguments.8.4.2 Michigan Campgrounds Server Logic.8.4 More Advanced Shiny App: Michigan Campgrounds.7.2 Programming: Conditional Statements.6.2 Reading Data with Missing Observations. ![]()
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