Introduction to S Programming in R: Features, Objects, and Classes
This session provides a comprehensive introduction to S programming in R, presented by Bill Venables. It covers the fundamental features of the S language, explaining its object-oriented structure where everything is an object belonging to a class. Participants will learn about object manipulation, querying, display, and comparison. The session also addresses how to locate objects within the search path, manage startup options, and utilize various methods for input/output operations. Enhance your understanding of R programming by exploring these essential concepts.
Introduction to S Programming in R: Features, Objects, and Classes
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Presentation Transcript
S Programming in R Bill Venables CSIRO Mathematics and Information Sciences Auckland, 7 July 2006
Session 1 Introduction Background, basic features and
The S Language • “S is a language for manipulating objects” • A function language • An object oriented language • Objects are the vehicle for information in S • Objects may be • constructed • interrogated • displayed • compared • modified, … S Programming in R
Objects and classes • “In S everything is an object and every object has a class”. • Objects: • data (vectors, matrices, character vectors, …) • objects constructed from data (fitted models, graphics objects, &c) • functions and other language elements • connections (file, text, …) • classes themselves, meta data, • … S Programming in R
How are objects located? • In one sense, on the search path > search() [1] ".GlobalEnv" ".R_Store" [3] "package:fortunes" "package:rpart" [5] "package:MASS" "package:ASOR" [7] "package:methods" "package:stats" [9] "package:graphics" "package:grDevices" [11] "package:utils" "package:datasets" [13] ".R_Utils" "package:svIDE" [15] "package:tcltk" "Autoloads" [17] "package:base" S Programming in R
What happens at startup? > ?.Rprofile Startup package:base R Documentation Initialization at Start of an R Session Description: In R, the startup mechanism is as follows. ..... S Programming in R
More on startup • Rprofile.site • File in R_HOME/etc • Invoked for all R sessions on the current machine • Probably best left alone • .Rprofile • File in R_USER or current working directory • Invoked for all R sessions for this user (or with this working directory) • Very useful for setting options • .Renviron, Rconsole, Rdevga S Programming in R
Getting Help in General • Help on a specific object or entity: • ?object ## and variants • help(object) • help.start() • RSiteSearch("keyword or phrase") • Help on packages is similarly available, • For a few packages • vignette("package_name") Gives an overview of what's available. S Programming in R
Adding to the search path • library(MASS) • require(MASS) • attach(list_object_or_data_frame) • detach(position_or_name) • Locally adding to the path • value <- with(object, <expression>) • dataset <- transform(dataset, v1 = x1, v2 = x2, ...) • dataset <- subset(dateset, condition, select = ...) • The 'data' argument in fitting functions, lattice, &c S Programming in R
More convenience features The (unofficial) ASOR package • Based on a CRAN package, 'gdata', by David Brahm, but not yet an official package – yet, • Allows you to 'offload' objects from memory, while remaining visible on the search path, • If objects are needed, they are placed back in memory • Attach() – makes saved objects visible • Save(...) – removes objects form .GlobalEnv • Objects() – lists offloaded objects attaching if necessary • Remove(...) – permanently removes saved objects. • Uses the idea of a "promise" to load the object, if necessary. • Not restricted to large objects S Programming in R
Some extracts from an .Rprofile options(show.signif.stars = FALSE, length = 999999) options(CRAN = "http://cran.ms.unimelb.edu.au") options(repos = c(CRAN = getOption("CRAN"), CRANextra = "http://www.stats.ox.ac.uk/pub/RWin")) options(save.defaults = list(compress = TRUE, ascii = FALSE, safe = TRUE)) autoload("xyplot", "lattice") autoload("odbcConnectExcel", "RODBC") autoload("stepAIC", "MASS") S Programming in R
Front ends • Tinn-R • Windows only • Now requires R to run in SDI mode • Very useful front end for working with R and keeping a working script • Emacs/ESS • Offers similar functionality • Available for Windows/Linux/Unix/Mac? • Rcmdr and SciViews both offer front ends with strengths and weaknesses. S Programming in R
Some input and output • scan() • read.table(), read.csv(), read.delim(), ... • write.table(), write.csv(), ... • sink(), print(), cat() – standard • source() • data.dump(), data.restore() – hardly needed • save(), save.image(), load(), ... • Connections – to external files or character string vectors • RODBC package allows external connections to data bases • con <- odbcConnectExcel("microsoft.xls") S Programming in R
