MAS Medizinphysik — Using R MAS Medizinphysik — Using R 1. Introduction excerpt from the lecture at ETHZ (1V + 1U) , Autumn Sem. 2010 In this Chapter you will ... Cornelia Schwierz, Andreas Papritz, ... learn what R is ... see a few first examples Martin M¨ achler <maechler@stat.math.ethz.ch> ... learn how to operate R Seminar f¨ ur Statistik, ETH Z¨ urich ... learn how to read in data ... learn how to quit an R session January 20, 2011 0partly based on work by Werner Stahel and Manuel Koller 0slides rendered (by L A T EX) on January 19, 2011 1 / 154 2 / 154 1.1 What is R? 1.2 Other Statistical Software ◮ S+ (formerly “S-PLUS”) same programming language, ◮ R is a software environment for statistical computing. commercial. Features a GUI. ◮ R is based on commands. Implements the S language. ◮ SPSS: good for standard procedures. ◮ There is an inofficial menu based interface called R-Commander. ◮ SAS: all-rounder, good for large data sets, complicated analyses. ◮ Drawbacks of menus: difficult to store what you do. A script of commands ◮ Systat: Analysis of Variance, easy-to-use graphics system. ◮ documents the analysis and ◮ Excel: Good for getting (a small!) dataset ready. Very limited ◮ allows for easy repetition with changed data, options, ... collection of statistical methods. ◮ R is free software. http://www.r-project.org Not for serious data analysis! Supported operating systems: Linux, Mac OS X, Windows ◮ Matlab: Mathematical methods. Statistical methods limited. ◮ Language for exchanging statistical methods among researchers Similar “paradigm”, less flexible structure. 3 / 154 4 / 154
1.3 Introductory examples A dataset that we have stored before in the system is called d.sport ◮ Scatter plot: type plot(d.sport[,"kugel"], d.sport[,"speer"]) weit kugel hoch disc stab speer punkte OBRIEN 7.57 15.66 207 48.78 500 66.90 8824 ◮ First argument: x coordinates; second: y coordinates BUSEMANN 8.07 13.60 204 45.04 480 66.86 8706 ◮ Many(!) optional arguments: DVORAK 7.60 15.82 198 46.28 470 70.16 8664 : : : : : : : : plot(d.sport[,"kugel"],d.sport[,"speer"], : : : : : : : : xlab="ball push",ylab="javelin",pch=7) : : : : : : : : CHMARA 7.75 14.51 210 42.60 490 54.84 8249 ◮ Scatter plot matrix Draw a histogram of the results of variable kugel : We type pairs(d.sport) hist(d.sport[,"kugel"]) Every column of d.sport is plotted against all other columns. The graphics window is opened automatically. We have called the function hist with argument d.sport[,"kugel"] . [, j] is used to select the column j . 5 / 154 6 / 154 1.4 Using R An R statement 1 is typically either ◮ a name of an object − → object is displayed ◮ Within a window running R, you will see the prompt ’ > ’. > d.sport You type a command and get a result and a new prompt. ◮ a call to a function − → graphical or numerical result > hist(d.sport[,"kugel"]) > hist(d.sport[,"kugel"]) > ◮ an assignment > a <- 2*pi/360 An incomplete statement can be continued on the next line > mn <- mean(d.sport[,"kugel"]) > plot(d.sport[,"kugel"], stores the mean of d.sport[,"kugel"] + d.sport[,"speer"]) under the name mn 1 R “statement”: more precisely R “function call” 7 / 154 8 / 154
Reading and Writing Data Get a dataset from a text file on the internet and assign it to a name: > d.sport <- read.table( + "http://stat.ethz.ch/Teaching/Datasets/WBL/sport.dat") Read a file in table format and create a data frame from it. For data files with a one-line header, you need to set the option With cases corresponding to lines and variables to fields. header = TRUE , ◮ Text-files: > d... <- read.table(... , header = TRUE) > read.table(file, header = FALSE, sep = "", + dec = ".", row.names, col.names,...) To download the file first to the local computer, R provides the ◮ Excel-files: command > read.csv(file, sep = ",", dec=".",...) > download.url("http://...") > read.csv2(file, sep = ";", dec=",",...) Get all possible arguments and defaults with ?read.table Use file browser (of the underlying operating system) to open a file: > d.sport <- read.table(file.choose()) 9 / 154 10 / 154 To save or write data to a file: ◮ Text-files: > write.table(x, file = "", append = FALSE, Reading Data (ctd.) + sep = " ",eol = " \ n", na = "NA", dec = ".", + row.names = TRUE, col.names = TRUE, ...) ◮ Tabulator-separated files: where x is the data object to be stored. > read.delim(file, sep = " \ t", dec=".",...) ◮ Excel-files: > read.delim2(file, sep = " \ t", dec=",",...) > write.csv(...) ◮ R-Data: > write.csv2(...) > load(file=’’myanalysis.Rdata’’) ◮ R-Data files: > load(file=’’C:/myanalysis.Rdata’’) > save(..., file, ascii = FALSE,...) Example: > x <- c(1:20) > y <- d.sport$kugel > save(x, y, file = "xy.Rdata") 11 / 154 12 / 154
Getting Help ◮ R stores all created “objects” in your workspace. List them by either ls() or equivalently, objects() : ◮ Documentation on the arguments etc. of a function > ls() (or dataset provided by the system): [1] "a" "d.sport" "mn" > help(hist) or ?hist ◮ Objects have names like a, fun, d.sport On the help page, the section “See Also...” contains related ◮ R provides a huge number of functions and other objects functions that could help you further. ◮ Arguments of functions are provided either by using their name, ◮ Search for a specific keyword: e.g. read.table(...,header=TRUE) , or by placing them > help.search("matrix") Lists packages and at their defined position (as defined in the help-pages). functions related to or using “matrix”. ◮ You can see the function definition (“source”) by typing its name Note: Takes a long time when you have many extra R packages installed without () : ◮ For many functions and data sets, examples are provided on the > read.table help page ( ?matrix ). You can execute them directly, ◮ Comments can be added using “#” : > example("matrix") > ls() ## Comments are ignored by R 13 / 154 14 / 154 Resources on the internet 1.5 Scripts and Editors ◮ R’s Project page http://www.r-project.org/ 2 Instead of typing commands into the R console, you can generate commands by an editor and then “send” them to R ... and later modify ◮ CRAN: use Swiss mirror 3 http://cran.CH.r-project.org/ : (correct, expand) and send again. Text Editors supporting R Links to Search (several search possibilites), Task Views (thematic collections of functions), Contributed (electronic ◮ WinEdt: http://www.winedt.com/ Documentation, Introductions) and FAQs . ◮ Emacs 4 with ESS: The following list could be extended “infinitely”: http://ESS.r-project.org/ 5 ◮ http://search.r-project.org/ : Search specific for R, also ◮ Tinn-R: http://www.sciviews.org/Tinn-R/ accessed via R function RSiteSearch() . Functions, Help, ◮ . . . and several more, partly depending on platform (Windows / etc. Mac / Linux) . . . . . . ◮ http://www.rseek.org/ : A “Google-type” search specific for R. Delivers Functions, Help Forums, etc. 4 http://www.gnu.org/software/emacs/ 2 all URLs on this page are “clickable” 5 For Windows and Mac, on the Downloads tab, look for the “All-in-one installation” 3 the Swiss CRAN mirror is at stat.ethz.ch by Vincent Goulet 15 / 154 16 / 154
The Tinn-R Window Define Tinn-R Keyboard Shortcuts: Menu item R / Hotkeys of R 17 / 154 18 / 154 MAS Medizinphysik — Using R 2. Basics Leave the R session: > q() You get the question: In this Chapter you will ... Save workspace image? [y/n/c]: ... learn how to select elements from a data set If you answer ”y”, your objects will be available for your next session. ... find out about vectors (numerical, logical, Note that we usually answer “ n ” 6 , but always store the script (*.R) files. character) ... use R as a calculator ... learn how to create and manipulate matrices 6 and M.M. even eliminates that question by starting R as R --no-save 19 / 154 20 / 154
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