8.1 Come analizzare i dati: R

Transcription

1 8.1 Come analizzare i dati: R Insegnamento di Informatica Elisabetta Ronchieri Corso di Laurea di Economia, Universitá di Ferrara I semestre, anno Elisabetta Ronchieri (Universitá) Insegnamento di Informatica I semestre, anno

2 Argomenti R Introduction What is R? R Installation R packages R Help and Doc R Workspace 1 / 22

3 Argomenti R Introduction What is R? R Installation R packages R Help and Doc R Workspace 2 / 22

4 What is R? R is a free software programming language and software environment for statistical computing and graphics. R is a dialect of the S language. 3 / 22

5 What is S? S is a language, developed by John Chambers and others at Bell Labs. S was initiated in 1976 as an internal statistical analysis environment, originally implemented as Fortran libraries. Early versions of the language did not contain functions for statistical modeling. In 1988 the system was rewritten in C and began to resemble the system that we have today (this was Version 3 of the language), including the statistical analysis functionality. Version 4 of the S language was released in 1998 and is the version we use today [Chambers, 2009]. Other books are available at 4 / 22

6 Back to R 1991: Created in New Zealand by Ross Ihaka and Robert Gentleman. 1993: First announcement of R to the public. 1995: Martin M achler convinces Ross and Robert to use the GNU General Public License to make R free software. 1996: A public mailing list is created (R-help and R-devel) 1997: The R Core Group is formed (containing some people associated with S-PLUS). The core group controls the source code for R. 2000: R version is released. 2014: R version is released on July / 22

7 Features of R Runs on almost any standard computing platform/os. Frequent releases (annual + bug fix releases). Active development. Functionality is divided into modular packages. Graphics capabilities very sophisticated. Contains a powerful programming language for developing new tools (user versus programmer). R has an amazing ecosystem of developers. R-help and R-devel mailing lists. 6 / 22

8 R is a free software With free software, you grant different levels of freedom: 1. to run the program, for any purpose. 2. to study how the program works, and adapt it to your needs. 3. to redistribute copies so you can help your neighbor. 4. to improve the program, and release your improvements to the public, so that the whole community benefits. Free Software Foundation (FSF) 7 / 22

9 Drawbacks of R They are mainly related to our knowledge. However, R: is essentially based on 40 year old technology; is based on consumer demand and user contributions; is not ideal for all possible situations (but this is a drawback of all software packages). partly supports 3-D graphics (but things have improved greatly since the old days). generally requires to store objects in physical memory, but there have been advancements to deal with this too. 8 / 22

10 Design of the R System The R system is divided into 2 conceptual parts: 1. the base R system that you download from CRAN ( 2. a collection of user contributed add-on packages. 9 / 22

11 Design of the R System R functionality is divided into a number of packages: The base R system contains, among other things, the base package which is required to run R and contains the most fundamental functions. Implementation of statistical and graphical procedures are separated from the base system, organized in packages. The main packages contained in the base system include utils, stats, datasets, graphics, grdevices, grid, methods, tools, parallel, compiler, splines, tcltk, stats4. There are also Recommend packages: boot, class, cluster, codetools, foreign, KernSmooth, lattice, mgcv, nlme, rpart, survival, MASS, spatial, nnet, Matrix. 10 / 22

12 Design of the R System R functionality is divided into a number of packages: There are about 4000 packages on CRAN that have been developed by users and programmers around the world. There are also many packages associated with the Bioconductor project ( There are packages related to econometrics 1 like ecdata [Farnsworth, 2008]. People often make packages available on their personal websites. There is no reliable way to keep track of how many packages are available in this fashion. 1 Econometrics is the tasks of developing and applying quantitative or statistical methods to the study and elucidation of economic principles 11 / 22

13 Argomenti R Introduction What is R? R Installation R packages R Help and Doc R Workspace 12 / 22

14 Steps to install R 1 Go to the website: ( r-project. org) 2 Click on the download link for your Operating System (OS), such as Windows and Linux. 13 / 22

15 Steps to install R 3 Click on base. 14 / 22

16 Steps to install R 4 Click on Download. 15 / 22

17 Steps to install R 5 Once the file is done downloading (selected Windows), open it up to begin the R installation. 6 Set some configuration options like SDI (separate windows) or create a desktop icon. 7 Click on Next. 16 / 22

18 Steps to open R 1 Find a program called R. R is the environment for your analysis. 2 Once R opens, you ll see: an introductory message; a prompt >. 17 / 22

19 R packages Packages not included in the base distribution can be installed from the R prompt. Given an Internet connection, a package called package-name is installed by supplying the name of the package to the install.packages() function: > install.packages("package-name") The package functionality is available after attaching the package by the library() function > library("package-name") Available packages can be obtained from 18 / 22

20 R Help and Doc 1. Online help comes with the base distribution or packages. It is a collection of manual pages describing function and data set that comes with R. 2. Electronic manuals are shown on web browser when the name of the function is supplied to the help() function: > help("mean") or >?mean 3. Publications work. Extensive documentation is available from the collection of manuals at 19 / 22

21 R Workspace Get workspace directory: > getwd() Set workspace directory: > setwd( NewDirectory ) or by R GUI (File Change Dir) 20 / 22

22 Save and Load Files Save data.rdata by R GUI (File Save Workspace) Save data.rhistory by R GUI (File Save History) Load.Rdata by R GUI (File Load Workspace) or by clicking directly on the file.rdata Save data.rhistory by R GUI (File Save History) Load.R script > load( filename ) 21 / 22

23 Per ulteriori letture John M. Chambers, Software for data analysis: Programming with R (Statistics and Computing), Springer (2008), Chambers_-_Software_for_Data_Analysis_-_ Programming_with_R.pdf Grant V. Farnsworth, Econometrics in R, October 26, 2008, Farnsworth-EconometricsInR.pdf 22 / 22