Getting started with R - coli.uni-saarland.degambi/lectures/GettingStartedwithR.pdf · Getting...

Getting started with RChiara Gambi

Tuesday 24 September 2013

Step 1 - Download

• Download the latest version of R and R studio from the websites listed on the course page onto your laptop.

• Installation should proceed smoothly, just follow the on-screen instructions

• Download R first

• Then download R studio


Step 2 - R studio basicsConsole & Script

• Open up R studio.

• This will automatically start an R session in the window on the bottom left corner: this window is the Console.

• You can type commands directly into the Console, which is good to try things out when you're not sure if they will work.



• Once you know what your doing, you should use an R script.

• This is displayed in the top left corner within R studio. If one is not already open, go to File --> New --> R script.



IMPORTANT NOTE

• Always type the commands you want to save for later on in the Script.

• You can save the output of R calculations, which is the content of the Workspace (go to Session --> Save Workspace As), at any time but you cannot save the list of commands you used to get that output unless you type them in a Script.

• Also, it's good to get into the habit of commenting on the commands as you go along, so that you can remember what each does. Anything that is preceded by # in the script will be treated by R as a comment and will not run.



• When the commands are typed into the Console just press ENTER to run.

• When the commands are typed into the Script, position your cursor on the command line (or highlight a group of lines) and hit RUN in the top right corner of the Script window.

• Alternatively, CMD + ENTER for Mac users or CTRL + ENTER for Windows users

• If a command is incomplete, R signals that it is waiting for more input by showing a + in the Console. To start anew when this happens, just hit ESC.



• If you realize a command you have used before is useful, but you forgot to type it in the script...

• you can still find it (provided you did not quit the session) in the History tab on the top right corner.


Step 3 - R studio basicsWorking Directory & Projects

• When working with R, it is crucial to know in which directory you want R to look for input and save output.

• Typically, you want your script and your data to be in the same directory.

• If you stick to this rule, when you open a saved script in R studio, all you have to do is to go to Session --> Set working directory --> To source file location

• which will tell R to look for files within the same directory of the current active script.



• If you want to avoid this step, you can create a project in R studio.

• Anytime you open a project, R will be directed towards the right folder.



• In any case, you can:

• check what the current directory is:

• use the command: getwd()

• set the current directory to any path within your machine:

• use the command: setwd("~/path") on Mac; setwd("C:/path") on Windows

(By default, R works in the home directory: ~/users/YourUsername on Mac).


Step 3 - R studio basicsWorkspace

• The output of all R calculations is temporarily stored in the workspace.

• You can check the contents of the workspace in the top right corner.

• Before quitting a session, R studio will prompt you to save the contents of the workspace. When you resume the session, you can load the contents of a previously saved workspace


Step 3 - R studio basicsWorkspace

• IMPORTANT NOTE

• R is very much like a calculator. It will not store anything (not even temporarily) unless you tell it to! Whenever you wish to store the output of a calculation for use in following calculations, you need to assign the calculated expression to an object (a variable). The assignment operator is <-

variable <- assigned expression

e.g., x <- 3*10+4/2x[1] 32


Step 3 - R studio basicsInstalling & loading packages

• The basic R installation allows you to do quite a lot, but the real power of R comes from the extensive range of freely available packages.

• Whatever you need to do, R has a package for it!

• Baayen's "Analyzing linguistic data with R" comes with a package, languageR, which you should install before the course starts. Here is how to do it in R studio.

Go to Tools --> Install packages

If prompted to create a package repository, just follow the instructions.

Then, type the package name under Packages, and hit Install.

IMPORTANT NOTE: your computer needs to be connected to the Internet for this to work!!!


Step 3 - R studio basicsInstalling & loading packages

• To load the packages in the current session, type the following in the Console

library(PackageName)

e.g., library(languageR)


Step 4 - R basicsReading in the data

• The next two sections are based on Baayen (2008). Analyzing linguistic data with R. Chapter 1 (up to and including section 1.3)

• You should have installed and loaded languageR before you continue!

• Please, go through these brief exercises and read up to p. 10 of Baayen's book before the course starts.



• First, run the following line:

• write.table(verbs, file = "/users/yourusername/yourfolder/dativeS.csv") #for Mac

• write.table(verbs, file = "C:/yourfolder/dativeS.csv") # for Windows

• This will create a file (dativeS.csv) on the specified location on your computer.

• If you open the file using any text editor, Excel, or Numbers, you will see that it contains 5 columns and several rows.

• The first row does not contain data, but gives the column names: RealizationOfRec, Verb, AnymacyOfRec, AnimacyOfTheme, LengthOfTheme.



• You will normally have your data in .csv or .txt format saved in the same directory as your R script. Make sure this directory is set as the current working directory (see Step 3).

• Then, read the data as follows:

• verbs<-read.table("dativeS.csv", header=T) # NOTE: this only works if yourfolder (as specified in the write.table command) is the current working directory!

• This creates an R object called verbs (you can see it in your Workspace now) that is of a special kind, namely a data frame.

• By specifying header=T you tell R that the first row in the file dativeS.csv is to be treated differently from all other rows, as it gives the column names.



• In R, you can also create and work with other types of objects: common ones include vectors, matrices, and lists. You can check what type of object you are dealing with using:

• class(objectname)

• Now, if you type names(verbs), R will return a list of names of the columns in the data frame.



• Also, in R studio, if you type verbs$ and then press the Tab key, you will be presented with the list of column names.

• Because verbs is a data frame you can refer to the columns within it with this syntax:

• dataframename$columnname

• e.g., verbs$Verb



• Alternatively, you can refer to any combination of columns and rows in a data frame using subscripting, with the following syntax:

• dataframename[rowID,columnID]

• You can refer to a row or column using the row/column number submitted as an integer:

Examplesverbs[1,1] # returns the element at the intersection of the first row and first columnverbs[1,] # returns all the elements in the first row (from all columns)verbs[,1] # returns all the elements from the first column (from all rows)



• You can refer to a subset of rows/columns in (at least) three ways:

a. 1:4 #all rows/columns from (and including) 1 to (and including) 4b. c(2,6) #row/column 2 and 6

NOTE: c is the concatenate function, useful to create vectors. Vectors can be numeric or string:

c(4,7:10,6) is the vector: (4,7,8,9,10,6)c("This","is","a","string","vector") is the vector: ("This","is","a","string","vector")

NOTE: for columns, you can also use a string vector of column namese.g., verbs[1:5,c("Verb","LengthOfTheme")]

c. Use logical subscripting. This is very powerful, and will be described in the next section


Step 4 - R basicsLogical subscripting

This allows you to select only those rows of a data frame that meet certain conditions.

For example, you can select only the rows for which Length of Theme is greater than 3.4

verbs[verbs$LengthOfTheme>3.4,]

Or, you can select only the rows that refer to verbs with animate themes

verbs[verbs$AnimacyOfTheme == "animate",]


Step 4 - R basicsLogical subscripting

Some logical operators:

- identity, equal to: == (DO NOT USE: =)- not equal to: !=- AND: &- OR: | (i.e., the vertical bar)


Getting started with R - coli.uni-saarland.degambi/lectures/GettingStartedwithR.pdf · Getting...

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