5 file types use the .r file extension.
- 1.R Script File
- 2.Rez Source Code File
- 3.REBOL Script
- 4.Ratfor Source Code File
- 5.Right Audio Channel File
File Type 1R Script File
| Developer | The R Project for Statistical Computing |
| Popularity | |
| Category | Developer Files |
| Format | Text |
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What is an R file?
An R file is a script written in R, a programming language used for statistical analysis and graphing purposes. It contains code that can be executed within the R software environment. R files may include commands that create objects (functions, values, etc.) and produce visualizations of the computed data.
You will most likely only encounter R scripts if you work in a field that focuses on statistical analysis and uses the R programming language to develop data analysis programs. The R and RStudio programs are typically used to open R files since they provide helpful IDE tools.
You can also use a plain text editor to view the contents of an R script. This is especially helpful for users unsure of what the R file contains. If this pertains to you, open the file with Microsoft Notepad in Windows or Apple TextEdit in macOS to examine what is stored in the file. Both of these text editors come bundled with their respective operating systems.
Programs that open R files
File Type 2Rez Source Code File
| Developer | Apple |
| Popularity | |
| Category | Developer Files |
| Format | Text |
.R File Association 2
Text file used by Rez, a resource compiler for Mac OS X applications; contains declarations for application resources, which can be string lists, icons, alerts, or one of many other resource types; used for building the resources into the resource fork of an application file.
R files must must contain both the type declarations and the resource definitions required to compile the resources. Compiled resources can be decompiled back into R files using DeRez.
NOTE: The Rez compiler is included with Apple Xcode development software.
Programs that open R files
File Type 3REBOL Script
| Developer | REBOL Technologies |
| Popularity | |
| Category | Developer Files |
| Format | Text |
.R File Association 3
Script written in the REBOL programming language; contains code that can be compiled into an executable program; may be a program file or a header file referenced by other REBOL program files.
REBOL stands for 'Relative Expression Based Object Language.' The language is commonly used for creating Internet scripts and applications.
Programs that open R files
File Type 4Ratfor Source Code File
| Developer | Brian Kerhighan |
| Popularity | |
| Category | Developer Files |
| Format | Text |
.R File Association 4
File used by Ratfor, a preprocessor for the FORTAN programming language; contains regular FORTRAN source code as well as Ratfor statements that can be translated into FORTAN source code before they are compiled by a FORTRAN compiler.
Ratfor source code allows developers to use a wider syntax than the syntax supported by the FORTRAN compiler. For example, Ratfor allows the specification of C-like control flow constructs such as if-else, switch, while, and for.
NOTE: Ratfor is distributed in a source code format.
Programs that open R files
File Type 5Right Audio Channel File
| Developer | N/A |
| Popularity | |
| Category | Audio Files |
| Format | N/A |
.R File Association 5
Audio file containing the right channel of an audio track; often exported by audio production programs, such as Digital Performer (Mac) and Cubase (Mac and Windows).
Programs that open R files
Obtaining R
R is available for Linux, MacOS, and Windows. Software can be downloaded from The Comprehensive R Archive Network (CRAN).
Startup
After R is downloaded and installed, simply find and launch R from your Applications folder.
Entering Commands
R is a command line driven program. The user enters commands at the prompt (> by default) and each command is executed one at a time.
The Workspace
The workspace is your current R working environment and includes any user-defined objects (vectors, matrices, data frames, lists, functions). At the end of an R session, the user can save an image of the current workspace that is automatically reloaded the next time R is started.
Graphic User Interfaces
Aside from the built in R console, RStudio is the most popular R code editor, and it interfaces with R for Windows, MacOS, and Linux platforms.
Operators in R
R's binary and logical operators will look very familiar to programmers. Note that binary operators work on vectors and matrices as well as scalars.
Arithmetic Operators include:
| Operator | Description |
| + | addition |
| - | subtraction |
| * | multiplication |
| / | division |
| ^ or ** | exponentiation |
Logical Operators include:
| Operator | Description |
| > | greater than |
| >= | greater than or equal to |
| exactly equal to | |
| != | not equal to |
Data Types
R has a wide variety of data types including scalars, vectors (numerical, character, logical), matrices, data frames, and lists.
Creating New Variables
Use the assignment operator <- to create new variables.
# An example of computing the mean with variables
mydata$sum <- mydata$x1 + mydata$x2
mydata$mean <- (mydata$x1 + mydata$x2)/2
Functions
Almost everything in R is done through functions. A function is a piece of code written to carry out a specified task; it may accept arguments or parameters (or not) and it may return one or more values (or not!). In R, a function is defined with the construct:
function ( arglist ) {body}
The code in between the curly braces is the body of the function. Note that by using built-in functions, the only thing you need to worry about is how to effectively communicate the correct input arguments (arglist) and manage the return value/s (if any).
Importing Data
Importing data into R is fairly simple. R offers options to import many file types, from CSVs to databases.
For example, this is how to import a CSV into R.
# first row contains variable names, comma is separator
# assign the variable id to row names
# note the / instead of on mswindows systems
mydata <- read.table('c:/mydata.csv', header=TRUE,
sep=',', row.names='id')
Descriptive Statistics
R provides a wide range of functions for obtaining summary statistics. One way to get descriptive statistics is to use the sapply( ) function with a specified summary statistic.
Below is how to get the mean with the sapply( ) function:
# get means for variables in data frame mydata
# excluding missing values
sapply(mydata, mean, na.rm=TRUE)
Possible functions used in sapply include mean, sd, var, min, max, median, range, and quantile.
Plotting in R
In R, graphs are typically created interactively. Here is an example:
# Creating a Graph
attach(mtcars)
plot(wt, mpg)
abline(lm(mpg~wt))
title('Regression of MPG on Weight')
R Program Machine Learning
The plot( ) function opens a graph window and plots weight vs. miles per gallon. The next line of code adds a regression line to this graph. The final line adds a title.
Packages
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Packages are collections of R functions, data, and compiled code in a well-defined format. The directory where packages are stored is called the library. R comes with a standard set of packages. Others are available for download and installation. Once installed, they have to be loaded into the session to be used.
.libPaths() # get library location
library() # see all packages installed
search() # see packages currently loaded
Getting Help
Once R is installed, there is a comprehensive built-in help system. At the program's command prompt you can use any of the following:
help.start() # general help
help(foo) # help about function foo
?foo # same thing
apropos('foo') # list all functions containing string foo
example(foo) # show an example of function foo
Going Further
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If you prefer an online interactive environment to learn R, this free R tutorial by DataCamp is a great way to get started.