R essentials Cheat Sheet

R help functions

help.start()	General help
help(plot) or ?plot	Help on function `plot`
help.search("geo")	Search help system for instances of string geo
example(plot)	Examples of function `plot`
RSiteSearch("geo")	Search for string geo in online help manuals and archived mailing lists
apropos("geo", mode="function")	List all available functions with geo in their name
data()	List all example datasets in loaded packages
vignette()	List all vignettes for installed packages
vignette("geo")	Display specific vignettes for topic geo

Managing R workspace

getwd()	Get working directory
setwd("mydirectory")	Set working directory to mydirectory
ls()	List the objects in workspace
rm(objectlist)	Remove one or more objects
help(options)	Learn about available options
options()	View or set current options
history(#)	Display the last # of commands (default=25)
savehistory("myfile")	Save the commands history to myfile (default = .Rhistory)
loadhistory("myfile")	Reload a commands history (default = .Rhistory)
save.image("myfile")	Save the workspace to myfile (default = .RData)
save(objectlist, file = "myfile")	Save specific objects to a file
load("myfile")	Load a workspace in the current session (default = .RData)
q()	Quit R. Will be prompted to save the workspace.

setwd("C:/myprojects/project1")

options()

options(digits=3)

x <- runif(20)

summary(x)

hist(x)

savehistory()

save.image()

q()

Saving graphic output

pdf("filename.pdf")	PDF file
win.metafile("filename.wmf")	Windows metafile
png("filename.png")	PBG file
jpeg("filename.jpg")	JPEG file
bmp("filename.bmp")	BMP file
postscript("filename.ps")	PostScript file

jpeg("rplot.jpeg")

plot(x,y)

dev.off()

Packages

.libPaths()	Shows where library is located
library()	Shows the packages saved in the library
search()	Shows which packages have been loaded and ready to use
install.packages("ggplot")	Install a package for the first time
update.packages("ggplot")	Update packages that have been installed
installed.packages()	Lists packages with version numbers, dependencies, and other info
library(ggplot)	Load package
help(package="ggplot")	Brief description of package and index of functions and datasets

help.start()

install.packages("vcd")

help(package="vcd")

library(vcd)

help(Arthritis)

Arthritis

example(Arthritis)

q()

Data input

Keyboard input	`mydata <- data.frame(age=numeric(0),gender=character(0),weight=numeric(0))`
	`mydata <- edit(mydata)` or `fix(mydata)`
Delimited text file	`mydataframe <- read.table("file", header=logical_value, sep="delimiter",row.names="name",stringsAsFactors=logical_value)`
Excel file	`library(RODBC)`
	`channel <- odbcConnectExcel("myfile.xls")`
	`mydataframe <- sqlFetch(channel, "mysheet")`
	`odbcClose(channel)` or
	`library(xlsx)`
	`workbook <- "c:/myworkbook.xlsx"`
	`mydataframe <- read.xlsx(workbook,1)`
Others	XML, Webscrapping, SPSS, SAS, Stata, netCDF, HDF5, DBMSs

Accessing DBMSs - RODBC package

`odbcConnect(dsn, uid=" ", pwd=" ")`	Open a connection to an ODBC database
`sqlFetch(channel, sqltable)`	Read a table from an ODBC database into a dataframe
`sqlQuery(channel, query)`	Submit a query to an ODBC database and return the results
`sqlSave(channel, mydf, tablename=sqtable, append=FALSE)`	Write or update (append=TRUE) a data frame to a table in the ODBC database
`sqlDrop(channel, sqtable)`	Remove a table from the ODBC database
`close(channel)`	Close the connection

library(RODBC)

myconn <- odbcConnect("mydsn", uid="Rob", pwd="aardvark")

crimedat <- sqlFetch(myconn, Crime)

pundat <- sqlQuery(myconn, "select * from Punishment")

close(myconn)

Data structures

Vectors

Hold numeric, character, or logical data e.g.

c(1,2,3,4,5)

c("one","two","three")

c(TRUE,TRUE,FALSE,FALSE)

Matrices

2D array where each element has the same mode

mymatrix <- matrix(vector, nrow=number_of_rows, ncol=number_of_columns, byrow=logical_value, dimnames=list(char_vector_rownames, char_vector_colnames))

Arrays

Similar to matrices but can have more than 2 dimensions

myarray <- array(vector, dimensions, dimnames)

Data frames

Different columns can contain different modes of data

mydata <- data.frame(col1, col2, col3, ...)

Factors

Nominal, ordinal or continuous

status <- c("Poor", "Improved", "Excellent", "Poor")

status <- factor(status, order=TRUE, levels=c("Poor","Improved","Excellent"))

Lists

Ordered collection of objects

mylist <- list(name1=object1, name2=object2, ...)

Example code

cells <- c(1,26,24,68)
rnames <- c("R1","R2")
cnames <- c("C1","C2")
mymatrix <- matrix(cells, nrow=2, ncol=2, byrow=TRUE, dimnames=list(rnames,cnames))

dim1 <- c("A1","A2")
dim2 <- c("B1","B2","B3")
dim3 <- c("C1","C2","C3","C4")
z <- array(1:24, c(2,3,4), dimnames=list(dim1, dim2, dim3))

patientID <- c(1,2,3,4)
age <- c(25,34,28,52)
diabetes <- c("Type1","Type2","Type1","Type1")
status <- c("Poor","Improved","Excellent","Poor")
patientdata <- data.frame(patientID, age, diabetes, status)
patientdata[1:2]
patientdata[c("diabetes","status")]
patientdata$age
# cross tabulate diabetes by status
table(patientdata$diabetes, patientdata$status) 

g <- "My First List"
h <- c(25,26,18,39)
j <- matrix(1:10, nrow=5)
k <- c("one","two","three")
mylist <- list(title=g, ages=h, j, k)
mylist[[2]]
mylist[["ages"]]

Useful tips

Attach, Detach and With

attach (mtcars)

summary(mpg)

plot(mpg,wt)

detach(mtcars)

with(mtcars, {

summary(mpg,disp,wt)

plot(mpg,disp)

plot(mpg,wt)

})

with(mtcars, {

nokeepstats <- summary(mpg)

keepstats <<- summary(mpg)

})

nokeepstats # object not found

keepstats # object exists in global env with superassignment '<<-'

Useful functions

`length(object)`	Number of elements/components
`dim(object)`	Dimensions of an object
`str(object)`	Structure of an object
`class(object)`	Class or type of an object
`mode(object)`	How an object is stored
`names(object)`	Names of components in an object
`cbind(object, object, ...)`	Combines objects as columns
`rbind(object, object, ...)`	Combines objects as rows
`head(object)`	Lists the first part of the object
`tail(object)`	Lists the last part of the object
`rm(object, object, ...)`	Deletes one or more objects. `rm(list=ls())` will remove most objects.
`newobject <- edit(object)`	Edits object and saves as newobject
`fix(object)`	Edits in place
`set.seed()`	To have reproducible results

Arithmetic operators

`+`	Addition
`-`	Subtraction
`*`	Multiplication
`/`	Division
`^` or `**`	Exponentiation
`x%%y`	Modulus (x mod y)
`x%/%y`	Integer division

Logical operators

`<`	Less than
`<=`	Less than or equal to
`>`	Greater than
`>=`	Greater than or equal to
`==`	Exactly equal to
`!=`	Not equal to
`!x`	Not `x`
`x \| y`	`x` or `y`
`x & y`	`x` and `y`
`isTRUE(x)`	Test if `x` is `TRUE`

R essentials Cheat Sheet (DRAFT) by xeonkai