# Variables, data structures and basic Operations
In R, data objects are manipulated using named data structures. The names of the objects might be called "variables" although that term does not have a specific meaning in the official R documentation. R names are case sensitive and may contain alphanumeric characters(
0-9), the dot/period(
.) and underscore(
_). To create names for the data structures, we have to follow the following rules:
list( '.11' ="a") #$`.11` # "a"
There is no restriction on the number of characters in a variable name.
Some examples of valid object names are:
In R, variables are assigned values using the infix-assignment operator
<-. The operator
= can also be used for assigning values to variables, however its proper use is for associating values with parameter names in function calls. Note that omitting spaces around operators may create confusion for users. The expression
a<-1 is parsed as assignment (
a <- 1) rather than as a logical comparison (
a < -1).
> foo <- 42 > fooEquals = 43
foo is assigned the value of
foo within the console will output
42, while typing
fooEquals will output
> foo  42 > fooEquals  43
The following command assigns a value to the variable named
x and prints the value simultaneously:
> (x <- 5)  5 # actually two function calls: first one to `<-`; second one to the `()`-function > is.function(`(`)  TRUE # Often used in R help page examples for its side-effect of printing.
It is also possible to make assignments to variables using
> 5 -> x > x  5 >
# Types of data structures
There are no scalar data types in R. Vectors of length-one act like scalars.
# Common operations and some cautionary advice
Default operations are done element by element. See
?Syntax for the rules of operator precedence. Most operators (and may other functions in base R) have recycling rules that allow arguments of unequal length.
Given these objects:
# Example objects
> a <- 1 > b <- 2 > c <- c(2,3,4) > d <- c(10,10,10) > e <- c(1,2,3,4) > f <- 1:6 > W <- cbind(1:4,5:8,9:12) > Z <- rbind(rep(0,3),1:3,rep(10,3),c(4,7,1))
# Some vector operations
> a+b # scalar + scalar  3 > c+d # vector + vector  12 13 14 > a*b # scalar * scalar  2 > c*d # vector * vector (componentwise!)  20 30 40 > c+a # vector + scalar  3 4 5 > c^2 #  4 9 16 > exp(c)  7.389056 20.085537 54.598150
# Some vector operation Warnings!
> c+e # warning but.. no errors, since recycling is assumed to be desired.  3 5 7 6 Warning message: In c + e : longer object length is not a multiple of shorter object length
R sums what it can and then reuses the shorter vector to fill in the blanks... The warning was given only because the two vectors have lengths that are not exactly multiples. c+f # no warning whatsoever.
# Some Matrix operations Warning!
> Z+W # matrix + matrix #(componentwise) > Z*W # matrix* matrix#(Standard product is always componentwise)
To use a matrix multiply: V %*% W
> W + a # matrix+ scalar is still componentwise [,1] [,2] [,3] [1,] 2 6 10 [2,] 3 7 11 [3,] 4 8 12 [4,] 5 9 13 > W + c # matrix + vector... : no warnings and R does the operation in a column-wise manner [,1] [,2] [,3] [1,] 3 8 13 [2,] 5 10 12 [3,] 7 9 14 [4,] 6 11 16
# "Private" variables
A leading dot in a name of a variable or function in R is commonly used to denote that the variable or function is meant to be hidden.
So, declaring the following variables
> foo <- 'foo' > .foo <- 'bar'
And then using the
ls function to list objects will only show the first object.
> ls()  "foo"
all.names = TRUE to the function will show the 'private' variable
> ls(all.names = TRUE)  ".foo" "foo"