styler packagescale()At its core, R (like all programming languages) is basically a fancy calculator. The syntax of most basic arithmetic operations in R should be familiar to you:
1 + 2 # addition
[1] 3
3 - 2 # subtraction
[1] 1
4 * 2 # multiplication
[1] 8
4 / 2 # division
[1] 2
1.234 + 2.345 - 3.5*4.9 # numbers can have decimals
[1] -13.571
1.234 + (2.345 - 3.5)*4.9 # expressions can contain parentheses
[1] -4.4255
2**2 # exponentiation
[1] 4
4**(1/2) # square root
[1] 2
9**(1/3) # cube root
[1] 3The [1] lines above are the output given by R when the preceding expression
is executed. Any portion of a line starting with a # is a comment and ignored
by R.
R also supports storing values into symbolic placeholders called variables, or
objects. An expression like those above can be assigned into a variable with a
name using the <- operator:
new_var <- 1 + 2Variables that have been assigned a value can be placed in subsequent expressions anywhere where their value is evaluated:
new_var - 2
[1] 1
another_var <- new_var * 4The correct way to assign a value to a variable in R is with the <- syntax,
unlike many other programming languages which use =. However, although the =
assignment syntax does work in R:
new_var = 2 # works, but is not common convention!this is considered bad practice and may cause confusion later. You should always
use the <- syntax when assigning values to variables!
In R, the period . does not have a special meaning like it does in many other
languages like python, C, javascript, etc. Therefore, new.var is a valid
variable name just like new_var, even though it may look strange to those
familiar with these other languages. While including . in your R variable
names is valid, the results that you will use in programs written in other
languages that do have a meaning for this character. Therefore, it is good
practice to avoid using . characters in your variable names to reduce the
chances of conflicts later.