R Function consist of 4 parts:
- Formals () – list of argument supplied to function
- Environment () –which stores the function name as an object
- Body () – contains list of statements that decides the task of this function name
- Return() – it returns the result of function call immediately from the function.
Example:
> func_name <- function(a)
+ a=10
> func_name <- function(a)a=10
> environment(func_name)
<environment: R_GlobalEnv>
> body(func_name)
a = 10
> formals(func_name)
$a
> check <- function(t) {
+ if (t == red) {
+ return(“STOP”)
+ }
+ else if (t ==green) {
+ return(“GO”)
+ }
+ else {
+ return(“WAIT”)
+ }
+ }
R Functions are of 2 types:
- User defined function
- Built-in function
User Defined Function:
One of the useful feature of R programming is its ability to allow programmer to create user defined functions.
Example
Here I am defining a function “fun” which will add 2 numbers
> fun <- function (a, b) {
+ a + b
+ }
> fun (5, 12)
[1] 17
Built-in Functions:
R programming comes up with a number of built in functions. Mostly they are of the following types:
- Numeric Functions
- Character Functions
- Statistical Functions
Numeric Functions:
- Floor(x) – floor (5.7) gives 5
- Ceiling(x) – ceiling (5.2) gives 6
- Trunc(x) – trunc(2.137) gives 2
- Abs(x) – abs(-3.4) gives 3.4
- Sqrt(x) – sqrt(25) gives 5
- Round(x, digit=n) – round(2.137, digit=2) gives 2.14
- Log(x) – log(5) gives natural logarithm of 5 which is 1.609438
- Log10(x) – log10(5) gives common logarithm of 5 which is 0.69897
- Sum(x) – sum (5 +6) gives 11
Character Functions
- Toupper(x) – toupper(“RamEswaRam”) gives “RAMESWARAM”
- Tolower(x) – tolower(“RamEswaRam”) gives “rameswaram”
- Grep() –used for keyword search.
- > str <-c(“are” ,”Delaware is a malware”,” But its not a hardware”)
- > total <- grep (“are”, str, value=F)
- > total
- [1] 1 2 3
- sub()—used for keyword substitution
- > total <- sub (“are”,”aks”, str)
- > total
- [1] “aks” “Delawaks is a malware”
- [3] ” But its not a hardwaks”
Statistical Functions:
- mean ()
- median ()
- mode ()
- min ()
- max ()
- range()
- sd()
Read more about Statistical use of R programming in the “Use of R Programming in Statistics” segment Click Here