Functions in R

👉🏻 Perform a specific task according to a set of instructions. 👉🏻 Some functions we have discussed so far,

c, matrix, array, list, data.frame, str, dim, length, nrow, plot

Functions in R (cont.)

👉🏻 There are basically two types of functions:

💻 Built-in functions

  Already created or defined in the programming framework to make our work easier.

👨 User-defined functions

  Sometimes we need to create our own functions for a specific purpose.

name <- function(arg1, aug2, ...){
<FUNCTION BODY>
return(value)
}

cal_power <- function(x){
a <- x^2; b <- x^3
out <- c(a, b)
names(out) <- c("squared", "cubed")
out # or return(out)
}

cal_power(2)

squared   cubed 
      4       8

👉 Functions are created using the function()

name <- function(arg1, aug2, ...){
<FUNCTION BODY>
return(value)
}

cal_power <- function(x){
a <- x^2
b <- x^3
out <- c(a, b)
names(out) <- c("squared", "cubed")
out # or return(out)
}

Function name: cal_power

Function name: cal_power

• use verbs, where possible

• should be meaningful

• use an underscore (_) to separate words

• avoid names of built-in functions

• start with lower case letters. Note that R is a case sensitive language

name <- function(arg1, aug2, ...){
<FUNCTION BODY>
return(value)
}

cal_power <- function(x){
 a <- x^2
 b <- x^3
 out <- c(a, b)
 names(out) <- c("squared", "cubed")
 out # or return(out)
}

Function arguments: x

• value passed to the function to obtain the function's result.

name <- function(arg1, aug2, ...){
<FUNCTION BODY>
return(value)
}

cal_power <- function(x){
  a <- x^2
  b <- x^3
  out <- c(a, b)
  names(out) <- c("squared", "cubed")
  out # or return(out)
}

Function body

Function with single line

cal_sqrt <- function(x){
x^2
}

cal_sqrt <- function(x) x^2

Function body (Cont.)

• {} do not go in one single line, always two lines

# Good ---
if(y == 2){
print("even")
}
# Bad ---
if(y == 2){ print("even")}

Load the mozzie dataset

library(mozzie)
data(mozzie); head(mozzie, 2)

  ID Year Week Colombo Gampaha Kalutara Kandy Matale Nuwara Eliya Galle
1  1 2008   52      15       7        1    11      4            0     0
2  2 2009    1      44      23        5    16     21            2     0
  Hambantota Matara Jaffna Kilinochchi Mannar Vavuniya Mulative Batticalo
1          6     22      0           0      8        0        0         1
2          5     18      1           0      0        0        0         0
  Ampara Trincomalee Kurunagala Puttalam Anuradhapura Polonnaruwa Badulla
1      0           0          2        1            2           0       1
2      1           1         10        5            0           0       1
  Monaragala Ratnapura Kegalle
1          1         2      16
2          0         1      25

Use Min-Max transformation to rescale all the districts variables onto 0-1 range.

Min-Max transformation is $\frac{x_i-min\left(x\right)}{max\left(x\right)-min\left(x\right)}$ where $x=(x_1,x_2,...x_n)$.

Min-Max transformation on mozzie

minmax.colombo <- (mozzie$Colombo - min(mozzie$Colombo, na.rm = TRUE)) /
  (max(mozzie$Colombo, na.rm=TRUE) - min(mozzie$Colombo, na.rm=TRUE))
head(minmax.colombo) # Colombo district

[1] 0.03157895 0.09263158 0.08210526 0.12000000 0.11157895 0.06105263

minmax.gampaha <- (mozzie$Gampaha - min(mozzie$Gampaha, na.rm = TRUE)) /
  (max(mozzie$Gampaha, na.rm = TRUE) - min(mozzie$Gampaha, na.rm = TRUE)) 
head(minmax.gampaha) # Gampaha district

[1] 0.02734375 0.08984375 0.07421875 0.08984375 0.09375000 0.06640625

minmax.kalutara <- (mozzie$Gampaha - min(mozzie$Kalutara, na.rm = TRUE)) /
  (max(mozzie$Kalutara, na.rm = TRUE) - min(mozzie$Kalutara, na.rm = TRUE))
head(minmax.kalutara) # Kalutara district

[1] 0.09333333 0.30666667 0.25333333 0.30666667 0.32000000 0.22666667

Copying-and-pasting

You could easily make errors.

A mistake copied becomes a mistake repeated.

When should you write a function?

• Whenever you need to copy and paste a block of codes many times

  • A function is a reusable block of programming code designed to do a specific task.

• If you don't find a suitable built-in function to serve your purpose, you can write your own function

• To share your work with others

Writing a function

Step 1: Function name

rescale_minmax

Step 2: Assign your function to the name

rescale_minmax <-

Step 3: Tell R that you are writing a function

rescale_minmax <- function(x) # Arguments/inputs should be defined inside ()

Step 4: Curly braces define the start and the end of your work

rescale_minmax <- function(x){
# Task
# output
}

Step 5: Function inputs, task and outputs

Find all the inputs that correspond to a given function output?

(x - min(x, na.rm = TRUE)) / (max(x, na.rm=TRUE) - min(x, na.rm=TRUE))

Step 6: Complete your function

rescale_minmax <- function(x){
  (x - min(x, na.rm = TRUE)) / (max(x, na.rm=TRUE) - min(x, na.rm=TRUE))
}

Step 7: Check your function with a few different inputs

rescale_minmax <- function(x){
  (x - min(x, na.rm = TRUE)) / (max(x, na.rm=TRUE) - min(x, na.rm=TRUE))
}

rescale_minmax(c(1, 200, 250, 80, NA))

[1] 0.0000000 0.7991968 1.0000000 0.3172691        NA

Functions are for humans and computers

• Descriptive names for variables.

• Comment your code.

Write a function to compute z-score value of a A/L Mathematics student given the marks of the student. Assume

mean(Mathematics) = 60, sd(Mathematics) = 10,

mean(Chemistry) = 45, sd(Chemistry) = 20,

mean(Physics) = 55, sd(Physics) = 5.