Lecture 10 - Programming Basics

In this lecture note, we will delve into the core of R programming by exploring its building blocks. Think of R as a language: to communicate effectively, you need to know the grammar (syntax), vocabulary (functions), and the rules of conversation (flow control and loops). Let us unpack these one by one.

R Syntax

function Statement

my_function <- function(parameters) {
  # Code to execute
  return(result)
}

Example:

add_numbers <- function(a, b) {
  sum <- a + b
  return(sum)
}

if-else Statement:

if (condition1) {
  # Code to execute if condition1 is TRUE
} else if (condition2) {
  # Code to execute if condition2 is TRUE
} else {
  # Code to execute if condition1 and condition2 are FALSE
}

Example:

number <- 10
if (number > 5) {
  print("Number is greater than 5")
} else {
  print("Number is 5 or less")
}

for Loop:

for (i in 1:n) {
  # Code to execute for each iteration
}

Example:
```
for (i in 1:5) {
  print(i)
}
```

while Loop:

while (condition) {
  # Code to execute as long as the condition is TRUE
}

Example:

count <- 1
while (count <= 5) {
  print(count)
  count <- count + 1
}

Core Apply Functions

Function	Input	Output	Description
`apply(x, margin, FUN)`	Mutlidimension (`dim`)	Customizable	Applies a function over rows or columns of a matrix or dimensions of an array.
`lapply(x, FUN)`	List-type (`as.list`)	List	Applies a function to each element of a list or vector and returns a list.
`sapply(x, FUN)`	List-type (`as.list`)	Simplified	Like `lapply`, but tries to simplify output.
`vapply(x, FUN, FUN.VALUE)`	List-type (`as.list`)	User-defined	Like `sapply`, but enforces a specific return type.