## R conditional statements

• function to check if the number is even or odd
check.even <- function(n){
if (n >=0 ){
is_even <- (n %% 2 == 0)
return(is_even)

}else {
print("invalid")
return(NULL)
}

}

check.even(-1)
check.even(2)
check.even(3)
• The last statement will be returned automatically by R functions
check.even <- function(n){
if (n >=0 ){
is_even <- (n %% 2 == 0)

}else {
print("invalid")
is_even <- NULL
}
is_even
}

check.even(4)

• Using switch
• Refer Here for the R sample code written

## Examples

• Write a function in R to
• Check the number is prime or not
is.prime <- function(number) {
if (number >= 2){
# finding the numbers to check
all_numbers <- 2:(number-1)
mod_results <- number%%all_numbers
if (any(mod_results == 0)){
return(FALSE)
}
else {
return(TRUE)
}
}
}

is.prime(7)
is.prime(9)
• print all the numbers in given range
is.prime <- function(number) {
if (number >= 2){
# finding the numbers to check
all_numbers <- 2:(number-1)
mod_results <- number%%all_numbers
if (any(mod_results == 0)){
return(FALSE)
}
else {
return(TRUE)
}
}
}

prime_numbers <- function(numbers) {
results <- c()
for (number in numbers){
if(is.prime(number) == TRUE) {
results <- append(results, number)
}
}
return(results)
}

prime_numbers(100:1000)

• Refer Here to view the code
• Write a function to find the N highest values from vector
# find the nth highest value
nth.highest <- function(numbers, n) {
return (sort(numbers, decreasing = TRUE)[n])
}

values <- c(100,45,23,34,46,57,102)
nth.highest(values, 3)
nth.highest(values,2)
• Write a function to remove NA elements from vector
# removing NA items from vector
remove.na <- function(values) {
return(values[!is.na(values)])
}

prices <- c(30.5, 31.5, NA, 30.5, 30.74, NA, 31)

prices <- remove.na(prices)
prices
• We can use na.omit function as well
• Write R code to filter the vector by some values
items <- c("apples", "oranges", "mangoes", "banana", "apples", "oranges", "mangoes", "banana", "apples", "oranges", "mangoes", "banana")

filter_by <- c("apples", "mangoes")

items[ items %in% filter_by]
• Write a R function to simulate a coin flip n times
coin.filp <- function(size=1) {
return(sample(c("H", "T"), replace = TRUE, prob = c(0.5, 0.5), size = size))
}

coin.filp(100)
coin.filp()

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