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Functions are a great way to leverage your creativity while coding. We're going to create a simple function to show how they work and then we're going to create a couple practical functions. One function will help us determine the square footage of a home and another to help us determine the monthly payment on a Tesla Model S and that $250,000 house we've being keeping an eye on.
To put it simply, functions are chunks of code that you can reuse over and over throughout your script. This can help save you time writing code and will keep your scripts shorter since you don't have to re-write multiple lines of code. It's all about convenience & efficiency!
PART 1: OUR FIRST FUNCTION
We are going to create a simple first function that multiplies two numbers together and then displays the results.
We use R's "function()" function to define our function and the variable that we assign the function to becomes the name of the function itself which we can then call anytime we want to in the R-Script.
A function needs us to define arguments or values that will be needed for calculations contained in it. In this example, we have two arguments, "first_number" and "second_number".
my_function <- function(first_number, second_number){
answer <- first_number * second_number
cat("My function calculates: ", first_number," X ",second_number, " = ", answer, ".\n", sep = "")
cat("Aren't functions great!?")
}
Our function use R's concatenate or "cat()" function to display a message to the user.
my_function(2,10)
Success! It worked!
PART 2: OUR SECOND FUNCTION
The next example will be a practical application using functions.
Let's create a function called "room_area" which needs the length and width of the room to calculate the area in square feet.
room_area <- function(length, width){
area <- length * width
}
Next let's say a house has 7 rooms, let's use that function to estimate the square footage of that house.
living_room <- room_area(length = 20, width = 20)
dining_room <- room_area(length = 20, width = 20)
kitchen <- room_area(length = 15, width = 25)
bath_1 <- room_area(length = 10, width = 10)
bath_2 <- room_area(length = 10, width = 20)
bed_1 <- room_area(length = 15, width = 20)
bed_2 <- room_area(length = 15, width = 15)
bed_3 <- room_area(length = 15, width = 15)
Now let's add up the square footage of all the rooms.
home_area <- living_room + dining_room + kitchen + bath_1 + bath_2 + bed_1 + bed_2 + bed_3
2,225 sq. ft.! That's a nice size home!
home_area
Are you starting to see the convenience of functions?!
PART 3: LET'S GET THE FUNCTION OUTTA HERE!
Here's a final practical application of using a function.
Let's create a function that will allow us to calculate the monthly payment on a fixed interest loan or mortgage.
We'll need to know the annual interest rate, the original loan amount, the down payment amount (if any), and finally the number of years to amortize the loan or mortgage.
monthly_payment <- function(annual_interest_rate, original_loan_amt, down_payment=0, number_of_years){
payment <- round(((annual_interest_rate/(12*100)) * (original_loan_amt-down_payment)) / (1-(1+(annual_interest_rate/(12*100)))^-(number_of_years*12)),2)
cat("Your monthly payment will be $", payment, " for ", number_of_years, " years", sep = "")
}
What would our monthly payment be for that new Tesla Model S at $99,500 if we amortize it over 5.5 years at a fixed-interest rate of 4.75%.
monthly_payment(4.75, 99500, 0, 5.5)
$1,716.03 per month for 5.5 years for a Tesla Model S?!
We may want to consider the Tesla Model 3 instead... ;P
Okay, now let's see what a $250,000 house will cost us each month if we amortize it over 30 years at a fixed-interest rate of 4.0%.
monthly_payment(4.00, 250000, 0, 30)
$1,193.54 per month for 30 years for that house we've been watching... better not quit our day job!
That's it for this lesson! Now get practicing!
CONGRATULATIONS! YOU'RE DONE WITH LESSON #6
DOWNLOAD CODE Here is the code from my GitHub gist "R Lesson 6 - Functions in R" in case you'd rather just copy and paste it and then play around with it.