add_two <- function(x){
x + 2
}Writing Vector Functions
New Seating Chart
Tuesday, November 2
Today we will…
- Reminder: Midterm Portfolio Meetings
- New Material
- Function Basics
- Variable Scope + Environment
- PA 7: Writing Functions
Midterm Portfolio Meetings
Midterm Portfolio Meetings
- No in-person class on Thursday
- Remember the time you signed up for: Google Sheet with Sign-up Times
- Deadline to sign-up (or move your time) is Tuesday at 5pm.
- Remember the time you signed up for: Google Sheet with Sign-up Times
- Meetings scheduled between 8am and 11am will be in Dr. T’s office (25-105).
- Meetings scheduled between 12pm and 3pm will be in our classroom (this room).
Functions
Why write functions?
Functions allow you to automate common tasks!
- We’ve been using functions since Day 1, but when we write our own, we can customize them!
- Have you found yourself copy-pasting code and only changing small parts?
Why write functions?
Writing functions has three big advantages over copy-paste:
- Your code is easier to read.
- To change your analysis, simply change one function.
- You avoid mistakes.
Function Basics
Function Syntax
Function Syntax
A (very) Simple Function
Let’s define a function.
- You run the code to define the function just once.
Naming: add_two
The name of the function is chosen by the author.
Arguments
The argument(s) of the function are chosen by the author.
- Arguments are how we pass external values into the function.
- They are temporary variables that only exist inside the function body.
Arguments
If we supply a default value when defining the function, the argument is optional when calling the function.
Body: { }
The body of the function is where the action happens.
- The body must be specified within a set of curly brackets.
- The code in the body will be executed (in order) whenever the function is called.
Output: return()
Your function will give back what would normally print out…
Function Style – Using return()s
I tend to disagree…
I prefer to use return() statements because it saves me from accidentally writing a function that outputs nothing.
Output: return()
If you need to return more than one object from a function, wrap those objects in a list.
Input Validation
When a function requires an input of a specific data type, check that the supplied argument is valid.
add_something <- function(x, something){
if(!is.numeric(x)){
stop("Please provide a numeric input for the x argument.")
}
return(x + something)
}
add_something(x = "statistics", something = 5)Error in add_something(x = "statistics", something = 5): Please provide a numeric input for the x argument.How would you modify the previous code to validate both x and something?
Meaning, the function should check if both x and something are numeric.
Multiple Validations
add_something <- function(x, something){
if(!is.numeric(x) | !is.numeric(something)){
stop("Please provide numeric inputs for both arguments.")
}
return(x + something)
}
add_something(x = 2, something = "R")Error in add_something(x = 2, something = "R"): Please provide numeric inputs for both arguments.Variable Scope + Environment
Variable Scope
The location (environment) in which we can find and access a variable is called its scope.
- We need to think about the scope of variables when we write functions.
- What variables can we access inside a function?
- What variables can we access outside a function?
Global Environment
- The top right pane of Rstudio shows you the global environment.
- This is the current state of all objects you have created.
- These objects can be accessed anywhere.
Function Environment
- The code inside a function executes in the function environment.
- Function arguments and any variables created inside the function only exist inside the function.
- They disappear when the function code is complete.
- Function arguments and any variables created inside the function only exist inside the function.
- What happens in the function environment does not affect things in the global environment.
Function Environment
We cannot access variables created inside a function outside of the function.
Name Masking
Name masking occurs when an object in the function environment has the same name as an object in the global environment.
Dynamic Lookup
Functions look for objects FIRST in the function environment and SECOND in the global environment.
It is not good practice to rely on global environment objects inside a function!
Debugging
Debugging
You will make mistakes (create bugs) when coding.
- Unfortunately, it becomes more and more complicated to debug your code as your code gets more sophisticated.
- This is especially true with functions!
Debugging Strategies
When you have a concept that you want to turn into a function…
Write a simple example of the code without the function framework.
Generalize the example by assigning variables.
Write the code into a function.
Call the function on the desired arguments
This structure allows you to address issues as you go.
An Example
Write a function called find_car_make() that takes in the name of a car and returns the “make” of the car (the company that created it).
find_car_make("Toyota Camry")should return “Toyota”.find_car_make("Ford Anglica")should return “Ford”.
An Example
Taking these examples, write a find_car_make() function that will output the maker / manufacturer of any car.
Once you’ve got a function written, can you add input validation to your function?
find_car_make()
find_car_make <- function(car_name){
# Check if there is a space in the string (so there are separate parts)
stopifnot(
stringr::str_detect(car_name, pattern = "\\w")
)
# Grab the first word of the car name (assuming Toyota Camry style input)
make <- word(string = car_name,
start = 1,
end = 1)
return(make)
}PA 7: Writing Functions
PA 7
You will write several small functions, then use them to unscramble a message. Many of the functions have been started for you, but none of them are complete as is.
This activity will require knowledge of:
- Summary functions
- Function documentation (for optional arguments)
- Function syntax
- modulus division (and remainders)
if ()&else if()statements- Using
[]and logical values to extract elements of a vector - Negating logical statements
None of us have all these abilities. Each of us has some of these abilities.
Base R Resources
Every group should have a base R cheatsheet!
On the front middle:
- Selecting Vectors can refresh your memory on using
[]to extract elements of a vector
On the front right:
- If Statements can help you write conditional checks / returns for your functions
- Functions can help you remember the syntax for creating a function
Getting Started
The partner who lives the furthest from SLO starts as the Developer (typing and listening to instructions from the Coder)!
- The Coder does not type.
- The collaborative editing feature should allow you to track what is being typed.
- The Developer only types what they are told to type.
Submission
Submit the name of the television show the six numbers are asssociated with.
- Each person will input the full name of the TV show into the PA 7 quiz.
- The person who last occupied the role of Developer will download and submit the
PA-7-functions.htmlfile for the group.- Only one submission per group!
Lab 7 & Challenge 7: Functions + Fish
To do…
- PA 7: Functions
- Due Thursday, 11/4 by 12:10pm
- Attend Your Midterm Portfolio Meeting
- Lab 7: Functions + Fish
- Due Sunday, 11/10 at 11:59pm.
Writing Vector Functions