Preliminaries

Contact Information:

Grading

• There will be two graded assignments.

• You will have to work on a final group project which focuses on one or more of the topics discussed in the course.

• The final grade is a weighted average of the grades for the group project (60%), its presentation (20%) and the assignments (20%).

Outline

RStudio

• RStudio is an integrated development environment (IDE) for R.
• It provides some convenient functionality compared to the IDE that comes with R.

RStudio Projects

• To work in a specific directory the base R way would be to use setwd(). This is problematic if you want to share your code or work from different machines on the same project.
• Use projects instead.

Workflow

• Instead of opening a new R session and use setwd() you open the project. The working path is automatically set to the folder where the .Rproj file lives in.

Some Shortcuts

RStudio supports:

• package development
• version control via git and svm
• creation and compilation of dynamic documents
• connections to external data bases
• ...

We will use some of this later on.

R Basics: Control Flows

The basic control flows are conditionals (choices) and loops.

Scoping Rules

R’s lexical scoping follows four primary rules:

• Name masking
• Functions versus variables
• A fresh start
• Dynamic lookup

Scoping Rules: Name Masking

x <- 3
square_1 <- function() x^2
square_1()

x <- 3
square_2 <- function(){ 
  x   <- 2
  foo <- function() x^2
  foo()
}
square_2()

Scoping Rules: Functions versus Variables

x <- 3
square_2 <- function(){ 
  x   <- 2
  foo <- function() x^2
  foo()
}
square_3 <- function(x){
  square_2 <- 5
  square_2()
}
square_3()

• When a function and a non-function share the same name, R ignores non-function objects in a function call.

Scoping Rules: A Fresh Start

x <- 2
square_4 <- function(){
  (x <- x^2)
}
square_4()
square_4()

• Every time a function is called a new environment is created to host its execution.
• A function has no way to tell what happened the last time it was run; each invocation is completely independent.

Scoping Rules: Dynamic Lookup

x  <- 1
f1 <- function() x
f1()
x <- 2 
f1()

• R looks for values when the function is run, not when the function is created.

Lazy Evaluation

lazy_function <- function(x){
  10
}
lazy_function()

lazy_function <- function(x){
  x
}
lazy_function()

Style Guide

Object names

day_one
day_1

# Bad
first_day_of_the_month
dayone
djm1
T <- FALSE
c <- 10
mean <- function(x) sum(x)

Spacing

average <- mean(feet / 12 + inches, na.rm = TRUE)

average<-mean(feet/12+inches,na.rm=TRUE)

x <- 1:10
base::get

x <- 1 : 10
base :: get

Spacing

list(
  total = a + b + c, 
  mean  = (a + b + c) / n
)

if (debug) do(x)
diamonds[5, ]

if ( debug ) do(x)  # No spaces around debug
x[1,]   # Needs a space after the comma
x[1 ,]  # Space goes after comma not before

Spacing

• An opening curly brace should never go on its own line and should always be followed by a new line. A closing curly brace should always go on its own line, unless it’s followed by else. Always indent the code inside curly braces.

if (y < 0 && debug) {
  message("Y is negative")
}
if (y == 0) {
  log(x)
} else {
  y ^ x
}

if (y < 0 && debug) {
message("Y is negative") }
if (y == 0) {
  log(x)
} else {
  y ^ x
}

Spacing

if (y < 0 && debug) message("Y is negative")

Assignment

x <- 5

x = 5

Commenting guidelines

• Comment your code.
• Each line of a comment should begin with the comment symbol and a single space: #.
• Comments should explain the why, not the what.
• Use commented lines of - and = to break up your file into easily readable chunks.

# Load data ---------------------------
# Plot data ---------------------------