if-else Statements & Basic Plotting

if Statement

• An if statement tells R to do a certain task for a certain case.
• In English, you would say “If <condition> is true, do <steps>!”
• In R, you would say:

if (condition) {
  step1
  step2
  ...
}

• condition object should be a logical statement/test or an R expression that evaluates to a single TRUE or FALSE.

• If condition is TRUE,
  • R will run all the code that appears between the curly brackets {} following the if statement.
• If condition is FALSE,
  • R will skip the code between the curly brackets without running it.

Below is an example of an if statement to make sure a number num is positive.

if (num < 0) {
  num <- num * -1
}

• In the case, num < 0 is TRUE:

num <- -2

if (num < 0) {
  num <- num * -1
}

num

## [1] 2

• In the case, num < 0 is FALSE:

num <- 4

if (num < 0) {
  num <- num * -1
}

num

## [1] 4

• Quiz 1: What will the following code return?

x <- 1
if (3 == 3) {
  x <- 2
}
x

• Quiz 2: What will the following code return?

x <- 1
if (TRUE) {
  x <- 2
}
x

• Quiz 3: What will the following code return?

x <- 1
if (x == 1) {
  x <- 2
  if (x == 1) {
    x <- 3
  }
}
x

else Statement

• if statement tells R what to do when the condition is TRUE.
• else statement tells R what to do when the condition is FALSE.

if (condition) {
  Plan A
} else {
  Plan B
}

• Example: Write a function for rounding a number to the nearest whole number.

a <- 3.14

• Isolate the decimal component with trunc() function.

decimal <- a - trunc(a)
decimal

## [1] 0.14

• Use if else to round the number (up or down):

if (decimal >= 0.5) {
  a <- trunc(a) + 1
} else {
  a <- trunc(a)
}

a

## [1] 3

• Write the rounding function:

my_round <- function(a) {
  decimal <- a - trunc(a)
  if (decimal >= 0.5) {
    a <- trunc(a) + 1
  } else {
    a <- trunc(a)
  }
  return(a)
}

my_round(3.14)

## [1] 3

round(3.14)

## [1] 3

my_round(4.9)

## [1] 5

round(4.9)

## [1] 5

• Another example

a <- 1
b <- 1

if (a > b) {
  print("A wins!")
} else if (a < b) {
  print("B wins!")
} else {
  print("Tie.")
}

## [1] "Tie."

Basic Plots

Histogram

cars

hist(x = cars$speed)

• Change the plot title

hist(x = cars$speed, main = "Histogram of Speed")

• Change x-axis label

hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)")

• Change the y-axis (from frequency) to probability/density

hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE)

• Change how the histogram is graphed (by changing the column width):
  • The argument breaks in hist() can take one of the following:
    • a vector giving the breakpoints between histogram cells,
    • a function to compute the vector of breakpoints,
    • a single number giving the number of cells for the histogram,
    • a character string naming an algorithm to compute the number of cells (see ‘Details’),
    • a function to compute the number of cells.

# a vector giving the breakpoints between histogram cells
hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = c(0, 4, 8, 12, 16, 20, 24, 28, 32))

# a function to compute the vector of breakpoints
hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = seq(from = 0, to = 30, by = 3))

# a single number giving the number of cells for the histogram
hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = 10)

# a single number giving the number of cells for the histogram
hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = "Freedman-Diaconis")

# a function to compute the number of cells
hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = 5*2)

• Let’s add some color to this histogram!

hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = seq(from = 0, to = 30, by = 3),
     col = "darkorange")

• A bit too much?

hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = seq(from = 0, to = 30, by = 3),
     border = "dodgerblue")

• Make it looks “professional”!

hist(x = cars$speed, main = "Histogram of Speed", xlab = "Speed (mph)", 
     probability = TRUE, breaks = seq(from = 0, to = 30, by = 3),
     col = "lightgrey")
box()
grid()

Boxplot

boxplot(x = cars$speed)

• Add title and axis label

boxplot(x = cars$speed, main = "Boxplot of Speed", ylab = "Speed (mph)")

• Change the orientation of the boxplot

boxplot(x = cars$speed, main = "Boxplot of Speed", xlab = "Speed (mph)",
        horizontal = TRUE)

Scatterplot

plot(x = cars$speed, y = cars$dist)

• Adding plot title, axis labels

plot(x = cars$speed, y = cars$dist, main = "Car Speed vs. Stopping Distance",
     xlab = "Speed (mph)", ylab = "Stopping Distance (ft)")

• Add color, change symbol, and other modifications.
  • See more details here.

plot(x = cars$speed, y = cars$dist, main = "Car Speed vs. Stopping Distance",
     xlab = "Speed (mph)", ylab = "Stopping Distance (ft)",
     col = "dodgerblue", pch = 19)
grid()

• Do you notice a difference in the code segment above and below?

plot(dist ~ speed, data = cars,
     main = "Car Speed vs. Stopping Distance",
     xlab = "Speed (mph)", ylab = "Stopping Distance (ft)",
     col = "dodgerblue", pch = 19)
grid()

To-do

• Homework 2 will be published after lecture.
• Read Chapter 11: Loops in Hands-On Programming with R.

References

• Hands-On Programming with R, by Garrett Grolemund.