Coordinate systems in R Programming - Mini Project: Build & Apply

Coordinate Systems

📖 Scenario: You are working with a simple map of a city park. The park has several landmarks, and you want to store their positions using coordinates.

🎯 Goal: Create a list of landmarks with their x and y coordinates, set a reference point, calculate the distance of each landmark from the reference point, and print the distances.

📋 What You'll Learn

Create a list called landmarks with named vectors for each landmark's x and y coordinates

Create a variable called reference_point as a named vector with x and y coordinates

Calculate the Euclidean distance from each landmark to the reference_point using a for loop and store results in a vector called distances

Print the distances vector

💡 Why This Matters

🌍 Real World

Coordinate systems help us locate places on maps, in games, or in real life, like finding landmarks in a park.

💼 Career

Understanding coordinates and distance calculations is useful in fields like geography, game development, robotics, and data visualization.

1

Create landmarks with coordinates

Create a list called landmarks with these exact entries: Fountain = c(x = 3, y = 4), Bench = c(x = 7, y = 1), Playground = c(x = 2, y = 8)

R Programming

# Create the landmarks list with coordinates
# Your code here

Hint

Use list() to create a list and c(x = value, y = value) for coordinates.

2

Set the reference point coordinates

Create a variable called reference_point as a named vector with x = 0 and y = 0

R Programming

landmarks <- list(Fountain = c(x = 3, y = 4), Bench = c(x = 7, y = 1), Playground = c(x = 2, y = 8))
# Create the reference_point vector
# Your code here

Hint

Use c(x = 0, y = 0) to create the reference point vector.

3

Calculate distances from reference point

Create a numeric vector called distances and use a for loop with variable name to calculate the Euclidean distance from each landmark in landmarks to reference_point. Store each distance in distances with the same names as landmarks.

R Programming

landmarks <- list(Fountain = c(x = 3, y = 4), Bench = c(x = 7, y = 1), Playground = c(x = 2, y = 8))
reference_point <- c(x = 0, y = 0)
# Calculate distances using a for loop
# Your code here

Hint

Use sqrt(dx^2 + dy^2) to calculate distance and assign it to distances[name].

4

Print the distances

Write a print() statement to display the distances vector

R Programming

landmarks <- list(Fountain = c(x = 3, y = 4), Bench = c(x = 7, y = 1), Playground = c(x = 2, y = 8))
reference_point <- c(x = 0, y = 0)
distances <- numeric(length(landmarks))
names(distances) <- names(landmarks)
for (name in names(landmarks)) {
  dx <- landmarks[[name]]["x"] - reference_point["x"]
  dy <- landmarks[[name]]["y"] - reference_point["y"]
  distances[name] <- sqrt(dx^2 + dy^2)
}
# Print the distances vector
# Your code here

Hint

Use print(distances) to show the distances.

Practice

1. Which function in R's ggplot2 package is used to flip the x and y axes on a plot?

easy

A. coord_flip()

B. coord_cartesian()

C. coord_polar()

D. coord_fixed()

Solution

1. Step 1: Understand coordinate functions in ggplot2

   The ggplot2 package provides several coordinate functions to control plot appearance.

2. Step 2: Identify the function that flips axes

   coord_flip() swaps the x and y axes, effectively flipping the plot.

3. Final Answer:

   coord_flip() -> Option A

4. Quick Check:

   Flip axes = coord_flip() [OK]

Hint: Flip axes with coord_flip() in ggplot2 [OK]

Common Mistakes:

• Confusing coord_flip() with coord_cartesian()
• Using coord_polar() which changes to polar coordinates
• Thinking coord_fixed() flips axes

2. Which of the following is the correct syntax to set fixed aspect ratio in ggplot2?

easy

A. coord_fixed_ratio(1)

B. coord_fixed(scale = 1)

C. coord_fixed(aspect = 1)

D. coord_fixed(ratio = 1)

Solution

1. Step 1: Recall the function for fixed aspect ratio

   coord_fixed() sets a fixed aspect ratio between x and y axes.

2. Step 2: Check correct argument name

   The argument to specify ratio is ratio, so coord_fixed(ratio = 1) is correct syntax.

3. Final Answer:

   coord_fixed(ratio = 1) -> Option D

4. Quick Check:

   Fixed ratio uses ratio= in coord_fixed() [OK]

Hint: Use ratio= argument in coord_fixed() for aspect ratio [OK]

Common Mistakes:

• Omitting argument name and just passing 1
• Using aspect= instead of ratio=
• Using a non-existent function coord_fixed_ratio()

3. What will be the effect of this code snippet in R using ggplot2?

ggplot(mtcars, aes(wt, mpg)) + geom_point() + coord_cartesian(xlim = c(2, 4), ylim = c(15, 30))

medium

A. Zooms the plot to show only points with weight between 2 and 4 and mpg between 15 and 30

B. Removes points outside the specified limits from the data

C. Flips the x and y axes

D. Changes the plot to polar coordinates

Solution

1. Step 1: Understand coord_cartesian() behavior

   coord_cartesian() zooms the plot to specified limits without removing data points.

2. Step 2: Analyze the limits given

   The x-axis is limited to 2 to 4 (weight), and y-axis to 15 to 30 (mpg), so plot zooms to this area.

3. Final Answer:

   Zooms the plot to show only points with weight between 2 and 4 and mpg between 15 and 30 -> Option A

4. Quick Check:

   coord_cartesian() zooms plot, does not remove data [OK]

Hint: coord_cartesian() zooms plot, keeps all data points [OK]

Common Mistakes:

• Thinking coord_cartesian() removes points outside limits
• Confusing with coord_flip() which flips axes
• Assuming coord_polar() is used here

4. Identify the error in this ggplot2 code snippet:

ggplot(mtcars, aes(wt, mpg)) + geom_point() + coord_flip(ratio = c(1, 5))

medium

A. geom_point() is missing required argument

B. coord_flip() does not accept ratio argument

C. ggplot() is missing data argument

D. coord_flip() should be replaced with coord_cartesian()

Solution

1. Step 1: Check arguments accepted by coord_flip()

   coord_flip() flips axes but does not accept ratio argument.

2. Step 2: Identify correct way to set aspect ratio when flipping

   Aspect ratio should be set using coord_fixed(), not inside coord_flip().

3. Final Answer:

   coord_flip() does not accept ratio argument -> Option B

4. Quick Check:

   coord_flip() has no ratio argument [OK]

Hint: coord_flip() does not accept ratio argument [OK]

Common Mistakes:

• Trying to set ratio inside coord_flip()
• Confusing coord_flip() with coord_cartesian()
• Assuming geom_point() needs extra arguments

5. You want to create a pie chart in ggplot2 using coord_polar(). Which coordinate system transformation should you apply before coord_polar() to make the pie chart correctly represent proportions?

hard

A. Use geom_point() with coord_polar()

B. Use geom_bar() with stat = 'identity'

C. Use geom_bar() with default settings and map fill to factor variable

D. Use geom_line() with coord_polar()

Solution

1. Step 1: Understand pie chart creation in ggplot2

   Pie charts are created by using bar charts with polar coordinates.

2. Step 2: Identify correct geom and mapping

   Using geom_bar() with default settings and mapping fill to a factor variable creates bars representing counts, which coord_polar() converts to pie slices.

3. Final Answer:

   Use geom_bar() with default settings and map fill to factor variable -> Option C

4. Quick Check:

   Pie chart = geom_bar() + coord_polar() with fill mapped [OK]

Hint: Pie charts use geom_bar() + coord_polar() with fill mapped [OK]

Common Mistakes:

• Using geom_point() or geom_line() which don't create bars
• Setting stat='identity' unnecessarily for counts
• Not mapping fill to a factor variable