Coordinate systems in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a scatter plot using base R with x and y coordinates.

R Programming

plot(x, y, type = [1])

Drag options to blanks, or click blank then click option'

A"p"

B"l"

C"h"

D"b"

Attempts:

3 left

💡 Hint

Common Mistakes

Using type = "l" which draws lines instead of points.

Forgetting to put quotes around the type value.

In base R, type = "p" creates a scatter plot showing points.

2fill in blank

medium

Complete the code to convert Cartesian coordinates (x, y) to polar coordinates (r, theta).

R Programming

r <- sqrt([1]^2 + y^2)

Drag options to blanks, or click blank then click option'

Ax

Btheta

Cr

Dsin

Attempts:

3 left

💡 Hint

Common Mistakes

Using theta instead of x in the formula.

Confusing the radius r with the angle theta.

The radius r in polar coordinates is the square root of x^2 + y^2.

3fill in blank

hard

Fix the error in the code to calculate the angle theta in radians from Cartesian coordinates.

R Programming

theta <- atan2(y, [1])

Drag options to blanks, or click blank then click option'

Ar

Bsin

Cx

Dcos

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the order of x and y in atan2.

Using trigonometric functions like sin or cos incorrectly.

The atan2 function takes y first and then x, but in R it is atan2(y, x). Here, to get the angle, the first argument should be y and the second x. The code has the arguments reversed, so the blank should be x to fix the order.

4fill in blank

hard

Fill both blanks to create a data frame with polar coordinates from Cartesian vectors x and y.

R Programming

polar_coords <- data.frame(r = sqrt(x[1] + y[2]))

Drag options to blanks, or click blank then click option'

A^2

B+

C*2

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiplication *2 instead of exponentiation.

Using subtraction instead of addition.

To calculate radius r, square both x and y using ^2, then add them.

5fill in blank

hard

Fill all three blanks to convert polar coordinates (r, theta) back to Cartesian coordinates (x, y).

R Programming

x <- [1] * cos([2])
y <- [3] * sin(theta)

Drag options to blanks, or click blank then click option'

Ar

Btheta

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Using x instead of r in the formulas.

Swapping r and theta in the function arguments.

To convert polar to Cartesian, multiply radius r by cosine or sine of angle theta.

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