Grammar of Graphics concept in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a basic scatter plot using ggplot2.

R Programming

library(ggplot2)
ggplot(data = mtcars, aes(x = wt, y = mpg)) + geom_[1]()

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

Apoint

Bbar

Cscatter

Dline

Attempts:

3 left

💡 Hint

Common Mistakes

Using geom_bar() or geom_line() instead of geom_point()

The geom_point() function creates a scatter plot in ggplot2, which is the basic geometric object for points.

2fill in blank

medium

Complete the code to map the color aesthetic to the variable 'cyl' in the plot.

R Programming

ggplot(mtcars, aes(x = wt, y = mpg, color = [1])) + geom_point()

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

Agear

Bwt

Ccyl

Dmpg

Attempts:

3 left

💡 Hint

Common Mistakes

Mapping color to continuous variables like 'wt' or 'mpg' without intention

Mapping color = cyl colors the points based on the number of cylinders, adding an informative visual grouping.

3fill in blank

hard

Fix the error in the code to add a title to the plot using ggtitle().

R Programming

ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() + ggtitle([1])

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

Ampg vs wt

B"mpg vs wt"

Cmpg_vs_wt

Dmpg_vs_wt()

Attempts:

3 left

💡 Hint

Common Mistakes

Not using quotes around the title text

The title text must be a string, so it needs to be enclosed in quotes like "mpg vs wt".

4fill in blank

hard

Fill both blanks to create a histogram of 'mpg' with blue fill color.

R Programming

ggplot(mtcars, aes(x = [1])) + geom_histogram(fill = [2])

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

Ampg

B"blue"

Cwt

D"red"

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong variable for x or missing quotes around color

The histogram should use mpg for the x-axis and fill color set to the string "blue".

5fill in blank

hard

Fill all three blanks to create a boxplot of 'mpg' grouped by 'cyl' with green boxes and a title.

R Programming

ggplot(mtcars, aes(x = [1], y = [2])) + geom_boxplot(fill = [3]) + ggtitle("MPG by Cylinders")

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

Acyl

Bmpg

C"green"

Dwt

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping x and y variables or missing quotes around color

The x-axis groups by cyl, y-axis shows mpg, and the boxplot fill color is "green".

Practice

1. In the Grammar of Graphics, which component defines how data variables are mapped to visual properties like color or size in a plot?

easy

A. Data

B. Aesthetics

C. Layers

D. Facets

Solution

1. Step 1: Understand the role of aesthetics

   Aesthetics specify how data variables correspond to visual elements such as color, size, or shape.

2. Step 2: Differentiate from other components

   Data is the raw information, layers are the graphical elements, and facets split plots; only aesthetics map variables visually.

3. Final Answer:

   Aesthetics -> Option B

4. Quick Check:

   Mapping variables to visuals = Aesthetics [OK]

Hint: Remember: aesthetics = visual mapping of data [OK]

Common Mistakes:

• Confusing data with aesthetics
• Thinking layers define variable mapping
• Mixing facets with aesthetics

2. Which of the following is the correct way to start a ggplot object in R using the Grammar of Graphics?

easy

A. ggplot(aes(x = var1, y = var2), data = mydata)

B. plot(data = mydata, aes(x = var1, y = var2))

C. ggplot(data = mydata, aes(x = var1, y = var2))

D. ggplot(mydata, x = var1, y = var2)

Solution

1. Step 1: Recall ggplot syntax

   The correct syntax is ggplot(data = ..., aes(...)) where data is first, then aesthetics.

2. Step 2: Check each option

   ggplot(data = mydata, aes(x = var1, y = var2)) matches the correct syntax; using plot() refers to base R graphics, not ggplot2; swapping data and aes() arguments assigns them incorrectly due to positional matching; omitting aes() fails to map variables to aesthetics.

3. Final Answer:

   ggplot(data = mydata, aes(x = var1, y = var2)) -> Option C

4. Quick Check:

   ggplot(data, aes()) syntax = ggplot(data = mydata, aes(x = var1, y = var2)) [OK]

Hint: ggplot(data=..., aes(...)) is the standard start [OK]

Common Mistakes:

• Using base plot() instead of ggplot()
• Swapping data and aes() arguments
• Not wrapping variables inside aes()

3. What will be the output of this R code using ggplot2?

library(ggplot2)
data <- data.frame(x = 1:3, y = c(2, 4, 6))
ggplot(data, aes(x = x, y = y)) + geom_point()

medium

A. An error because geom_point() is missing arguments

B. A line plot connecting points (1,2), (2,4), and (3,6)

C. A bar chart showing counts of x values

D. A scatter plot with points at (1,2), (2,4), and (3,6)

Solution

1. Step 1: Understand the code components

   ggplot() sets data and aesthetics; geom_point() adds points for each (x,y) pair.

2. Step 2: Predict the plot output

   Since geom_point() is used, the plot shows points at (1,2), (2,4), and (3,6) as a scatter plot.

3. Final Answer:

   A scatter plot with points at (1,2), (2,4), and (3,6) -> Option D

4. Quick Check:

   geom_point() = scatter plot points [OK]

Hint: geom_point() always plots points, not lines or bars [OK]

Common Mistakes:

• Confusing geom_point() with geom_line()
• Expecting a bar chart instead of points
• Thinking geom_point() needs extra arguments

4. Identify the error in this ggplot2 code snippet:

ggplot(data = df, aes(x = var1, y = var2)) + geom_point(color = var3)

medium

A. color should be inside aes() to map to var3

B. geom_point() cannot have color argument

C. aes() must include color outside geom_point()

D. data argument is missing in ggplot()

Solution

1. Step 1: Understand color mapping in ggplot2

   To map a variable to color, it must be inside aes(), not as a fixed argument.

2. Step 2: Analyze the code

   color = var3 is outside aes(), so ggplot treats it as a fixed color, causing an error or wrong plot.

3. Final Answer:

   color should be inside aes() to map to var3 -> Option A

4. Quick Check:

   Variable color mapping requires aes() [OK]

Hint: Put variable color inside aes(), fixed color outside [OK]

Common Mistakes:

• Placing variable color outside aes()
• Thinking geom_point() disallows color
• Omitting data argument in ggplot()

5. You want to create a layered plot in ggplot2 showing points and a smooth trend line for data frame df with variables x and y. Which code correctly applies the Grammar of Graphics to achieve this?

hard

A. ggplot(df, aes(x = x, y = y)) + geom_point() + geom_smooth()

B. ggplot(df) + geom_point(aes(x = x, y = y)) + geom_smooth()

C. ggplot() + geom_point(df, aes(x = x, y = y)) + geom_smooth(df, aes(x = x, y = y))

D. ggplot(df, aes(x = x)) + geom_point() + geom_smooth()

Solution

1. Step 1: Understand layering in ggplot2

   Layers add graphical elements; setting data and aesthetics once in ggplot() is best practice.

2. Step 2: Evaluate each option

   ggplot(df, aes(x = x, y = y)) + geom_point() + geom_smooth() sets data and aesthetics once, then adds point and smooth layers correctly. Specifying aes(x = x) globally without y in layers causes missing y aesthetic error. Starting with bare ggplot(df) and aes only in first geom leaves smooth without mappings. Passing df directly to geoms after empty ggplot() misuses argument positions.

3. Final Answer:

   ggplot(df, aes(x = x, y = y)) + geom_point() + geom_smooth() -> Option A

4. Quick Check:

   Layered plot with shared aes() = ggplot(df, aes(x = x, y = y)) + geom_point() + geom_smooth() [OK]

Hint: Set data and aes() once, then add layers [OK]

Common Mistakes:

• Incomplete aesthetics when splitting across layers
• Omitting aes() in later layers
• Passing data inside geom_ functions incorrectly