Scatter plots (geom_point) in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of basic scatter plot code

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

R Programming

library(ggplot2)
data <- data.frame(x = 1:5, y = c(2, 3, 5, 7, 11))
ggplot(data, aes(x = x, y = y)) + geom_point()

A An error because geom_point() requires a color aesthetic

B A line plot connecting points (1,2), (2,3), (3,5), (4,7), (5,11)

C A bar chart showing y values for x from 1 to 5

D A scatter plot with points at coordinates (1,2), (2,3), (3,5), (4,7), (5,11)

💡 Hint

geom_point() creates scatter plots by plotting points at given x and y coordinates.

The code uses ggplot2 to plot points at the specified x and y values. geom_point() adds points, not lines or bars.

🧠 Conceptual

intermediate

Understanding aesthetics in geom_point

Which option correctly describes the role of the aes() function inside ggplot() when creating a scatter plot with geom_point()?

A aes() defines how variables map to visual properties like x and y positions of points

B aes() sets the size of the plot window

C aes() adds titles and labels to the plot

D aes() changes the color of the plot background

💡 Hint

Think about what aes() does with data variables in ggplot2.

aes() maps data variables to visual aesthetics like x, y, color, size, shape, etc. It does not control plot size or labels.

🔧 Debug

advanced

Identify the error in this scatter plot code

What error will this R code produce?

R Programming

library(ggplot2)
data <- data.frame(x = 1:3, y = c(4, 5, 6))
ggplot(data, aes(x = x, y = y)) + geom_point(color = "blue")

A Error: object 'color' not found

B SyntaxError: unexpected end of input due to missing closing parenthesis

C No error, plot will show blue points

D Error: geom_point() requires a size argument

💡 Hint

Check if all parentheses are properly closed.

The original code was missing a closing parenthesis after geom_point(color = "blue"), causing a syntax error. The corrected code includes the closing parenthesis.

❓ Predict Output

advanced

Effect of mapping color inside aes() vs outside

What is the difference in output between these two ggplot2 codes?

R Programming

library(ggplot2)
data <- data.frame(x = 1:4, y = c(2, 4, 6, 8), group = c('A', 'B', 'A', 'B'))

# Code 1:
ggplot(data, aes(x = x, y = y, color = group)) + geom_point()

# Code 2:
ggplot(data, aes(x = x, y = y)) + geom_point(color = 'red')

A Both codes color points by group

B Code 1 colors points by group; Code 2 colors all points red

C Code 1 colors all points red; Code 2 colors points by group

D Both codes color all points red

💡 Hint

aes() maps data variables to aesthetics; setting color outside aes() applies a fixed color.

In Code 1, color is mapped to the group variable, so points get different colors by group. In Code 2, color is fixed to red for all points.

🚀 Application

expert

Count of points plotted with filtering in geom_point

Given this code, how many points will be shown in the scatter plot?

R Programming

library(ggplot2)
data <- data.frame(x = 1:6, y = c(3, 5, 7, 9, 11, 13))
ggplot(data, aes(x = x, y = y)) + geom_point(data = subset(data, y > 7))

A 3 points

B 0 points

C 4 points

D 6 points

💡 Hint

Look at the subset condition y > 7 and count how many rows satisfy it.

Only points with y values greater than 7 are plotted. y values are 3,5,7,9,11,13 so points with y=9,11,13 qualify (3 points).

Practice

1. What does the geom_point() function do in ggplot2?

easy

A. It adds a line connecting data points.

B. It creates a bar chart with grouped bars.

C. It creates a scatter plot showing points for data pairs.

D. It summarizes data with a boxplot.

Solution

1. Step 1: Understand the purpose of geom_point()

   The function geom_point() is used in ggplot2 to add points to a plot, which is the basis of a scatter plot.

2. Step 2: Identify the plot type created

   Scatter plots show the relationship between two numeric variables using dots, which matches what geom_point() does.

3. Final Answer:

   It creates a scatter plot showing points for data pairs. -> Option C

4. Quick Check:

   geom_point() = scatter plot points [OK]

Hint: Remember: geom_point() means dots on a scatter plot [OK]

Common Mistakes:

• Confusing geom_point() with geom_line()
• Thinking geom_point() creates bar charts
• Mixing up scatter plots with boxplots

2. Which of the following is the correct syntax to create a scatter plot with height on the x-axis and weight on the y-axis using ggplot2?

easy

A. ggplot(data) + geom_point(height, weight)

B. ggplot(data) + geom_point(aes(x = weight, y = height))

C. ggplot(data) + geom_point(x = height, y = weight)

D. ggplot(data) + geom_point(aes(x = height, y = weight))

Solution

1. Step 1: Check the correct use of aes() inside geom_point()

   The aesthetics mapping aes() must specify which variables go on x and y axes inside geom_point().

2. Step 2: Verify the order of variables

   The question asks for height on x-axis and weight on y-axis, so aes(x = height, y = weight) is correct.

3. Final Answer:

   ggplot(data) + geom_point(aes(x = height, y = weight)) -> Option D

4. Quick Check:

   Correct aes() syntax = ggplot(data) + geom_point(aes(x = height, y = weight)) [OK]

Hint: Always put aes(x=, y=) inside geom_point() [OK]

Common Mistakes:

• Swapping x and y variables
• Passing variables directly to geom_point() without aes()
• Omitting aes() entirely

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

library(ggplot2)
data <- data.frame(x = 1:3, y = c(4, 5, 6))
ggplot(data) + geom_point(aes(x = x, y = y))

medium

A. A scatter plot with points at (1,4), (2,5), and (3,6).

B. A line plot connecting points (1,4), (2,5), and (3,6).

C. An error because aes() is missing.

D. A bar chart showing counts of x.

Solution

1. Step 1: Understand the data and mapping

   The data frame has x values 1, 2, 3 and y values 4, 5, 6. The aes() maps x to x-axis and y to y-axis.

2. Step 2: Identify the plot type from geom_point()

   geom_point() creates a scatter plot with points at the specified coordinates.

3. Final Answer:

   A scatter plot with points at (1,4), (2,5), and (3,6). -> Option A

4. Quick Check:

   geom_point() plots points at (x,y) pairs [OK]

Hint: geom_point() plots points exactly at aes(x, y) coordinates [OK]

Common Mistakes:

• Expecting a line plot instead of points
• Thinking aes() is missing causes error here
• Confusing bar chart with scatter plot

4. Identify the error in this code snippet:

ggplot(data) + geom_point(x = height, y = weight)

medium

A. Using ggplot() without data argument.

B. Missing aes() around x and y inside geom_point().

C. geom_point() cannot plot numeric data.

D. x and y should be swapped.

Solution

1. Step 1: Check how aesthetics are passed to geom_point()

   In ggplot2, x and y mappings must be inside aes() to link variables to axes.

2. Step 2: Identify the missing aes() call

   The code passes x and y directly to geom_point(), which is incorrect syntax.

3. Final Answer:

   Missing aes() around x and y inside geom_point(). -> Option B

4. Quick Check:

   Always use aes(x=, y=) inside geom_point() [OK]

Hint: Always wrap x and y in aes() inside geom_point() [OK]

Common Mistakes:

• Passing x and y directly without aes()
• Forgetting to provide data to ggplot()
• Swapping x and y unnecessarily

5. You want to create a scatter plot of mpg vs hp from the built-in mtcars dataset, but only for cars with cyl equal to 6. Which code correctly does this?

hard

A. ggplot(subset(mtcars, cyl == 6)) + geom_point(aes(x = hp, y = mpg))

B. ggplot(mtcars) + geom_point(aes(x = hp, y = mpg), subset = cyl == 6)

C. ggplot(mtcars) + geom_point(aes(x = hp, y = mpg)) + filter(cyl == 6)

D. ggplot(mtcars) + geom_point(aes(x = hp, y = mpg)) + subset(cyl == 6)

Solution

1. Step 1: Filter data before plotting

   To plot only cars with 6 cylinders, filter the data frame using subset(mtcars, cyl == 6).

2. Step 2: Use filtered data in ggplot()

   Pass the filtered data to ggplot(), then add geom_point() with correct aesthetics.

3. Final Answer:

   ggplot(subset(mtcars, cyl == 6)) + geom_point(aes(x = hp, y = mpg)) -> Option A

4. Quick Check:

   Filter data first, then plot with geom_point() [OK]

Hint: Filter data before ggplot() to plot subsets [OK]

Common Mistakes:

• Trying to filter inside geom_point() which is invalid
• Using filter() without dplyr or outside ggplot()
• Passing subset as argument to geom_point()