Scatter plots (geom_point) in R Programming - Mini Project: Build & Apply

Scatter plots (geom_point)

📖 Scenario: You are a data analyst working with a small dataset of car speeds and stopping distances. You want to visualize the relationship between speed and distance using a scatter plot.

🎯 Goal: Create a scatter plot using geom_point in ggplot2 to show how car speed relates to stopping distance.

📋 What You'll Learn

Create a data frame called cars_data with columns speed and dist using the exact values provided.

Create a variable called plot_title with the exact string 'Speed vs Stopping Distance'.

Use ggplot with geom_point to create a scatter plot of speed on the x-axis and dist on the y-axis.

Add the title stored in plot_title to the plot using ggtitle().

Print the plot object to display the scatter plot.

💡 Why This Matters

🌍 Real World

Scatter plots help visualize relationships between two numeric variables, such as speed and stopping distance in cars.

💼 Career

Data analysts and scientists use scatter plots to explore data patterns and communicate findings clearly.

1

Create the data frame

Create a data frame called cars_data with two columns: speed containing the values 4, 7, 8, 9, 10 and dist containing the values 2, 10, 15, 20, 25.

R Programming

# Create the data frame cars_data with speed and dist columns
# Your code here

Hint

Use data.frame() with speed = c(...) and dist = c(...) to create the data frame.

2

Add a plot title variable

Create a variable called plot_title and assign it the string 'Speed vs Stopping Distance'.

R Programming

cars_data <- data.frame(
  speed = c(4, 7, 8, 9, 10),
  dist = c(2, 10, 15, 20, 25)
)
# Create the plot_title variable
# Your code here

Hint

Assign the exact string to plot_title using the assignment operator <-.

3

Create the scatter plot

Use ggplot with the data frame cars_data. Map speed to the x-axis and dist to the y-axis. Add geom_point() to create the scatter plot points.

R Programming

cars_data <- data.frame(
  speed = c(4, 7, 8, 9, 10),
  dist = c(2, 10, 15, 20, 25)
)
plot_title <- 'Speed vs Stopping Distance'

# Create the ggplot object with geom_point
# Your code here

Hint

Use ggplot(data, aes(x = ..., y = ...)) + geom_point() to create the scatter plot.

4

Add title and display the plot

Add the title stored in plot_title to the plot using ggtitle(plot_title). Then print the plot object to display the scatter plot.

R Programming

library(ggplot2)
cars_data <- data.frame(
  speed = c(4, 7, 8, 9, 10),
  dist = c(2, 10, 15, 20, 25)
)
plot_title <- 'Speed vs Stopping Distance'

plot <- ggplot(cars_data, aes(x = speed, y = dist)) + geom_point()

# Add the title and print the plot
# Your code here

Hint

Use plot + ggtitle(plot_title) to add the title, then print(plot) to show the plot.

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()