ggplot() and aes() basics in R Programming - Mini Project: Build & Apply

Basic Plot with ggplot() and aes() in R

📖 Scenario: You are a data analyst who wants to visualize the relationship between two variables in a small dataset. You will create a simple scatter plot using ggplot() and aes() from the ggplot2 package in R.

🎯 Goal: Build a scatter plot using ggplot() and aes() to map variables to the x and y axes.

📋 What You'll Learn

Create a data frame called data with two numeric columns: height and weight with exact values

Create a ggplot object using ggplot() with data as the data source

Use aes() inside ggplot() to map height to the x-axis and weight to the y-axis

Add geom_point() to display the points

Print the plot object to display the scatter plot

💡 Why This Matters

🌍 Real World

Creating visualizations helps understand data patterns and relationships quickly, which is useful in reports and presentations.

💼 Career

Data analysts and scientists use ggplot2 to create clear and attractive charts to communicate insights effectively.

1

Create the data frame

Create a data frame called data with two columns: height containing the values 150, 160, 170, 180, 190 and weight containing the values 65, 70, 75, 80, 85.

R Programming

# Create the data frame called data with height and weight columns
# Your code here

Hint

Use data.frame() with height = c(...) and weight = c(...) to create the data.

2

Create the ggplot object with aes()

Create a variable called plot and assign it the result of ggplot() with data as the data source and aes() mapping height to x and weight to y.

R Programming

data <- data.frame(
  height = c(150, 160, 170, 180, 190),
  weight = c(65, 70, 75, 80, 85)
)
# Create the ggplot object called plot with aes mapping height to x and weight to y
# Your code here

Hint

Use ggplot(data, aes(x = height, y = weight)) and assign it to plot.

3

Add points to the plot

Add geom_point() to the plot object to show the data points. Update plot by adding + geom_point().

R Programming

library(ggplot2)

data <- data.frame(
  height = c(150, 160, 170, 180, 190),
  weight = c(65, 70, 75, 80, 85)
)

plot <- ggplot(data, aes(x = height, y = weight))
# Add geom_point() to plot
# Your code here

Hint

Add + geom_point() to the ggplot call to show points.

4

Display the plot

Print the plot object to display the scatter plot.

R Programming

library(ggplot2)

data <- data.frame(
  height = c(150, 160, 170, 180, 190),
  weight = c(65, 70, 75, 80, 85)
)

plot <- ggplot(data, aes(x = height, y = weight)) + geom_point()
# Print the plot to display it
# Your code here

Hint

Use print(plot) to show the plot.

Practice

1. What is the main purpose of the aes() function in ggplot()?

easy

A. To add titles and labels to the plot

B. To map data columns to visual properties like x and y axes

C. To create the plot background color

D. To save the plot as an image file

Solution

1. Step 1: Understand the role of aes()

   The aes() function defines how data columns are linked to visual elements like axes or colors.

2. Step 2: Compare options with aes() purpose

   Only To map data columns to visual properties like x and y axes correctly describes mapping data columns to x and y axes, which is the main use of aes().

3. Final Answer:

   To map data columns to visual properties like x and y axes -> Option B

4. Quick Check:

   Mapping data columns = A [OK]

Hint: Remember: aes() sets data to axes or colors [OK]

Common Mistakes:

• Thinking aes() adds titles or labels
• Confusing aes() with saving or styling functions
• Assuming aes() creates plot background

2. Which of the following is the correct syntax to start a scatter plot with ggplot() using data frame df and mapping x to column age and y to column height?

easy

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

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

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

D. ggplot(df, geom_point(aes(x = age, y = height)))

Solution

1. Step 1: Recall correct ggplot() syntax

   The correct syntax is ggplot(data, aes(...)) + geom_* where data is first, then aes() inside ggplot.

2. Step 2: Check each option

   ggplot(df, aes(x = age, y = height)) + geom_point() matches the correct order and usage. The other options misuse argument order or place aes() outside ggplot().

3. Final Answer:

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

4. Quick Check:

   Data first, then aes() inside ggplot() = B [OK]

Hint: Put data first, then aes() inside ggplot() [OK]

Common Mistakes:

• Swapping data and aes() arguments
• Calling aes() outside ggplot()
• Putting geom_point() inside ggplot() arguments

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

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

medium

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

B. A bar chart showing counts of x values

C. An error because geom_point() is missing arguments

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

Solution

1. Step 1: Understand the code components

   The code creates a data frame with x and y values, then plots points using geom_point() which draws scatter points.

2. Step 2: Identify the plot type and points

   geom_point() creates scatter points at coordinates from x and y columns: (1,4), (2,5), (3,6).

3. Final Answer:

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

4. Quick Check:

   geom_point() draws scatter points = D [OK]

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

Common Mistakes:

• Confusing geom_point() with geom_bar() or geom_line()
• Expecting a line plot instead of points
• Thinking geom_point() needs extra arguments

4. Identify the error in this code snippet:

ggplot(mtcars, aes(x = mpg, y = hp))
geom_point()

medium

A. aes() should be outside ggplot()

B. Incorrect column names mpg and hp

C. geom_point() cannot be used with mtcars dataset

D. Missing + operator between ggplot() and geom_point()

Solution

1. Step 1: Check how layers are added in ggplot2

   Layers like geom_point() must be added with a + operator after ggplot().

2. Step 2: Review the code for missing +

   The code calls ggplot() and then geom_point() on a new line without +, causing an error.

3. Final Answer:

   Missing + operator between ggplot() and geom_point() -> Option D

4. Quick Check:

   Use + to add layers in ggplot2 = C [OK]

Hint: Add + between ggplot() and geoms to avoid errors [OK]

Common Mistakes:

• Forgetting the + operator between layers
• Thinking aes() must be outside ggplot()
• Assuming dataset columns are incorrect without checking

5. You want to create a scatter plot using ggplot() with data frame df that has columns time, score, and group. You want points colored by group. Which code correctly achieves this?

hard

A. ggplot(df) + aes(x = time, y = score, color = group) + geom_point()

B. ggplot(df, aes(x = time, y = score)) + geom_point(color = group)

C. ggplot(df, aes(x = time, y = score, color = group)) + geom_point()

D. ggplot(df, geom_point(aes(x = time, y = score, color = group)))

Solution

1. Step 1: Understand how to map color by a data column

   Color mapping must be inside aes() so ggplot knows to use data values for color.

2. Step 2: Check each option for correct color mapping

   ggplot(df, aes(x = time, y = score, color = group)) + geom_point() correctly maps color inside aes() in ggplot().
   ggplot(df, aes(x = time, y = score)) + geom_point(color = group) sets color outside aes(), causing an error.
   ggplot(df) + aes(x = time, y = score, color = group) + geom_point() incorrectly treats aes() as a layer.
   ggplot(df, geom_point(aes(x = time, y = score, color = group))) incorrectly nests geom_point() inside ggplot().

3. Final Answer:

   ggplot(df, aes(x = time, y = score, color = group)) + geom_point() -> Option C

4. Quick Check:

   Map color inside aes() in ggplot() = A [OK]

Hint: Put color inside aes() to map by data column [OK]

Common Mistakes:

• Setting color outside aes() causing fixed color
• Adding aes() as a layer with +
• Putting geom_point() inside ggplot() arguments