Scatter plots (geom_point) in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of geom_point() in R's ggplot2?

geom_point() adds points to a plot, creating a scatter plot that shows the relationship between two continuous variables.

beginner

How do you specify the x and y variables in a scatter plot using ggplot2?

You specify them inside aes() as x = variable1 and y = variable2 when creating the plot.

intermediate

What happens if you add color inside aes() in geom_point()?

Points are colored based on the values of the variable mapped to color, helping to show groups or categories.

beginner

How can you change the size of points in a scatter plot?

You can set the size argument inside geom_point() to a number to make points bigger or smaller.

beginner

Why is a scatter plot useful in data analysis?

It helps you see patterns, trends, or relationships between two numeric variables visually.

What does geom_point() do in ggplot2?

A Creates a scatter plot by adding points

B Creates a bar chart

C Adds a line to the plot

D Removes points from the plot

geom_point() adds points to create scatter plots showing relationships between variables.

Where do you specify which variables go on the x and y axes in ggplot2?

A Inside <code>aes()</code> function

B Inside <code>geom_point()</code> size argument

C In the <code>labs()</code> function

D In the <code>theme()</code> function

The aes() function maps variables to axes and other aesthetics.

How do you color points by a category in a scatter plot?

A Use <code>size</code> argument

B Map the category variable to <code>color</code> inside <code>aes()</code>

C Set <code>color</code> outside <code>aes()</code> to a variable

D Use <code>fill</code> argument inside <code>geom_point()</code>

Mapping a variable to color inside aes() colors points by that variable.

Which argument changes the size of points in geom_point()?

A alpha

B color

C size

D shape

The size argument controls how big or small the points appear.

What kind of variables are best visualized with scatter plots?

A Only one variable

B Two categorical variables

C One numeric and one categorical variable

D Two numeric continuous variables

Scatter plots show relationships between two numeric continuous variables.

Explain how to create a basic scatter plot using ggplot2 and geom_point().

Think about how you tell ggplot which data to use and which variables go on the axes.

Describe how you can use color and size to add more information to a scatter plot.

Consider how different point colors or sizes can show categories or importance.

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()