Multiple Choices: Based Plot: Barplot

1. Which function is primarily used to create a bar plot in base R?

barplot() plot() hist() pie()

2. When using barplot(), which argument adjusts the colors of the bars?

color col fill bars

3. To create a horizontal bar plot using barplot(), which argument should be set to TRUE?

horizontal vert horiz side

4. Which argument in barplot() specifies the labels for each bar?

names.arg labels text lab

5. In the following code, what does las = 2 do to the bar plot?

   barplot(1:5, las = 2)

Rotates bar labels 45 degrees. Rotates bar labels 90 degrees. Inverts the colors of the bars. Changes the font of the labels.

6. How can you create a stacked bar plot with barplot() in base R?

Use stacked = TRUE Use beside = FALSE Use beside = TRUE Use grouped = TRUE

7. What does setting beside = TRUE in barplot() do?

Stacks the bars. Creates grouped bars side by side. Adds space between the bars. Flips the orientation of the bars.

8. In base R, how can you add a title to a bar plot created with barplot()?

title = "Title" main = "Title" header = "Title" caption = "Title"

9. Which function can be used to add a legend to a bar plot created with barplot()?

legend() addLegend() barlegend() add.legend()

10. What argument controls the space between bars in a bar plot created with barplot()?

gap spacing space pad

11. To add axis labels to a bar plot in base R, which arguments are used?

xlabel and ylabel xlab and ylab axis.x and axis.y xaxis and yaxis

12. What is the purpose of the ylim argument in barplot()?

Sets the color limit for the bars. Specifies the label of the y-axis. Controls the range of values on the y-axis. Defines the maximum width of each bar.

13. Which argument is used in barplot() to set the width of each bar?

barwidth width size thickness

14. How would you display the numeric values above each bar in a bar plot?

text() label() values() annotate()

15. In the following code, what effect does border = "blue" have?

   barplot(1:5, border = "blue")

Fills bars with blue. Adds a blue border around each bar. Adds blue labels to each bar. Colors the background blue.

16. To save a bar plot as a PNG file in base R, which function should be used before barplot()?

png() savePlot() export() write()

17. How can you add grid lines to a bar plot in base R?

grid() lines() abline() gridlines()

18. Which of the following creates a bar plot with bars ordered from largest to smallest?

   values <- c(4, 7, 3, 6)
   names(values) <- c("A", "B", "C", "D")

barplot(values, order = TRUE) barplot(sort(values, decreasing = TRUE)) barplot(values, decreasing = TRUE) barplot(desc(values))

19. Which function in base R can be used to calculate the heights needed for a bar plot with grouped data?

table() summary() length() aggregate()

20. When creating a stacked bar plot in base R, what format should the data be in?

List format. Matrix format. Data frame format. Vector format.

NoteNote

abline()

To add grid lines to a bar plot in base R, you can use the abline() function after calling barplot(). Here’s a quick example:

# Sample data
heights <- c(5, 10, 15, 20)

# Create bar plot
barplot(heights, col = "skyblue", ylim = c(0, 20))

# Add horizontal grid lines
abline(h = seq(0, 20, by = 5), col = "gray", lty = 2)

Explanation:

• seq(0, 20, by = 5): Creates a sequence of values for the y-axis grid lines, from 0 to 20 in increments of 5.

• abline(h = ...): Adds horizontal lines at the specified y values.

• col = "gray": Sets the color of the grid lines to gray.

• lty = 2: Specifies a dashed line type for the grid lines.

This approach can be adjusted for vertical lines using v = ... inside abline() if needed.

Good question! The grid() function is indeed another way to add grid lines to a plot in base R. However, grid() works best with the plot() function, which has default grid spacing aligned with the major tick marks.

For bar plots, where the x-axis positions of the bars are not automatically aligned with tick marks, abline() offers more precise control over the exact placement of the grid lines.

grid():

If you still want to use grid() with barplot(), you can do so like this:

# Sample data
heights <- c(5, 10, 15, 20)

# Create the bar plot
barplot(heights, col = "skyblue", ylim = c(0, 20))

# Add grid lines
grid(nx = NA, ny = NULL, col = "gray", lty = 2)

Explanation:

• nx = NA: Omits grid lines on the x-axis (since bar centers may not align perfectly).

• ny = NULL: Adds grid lines on the y-axis according to tick marks.

• col = "gray" and lty = 2: Customize the color and line type of the grid lines.

In summary:

• Use grid() for a quick grid with default spacing aligned with tick marks.

• Use abline() for finer control over the exact placement and spacing of grid lines.

In base R, a stacked bar plot requires the data to be in a matrix format because each column in the matrix represents a category, and each row represents a component to be stacked on top of each other within each bar.

Why Matrix Format?

1. Column as Categories: Each column in the matrix corresponds to a single bar in the plot, representing a distinct category.
2. Row as Stacks: Each row contains values for components that are stacked on top of each other within each bar.
3. Alignment: The matrix format allows barplot() to treat each column as a separate bar and to stack the values of each row on top of each other within that bar.

Example of a Stacked Bar Plot in Base R

Here’s an example that demonstrates how to use matrix data for a stacked bar plot:

# Create a matrix of data
data_matrix <- matrix(c(4, 6, 8, 2, 5, 7), nrow = 3, byrow = TRUE)
colnames(data_matrix) <- c("Category 1", "Category 2")
rownames(data_matrix) <- c("Group A", "Group B", "Group C")

# Create stacked bar plot
barplot(data_matrix, col = c("skyblue", "orange", "lightgreen"), 
        legend.text = rownames(data_matrix), beside = FALSE)

Explanation:

• matrix(): Constructs a 3x2 matrix where each row (Group A, Group B, Group C) represents a component that will be stacked in each bar.

• colnames and rownames: Assign category names for each bar and component names for each stack, which helps in identifying the bars and components in the plot.

• col: Sets different colors for each row (stack) to visually distinguish the stacked segments.

• legend.text: Adds a legend that maps the color to each row (stacked component).

• beside = FALSE: Ensures the bars are stacked rather than placed side-by-side.

Using a matrix ensures the barplot() function can accurately stack the data, making it a clear and effective representation.