Multiple Choices: Based Plot: Barplot

  1. Which function is primarily used to create a bar plot in base R? ::: {.cell}
  1. When using barplot(), which argument adjusts the colors of the bars? ::: {.cell}

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  1. To create a horizontal bar plot using barplot(), which argument should be set to TRUE? ::: {.cell}

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  1. Which argument in barplot() specifies the labels for each bar? ::: {.cell}

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  1. In the following code, what does las = 2 do to the bar plot?
   barplot(1:5, las = 2)
  1. How can you create a stacked bar plot with barplot() in base R? ::: {.cell}

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  1. What does setting beside = TRUE in barplot() do? ::: {.cell}

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  1. In base R, how can you add a title to a bar plot created with barplot()? ::: {.cell}

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  1. Which function can be used to add a legend to a bar plot created with barplot()? ::: {.cell}

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  1. What argument controls the space between bars in a bar plot created with barplot()? ::: {.cell}

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  1. To add axis labels to a bar plot in base R, which arguments are used? ::: {.cell}

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  1. What is the purpose of the ylim argument in barplot()? ::: {.cell}

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  1. Which argument is used in barplot() to set the width of each bar? ::: {.cell}

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  1. How would you display the numeric values above each bar in a bar plot? ::: {.cell}

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  1. In the following code, what effect does border = "blue" have?
   barplot(1:5, border = "blue")
  1. To save a bar plot as a PNG file in base R, which function should be used before barplot()?
  1. How can you add grid lines to a bar plot in base R?
  1. 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")
  1. Which function in base R can be used to calculate the heights needed for a bar plot with grouped data? ::: {.cell}

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  1. When creating a stacked bar plot in base R, what format should the data be in? ::: {.cell}

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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.