In R, graphics devices are the interfaces through which R plots are rendered. If you understand graphics devices it’s crucial for creating and customizing plots effectively.

There are primarily two types of graphics devices in R: screen devices and file devices.

1. Screen Devices

Screen devices, as the name suggests, render plots directly onto the screen. The primary screen device in R is the default graphics device, usually a window displaying the plot.

Example

# Open a new graphics device (screen device)
x <- c(1, 2, 3, 4)
y <- c(1, 4, 9, 16)
plot(x, y) # Plot displayed on the screen

2. File Devices

File devices render plots to external files in various formats such as PNG, PDF, JPEG, etc. This is useful for saving plots for later use or embedding them in documents.

Example

# Open a new graphics device (file device)
png("plot.png")
x <- c(1, 2, 3, 4)
y <- c(1, 4, 9, 16)
plot(x, y) # Plot rendered to the file "plot.png"
dev.off() # Close the file device

Graphics parameters in R control various aspects of plot appearance such as colors, line types, point types, etc. They can be set globally for all subsequent plots or locally for individual plots.

Let me explain the commonly used graphics parameters in R.

• pch – Sets the plotting symbol (point type).
• col – Sets the color of plotting symbols, lines, and text.
• lty – Sets the line type (solid, dashed, etc.).
• lwd – Sets the line width.
• main – Sets the main title of the plot.
• xlab, ylab – Set the labels for the x and y-axis respectively.

Now I’ll give you an example demonstrating the use of some of these graphics parameters.

# Set up some data
x <- 1:10
y <- x^2

# Customize plot appearance using graphics parameters
plot(x, y,
type = "b", # Plot both points and lines
pch = 16, # Point type (filled circle)
col = "blue", # Color of points and lines
lty = 2, # Line type (dashed)
lwd = 2, # Line width
main = "Squared Values", # Main title
xlab = "X", # X-axis label
ylab = "Y") # Y-axis label

In this example, I’m plotting the squared values of `x`, customizing the appearance of the plot with various graphics parameters.

Example – Customizing a Scatter Plot

# Generate random data
set.seed(123)
x <- rnorm(100)
y <- rnorm(100)

# Create a scatter plot with customized appearance
plot(x, y,
main = "Customized Scatter Plot", # Main title
xlab = "X-axis", ylab = "Y-axis", # Axis labels
col = "darkgreen", # Point color
pch = 20, # Point type (solid circle)
cex = 1.5, # Point size
xlim = c(-3, 3), ylim = c(-3, 3), # Set limits for x and y axes
bg = "lightblue", # Background color for points
las = 1) # Orientation of axis labels (horizontal)

Let me explain the above code.

• `set.seed(123)`: Sets a seed for reproducibility.
• `rnorm(100)`: Generates 100 random numbers from a normal distribution.
• `plot(x, y, …)`: Creates a scatter plot with `x` and `y` data.
• `main`, `xlab`, `ylab`: Set the main title and axis labels.
• `col`: Sets the color of points to dark green.
• `pch`: Sets the point type to a solid circle.
• `cex`: Adjusts the size of points to 1.5 times their default size.
• `xlim`, `ylim`: Sets the limits for the x and y axes.
• `bg`: Sets the background color for points to light blue.
• `las`: Sets the orientation of axis labels to horizontal.

With these examples, as a beginner you understood that graphics devices and parameters in R is crucial for effective data visualization.

You can easily customize where plots are rendered and customizing their appearance, you can create informative and visually appealing visualizations using R.