6  Saving Plots in R

6.1 Introduction

The worst mistake is relying on “Export” buttons or right-clicking to save plots. This chapter teaches you the proper, reproducible way to save plots in R using ggsave() and graphics devices, with complete control over dimensions, resolution, and format.

Learning Objectives

By the end of this chapter, you will:

  • Understand the graphics device system in R
  • Know how to use ggsave() properly with all parameters
  • Learn when to use cairo_pdf for better font handling
  • Be able to save both PDF and PNG versions automatically
  • Know how to batch-save multiple plots efficiently
  • Understand the difference between exporting manually vs. scripted saving

6.2 The Graphics Device System

Every plot needs a “device”

Device = where R sends the graphics output (device = “the printer”)

  • Screen (RStudio viewer)
  • PDF file
  • SVG file
  • PNG file
  • JPEG file
  • etc.

6.3 Old Way: Manual Device Management

pdf("myplot.pdf", width = 7, height = 5)
  plot(x, y)
dev.off()  # CRITICAL! Must close device
dev.off() Works with ALL R Plots

The dev.off() approach works for:

  • Base R plots (plot(), hist(), barplot(), etc.)
  • ggplot2 plots
  • Any R graphics output

It’s universal - not limited to any specific plotting system!

Problems with manual device management:

  • Easy to forget dev.off()
  • Verbose
  • Not intuitive
  • Must manage device lifecycle manually

6.4 Modern Way: ggsave()

For ggplot2 objects (recommended!)

p <- ggplot(mtcars, aes(wt, mpg)) + geom_point()

# Saves last plot by default
ggsave("myplot.pdf")

# Better: explicit plot object
ggsave("myplot.pdf", plot = p, width = 6, height = 4)

No dev.off() needed! ✨

Full Control

ggsave(
  filename = "figure1.pdf",
  plot = my_plot,
  width = 7,
  height = 5,
  units = "in",     # or "cm", "mm"
  dpi = 300,        # for raster formats
  device = "pdf"    # or "png", "svg", "tiff"
)

6.5 Batch Saving: Result

# View the resulting tibble
plot_data
# A tibble: 3 × 3
  Species    data               plot
  <fct>      <list>             <list>
1 setosa     <tibble [50 × 4]>  <gg>
2 versicolor <tibble [50 × 4]>  <gg>
3 virginica  <tibble [50 × 4]>  <gg>

Each row contains:

  • Species name
  • Nested data for that species
  • A ggplot object with regression

Example: Setosa species plot

6.6 File Organization

library(glue)

# Good practice: separate directory
fig_dir <- "figures"
dir.create(fig_dir, showWarnings = FALSE)

ggsave(glue("{fig_dir}/figure1.pdf"), p1, width = 7, height = 5)
ggsave(glue("{fig_dir}/figure1.png"), p1, width = 7, height = 5, dpi = 300)

# Save both vector and raster versions!

6.7 Using magick for Conversion

library(magick)

# Convert PDF to 300 DPI PNG
img <- image_read_pdf("plot.pdf", density = 300)
image_write(img, "plot.png", format = "png", quality = 100)

# With better antialiasing (remove alpha channel)
img <- image_read_pdf("plot.pdf", density = 300)
img <- image_background(img, "white")  # Remove alpha
image_write(img, "plot.png", format = "png", quality = 100)

# Batch convert all PDFs in directory
pdf_files <- list.files(pattern = "\\.pdf$")
for (file in pdf_files) {
  img <- image_read_pdf(file, density = 300)
  img <- image_background(img, "white")
  out_file <- sub("\\.pdf$", ".png", file)
  image_write(img, out_file, format = "png", quality = 100)
}

6.8 Batch Saving Multiple Plots

Make a plotting function

make_species_plot <- function(data, species) {
  ggplot(data, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_point(size = 2, color = "steelblue") +
    geom_smooth(method = "lm", se = TRUE, color = "darkred", formula = y ~ x) +
    labs(title = glue("Iris {species}"), x = "Sepal Length (cm)", y = "Sepal Width (cm)") +
    theme_classic(base_size = 12)
}


Nest data per Species

# Nest data by Species and apply plotting function
plot_data <- iris %>%
  nest(data = -Species) %>%
  mutate(plot = map2(data, Species, make_species_plot))


Write out to separate file per Species

# Save all plots using walk2
walk2(plot_data$plot, plot_data$Species, ~ggsave(
  filename = glue("{fig_dir}/iris_{..2}.pdf"),
  plot = ..1,
  width = 6, height = 5
))
# A tibble: 3 × 3
  Species    data              plot      
  <fct>      <list>            <list>    
1 setosa     <tibble [50 × 4]> <ggplt2::>
2 versicolor <tibble [50 × 4]> <ggplt2::>
3 virginica  <tibble [50 × 4]> <ggplt2::>
head(plot_data$data[[1]])
# A tibble: 6 × 4
  Sepal.Length Sepal.Width Petal.Length Petal.Width
         <dbl>       <dbl>        <dbl>       <dbl>
1          5.1         3.5          1.4         0.2
2          4.9         3            1.4         0.2
3          4.7         3.2          1.3         0.2
4          4.6         3.1          1.5         0.2
5          5           3.6          1.4         0.2
6          5.4         3.9          1.7         0.4


plot_data$plot[[1]]

6.9 Recommendations

Best Practices
  1. Always use ggsave() for ggplot2 (not manual devices)
  2. Always specify width, height, units and DPI (for raster output)
  3. Increase DPI from the default for all raster formats set ≥300
  4. Use cairo_pdf for PDF output
  5. Save both PDF and PNG versions
  6. Organize figures in dedicated directory

6.10 Summary

Key Takeaways

  1. Use ggsave() for ggplot2 - never use manual devices or Export button

  2. Always specify dimensions explicitly:

    ggsave("plot.pdf", p, width = 7, height = 5, units = "in")

  3. Key parameters:

    • width, height, units - control size
    • dpi - resolution for raster (300+ for print)
    • device - format override (e.g., cairo_pdf)

  4. Use cairo_pdf for PDFs - better Unicode and font support

  5. Save dual formats - PDF for publication, PNG for presentations/emails

  6. Batch saving workflow:

    • Create plotting function
    • Use walk() or loops to save multiple plots
    • Consistent naming scheme

  7. Reproducibility - scripted saving ensures consistent output

  8. Organize output - dedicated figures/ directory with meaningful names

6.11 Exercises

Try It Yourself

  1. Create a plot and save it using ggsave() with explicit parameters:

    p <- ggplot(mtcars, aes(mpg, hp)) + geom_point()
ggsave("my_plot.pdf", p, width = 7, height = 5, device = cairo_pdf)
ggsave("my_plot.png", p, width = 7, height = 5, dpi = 300)

  2. Create a function that saves both PDF and PNG:

    save_dual <- function(filename, plot, ...) {
  ggsave(paste0(filename, ".pdf"), plot, device = cairo_pdf, ...)
  ggsave(paste0(filename, ".png"), plot, dpi = 300, ...)
}

  3. Use purrr::walk() to batch-save 5 different plots

  4. Compare file sizes between 72 DPI and 300 DPI PNG

6.12 Further Reading