It is not always appropriate or sufficient to make figures inside a dynamic report, such as an R Markdown document. In a real world analysis, you will want to write key figures to file for downstream use in a variety of settings.
During developement, you will want the immediate feedback from seeing your figures appear in a screen device, such as the RStudio Plots pane. Once you're satisfied, make sure you have saved in an R script all of the commands to produce the figure. You want everything, nachos to cheesecake: data import, any manipulation that necessary, then plotting.
Now what? How to preserve the figure in a file?
Do not succumb to the temptation of a mouse-based process. If might feel great at the time, but you will regret it. This establishes no link between the source code and the figure product. So when -- not if -- you need to remake the figure with a different color scheme or aspect ratio or graphics device, you will struggle to dig up the proper source code. Use one of the methods below to avoid this predicament.
Edit your source code in the following way: Precede the figure-making code by opening a graphics device and follow it with a command that closes the device. Here's an example:
pdf("testFigure_method1.pdf") # starts writing a PDF to file
plot(1:10) # makes the actual plot
dev.off() # closes the PDF file## pdf
## 2You will see there's now a new file in the working directory:
list.files(pattern = "^testFigure*")## [1] "testFigure_method1.pdf"You can view the file whatever way is appropriate to your OS. It's a silly figure but we've shown the process. Don't be surprised when you don't see any figure appear in your screen device. While you're sending graphics output to, e.g., the pdf() device, you'll be "flying blind", which is why it's important to work out the graphics commands in advance.
Here's a handy short cut for writing a figure to file:
plot(1:10) # makes the actual plot
dev.print(pdf, # copies the plot to a the PDF file
"testFigure_method2.pdf") ## pdf
## 2You will see there's now another new file in the working directory:
list.files(pattern = "^testFigure*")## [1] "testFigure_method1.pdf" "testFigure_method2.pdf"Again, you can view the file, see the silly figure, but appreciate this process will work for real figures in the future. The appeal of this method is that you will literally copy the figure in front of your eyeballs to file, which is pleasingly immediate. There's also less code to repeatedly (de-)comment as you run and re-run the script during development.
Why is this method improper? Various aspects of a figure -- such as font size -- are determined by the target graphics device and its physical size. Therefore, it is best practice to open your desired graphics device explicitly, using any necessary arguments to control height, width, fonts, etc. Make your plot. And close the device. But for lots of everyday plots the dev.print() method works just fine.
ggplot2 offers ggsave()To be written.
If you are using ggplot2, you should look into the ggsave() function.
If you follow the practice of always saving R scripts (not your workspace) and saving figures to file with code (not mouse clicks), you'll be glad. Let's say you need to remake testFigure_method2.pdf or you want to modify the code for another project. If your figure has a descriptive name it will presumably be at least somewhat unique. Search your computer for files containing the text string "testFigure_method2.pdf". You may be able to narrow the search to files ending in .R or .Rmd. You should quickly zero in on the R script containing the code that created the figure in question and you are ready to rerun or reuse.
Read the R help for Devices to learn about more graphics devices and which are available on your system (obviously requires you read your local help). pdf() is a good default: the files are easy to view and it's a vector format, so they resize gracefully. For insertion into Microsoft Word or PowerPoint, you may want to consider png(). For embedding into a web page, consider png() or svg(). Here are two good posts from the Revolutions Analytics blog with tips for saving figures to file:
It is very important to understand the difference between vector graphics and raster. PDF, postscript, and SVG are vector; PNG, JPEG, BMP, and GIF are raster. Vector graphics resize much more gracefully but raster graphics are easier to insert in Microsoft Office documents and web pages.
If you call up the help file for dev.off() and/or dev.print(), you can learn about many other functions for controlling graphics devices.
Let's delete the files we've created.
file.remove(list.files(pattern = "^testFigure*"))## [1] TRUE TRUE