Plotting in R

1 native

Basic r plotting via the plot command is functional.

2 ggplot2

More tidyverse! Probably the favourite plotting system for R these days.

Kieran Healy advises the following set up for visualisation in the tidyverse style :

my_packages <- c("tidyverse", "broom", "coefplot", "cowplot",
    "gapminder", "GGally", "ggrepel", "ggridges",X "gridExtra",
    "interplot", "margins", "maps", "mapproj", "mapdata",
    "MASS", "quantreg", "scales", "survey", "srvyr",
    "viridis", "viridisLite", "devtools")

install.packages(my_packages,
    repos = "http://cran.rstudio.com")

• yonicd/ggedit: Interactively edit ggplot layer aesthetics and theme definitions.

  ggedit is a package that helps users bridge the gap between making a plot and getting all of those pesky plot aesthetics just right, all while keeping everything portable for further research and collaboration.

  ggedit is powered by a Shiny gadget where the user inputs a ggplot plot object or a list of ggplot objects. You can run ggedit directly from the console or from the Addin menu within RStudio.

  See The ggedit gitbook

• The ggplot2 reference is thorough but inscrutable without knowing the philosophy of the thing.

• Fancy features are best discovered via the extension gallery.

• The cheat sheet has graphical references, which is the appropriate way to consider this thing.

• Max Woolf’s simple ggplot tutorial

• The ggplot book is available free if you build it yourself

• The ggplot chapter of R for data science.

• Want arbitrary lines and stuff to appear in the legends? E.g. a mean line or multiple model fits.

• diagrammer emits your graphs as javascript widgets. V Web2.0 wow.

• ggvis is a planned next iteration of the Hadley Wickham’s ggplot family, AFAICT, but currently on hiatus

• animating is sort of possible using ggplot2 but it is not fun.

• gggedit is an interactive rstudio extension for dynamically adjusting plots

• Plotly graphing library for ggplot2 in ggplot2

  With ggplotly() by Plotly, you can convert your ggplot2 figures into interactive ones powered by plotly.js.

3 plotly

Browser-backed option Plotly has R support. See plotly.

4 Echarts

Create Interactive Graphs with Echarts JavaScript Version 5 • echarts4r.

5 Other plotting systems

R Graphical Manual visualization of all CRAN R package example plots, and is searchable by topic.

• nx10/httpgd: Asynchronous http server graphics device for R.

6 Other image wrangling

meme produces image macros from inside R. hexSticker does hexStickers.

7 Spatial data and maps and such

See maps in R.

8 cairo errors

Do you get an error like this when plotting SVGs?

unable to load shared object '/usr/local/Cellar/r/3.5.0_1/lib/R/library/grDevices/libs//cairo.so':
dlopen(/usr/local/Cellar/r/3.5.0_1/lib/R/library/grDevices/libs//cairo.so, 6): image not found

Or this?

Error in dev.control(displaylist = if (record) "enable" else "inhibit") :
  dev.control() called without an open graphics device
Calls: local ... call_block -> block_exec -> chunk_device -> dev.control
In addition: Warning messages:
1: In (function (filename = if (onefile) "Rplots.svg" else "Rplot%03d.svg",  :
  unable to load shared object 'SOMETHING/r/3.6.2/lib/R/library/grDevices/libs//cairo.so':
  dlopen(SOMETHING/r/3.6.2/lib/R/library/grDevices/libs//cairo.so, 6): image not found

Cairo is finicky.

One problem can be that homebrew R doesn’t support the cairo library. Yihui recommends:

brew install --cask r

or you can install svglite as an alternative plotting backend

install.packages("svglite")

and use the device option dev = "svglite". Mind you, svglite can have its own problems. I needed to do the following, on one Kubuntu workstation,

install.packages("devtools")
devtools::install_github('davidgohel/gdtools')
devtools::install_github("r-lib/svglite")

On macOS, XQuartz helps

brew install --cask xquartz

Although I suspect it is a bloated security risk so avoid if poss; XQuartz is a community maintained fork of a notoriously insecure piece of software that runs as root, so it would be a an embarrassing way to get p3ned.

For anaconda R, this seems to help:

conda update conda
conda update --all
conda install -c r r-essentials=1.7.0

Generally anaconda R is a nightmare though, and all sorts of things fail to compile for me, so I do not recommend it.