Plotting in R

native

Basic r plotting via the plot command is functional.

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.

plotly

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

Echarts

Create Interactive Graphs with Echarts JavaScript Version 5 • echarts4r.

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.

Other image wrangling

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

Spatial data and maps and such

See maps in R.

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.

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")

Or if you are using 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.