Plotting for r is a major selling point o fthe whole platform. And thanks to projects like shiny it is not only for your own computer but can even be used to backend webapps.
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")
- The ggplot2 reference is thorough but utterly inscrutable without knowing the philosophy of the thing.
- Fancy new features are best discovered via the extension gallery.
- The cheat sheet has useful 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.
- ggvis is the latest 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.
Other plotting systems
R Graphical Manual visualization of all CRAN R package example plots, and is searchable by topic.