This virtual event involves some slide presentations but is mainly a hands on interactive data exploration.
Participants will be executing R
code (will be provided) and exploring the data and interactive tools on their own machine during the course.
This means that, for the course to be successful, each participant will need to ensure that the setup of their machine meets certain requirements before the course begins.
Nevertheless, it would be a good idea to set your environment up a day or two before the course. If you haven’t you might not be able to participate.
the mouse/trackpad must have
if possible have two (or more!) display screens for the virtual event:
the bigger these screens are, the better.
(Alternatively, in modern operating systems (viz., Linux, Mac OSX, Windows 10) you can always swap between virtual screens (or desktops) if you have only the one physical screen.)
You will need to make sure you have up to date software installed for each of the following (blue links lead to further instructions below).
A recent release of R with tcltk
installed. Check R installation instructions.
A relatively recent release of RStudio. Note that this must be the desktop version, not the server version (which your company might force you to use and which will not work with loon
). Check RStudio installation instructions
Specific R packages
Principally loon
and loon.ggplot
The principal packages that the course will be using are loon
and those associated with loon
. These are available for installation from CRAN
.
Other CRAN
packages will be accessed either for data or for some statistical functionality. A few will need to be installed from bioconductor
.
loon
related packagesThese packages (loon
and others) have been bundled together in the suite package diveR (direct interactive visual exploration in R) which is now available on CRAN
install.packages("diveR")
Alternatively, for this course, you can just install loon
and loon.ggplot
loon
(packageVersion("loon")
>= 1.3.6) andloon.ggplot
(packageVersion("loon.ggplot")
>= 1.2.0)Again, these can be installed as usual from CRAN
using install.packages()
or via the RStudio
GUI.
install.packages(pkgs = c("loon", "loon.ggplot"))
loon
Once installed, check loon
out in R
:
library(loon)
p <- with(iris,
l_plot(x = Sepal.Length, y = Sepal.Width, color = Species))
If this creates a scatterplot and an inspector window, then loon
was correctly installed.
l_web()
In addition to the help pages in R
, the function l_web()
will pop up a website which can be explored in more detail.
library(loon)
l_web()
This will lead to the site
https://great-northern-diver.github.io/loon/
where you will find the entire reference manual, articles/vignettes on how to use loon, and videos that illustrate some of the functionality of loon
.
loon
demosDemos can be found by executing
library("loon")
demo(package = "loon")
# for example, the interactive graphics equivalent of "Hello world"
demo(l_power, package = "loon")
(Note that some demos and examples appearing in loon
documentation could require other packages to be loaded from CRAN
or from Bioconductor
)
CRAN
packagesThe following CRAN
packages will be used in the course
install.packages(c("MASS", "gridExtra", "RColorBrewer",
"tidyverse",
"maps", "sp", "rworldmap")
)
The course material will consist of slides and R
code.
NOW IS THE TIME TO DOWNLOAD THE COURSE MATERIAL: here
Please revisit this site on the morning of the course in case there are updates to this information. Such updates may need to be made to your machine to ensure a successful course session.
Good luck and have fun!