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The yarrr
package contains a mixture of data, functions
and tutorials supporting the e-book “YaRrr! The Pirate’s Guide to R” (https://bookdown.org/ndphillips/YaRrr/).
To install the (stable) version from CRAN, run the following code
install.packages("yarrr") # install yarrr
library("yarrr") # load yarrr
yarrr.guide() # run main package guide
To install the latest developer version from GitHub, run the following code
# install.packages("devtools") # install devtools if needed
::install_github("ndphillips/yarrr", build_vignettes = TRUE) devtools
library(yarrr)
#> Warning: package 'jpeg' was built under R version 4.3.3
Once you have installed the package, you can run the main package guide with the following code:
yarrr.guide() # run main package guide
Here are the most important parts of the package:
# Create a Pirate Plot using theme 1
pirateplot(
formula = weight ~ Time,
data = ChickWeight,
theme = 1,
main = "Pirateplot using theme = 1"
)
The pirateplot
function creates a pirateplot, a
transparent (both literally and figuratively) plot for displaying
continuous data as a function of 1, 2, or 3 discrete variables. Unlike
traditional plots, like barplots and boxplots, the pirateplot shows both
raw data (jittered points), descriptive statistics (line and/or bar),
and inferential statistics (95% Bayesian Highest Density Intervals or
Confidence Intervals), in one plot. While the default plot shows all
these elements, the user can easily customize the transparency of each
element using additional arguments.
piratepal()
is a function that returns color palettes.
See ?piratepal
for more details
To see all of the palettes, run piratepal("all")
piratepal(palette = "all")
Once you find a palette you’d like to use, you can return the colors
as a vector by specifying the name of the palette in the
palette
argument. Here is the Basel palette
piratepal(
palette = "basel",
trans = .5,
plot.result = T
)
Let’s use the basel palette to draw the house from the Pixar film Up
# Set up balloons
<- piratepal("basel", trans = .2)
balloon.colors <- rnorm(500, 0)
balloon.x <- rnorm(500, 4, 1)
balloon.y
par(mar = rep(.1, 4))
plot(1,
xlim = c(-15, 7), ylim = c(-15, 7),
xlab = "", ylab = "", type = "n",
xaxt = "n", yaxt = "n", bty = "n"
)
# skyline
<- runif(200, -15, 7)
start.x <- sort(runif(200, -15, -12), decreasing = T)
start.y <- runif(200, 2, 4)
heights <- runif(200, .25, 1.5)
widths
rect(start.x, start.y, start.x + widths, start.y + heights,
col = "white", border = gray(.4)
)
# house
rect(-2, -6, 2, -2)
polygon(
c(-2, 0, 2),
c(-2, 0, -2)
)rect(-.5, -6, .5, -4)
points(.3, -5)
# strings
<- rnorm(500, 0, .2)
line.start.x <- -1 + rnorm(500, 0, .1)
line.start.y segments(line.start.x,
line.start.y,
balloon.x, balloon.y,lty = 1, col = gray(.5, .1), lwd = .2
)
# balloons
points(balloon.x, balloon.y,
pch = 21,
bg = balloon.colors,
col = gray(.9), cex = rnorm(100, 2, .3)
)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.