Package 'yarrr'

apa

Description

This function takes a hypothesis test object (e.g.; t.test(), cor.test(), chisq.test()) as an input, and returns a string with the test result in APA format.

Usage

apa(test.object, tails = 2, sig.digits = 2, p.lb = 0.01)

Arguments

test.object	A hypothesis test object generated by functions such as t.test(), cor.test, chisq.test()
tails	The number of tails in the test (1 or 2)
sig.digits	The number of digits results are rounded to
p.lb	The lower bound of the p-value display. If the p-value is less than p.lb, the exact value will not be displayed.

Examples

x <- rnorm(100)
y <- x + rnorm(100)
a <- sample(1:3, size = 200, prob = c(.3, .2, .5), replace = TRUE)
b <- sample(1:3, size = 200, prob = c(.3, .2, .5), replace = TRUE)

apa(t.test(x, y))
apa(cor.test(x, y))
apa(chisq.test(table(a, b)))

---

auction

Description

A dataframe containing data from 1000 ships sold at a pirate auction.

Usage

auction

Format

A data frame containing 1000 rows and 8 columns

cannons

(integer) The number of cannons on the ship

rooms

(integer) The number of rooms on the ship

age

(numeric) The age of the ship in years

condition

(integer) The condition of the ship on a scale of 1 to 10

color

(string) The color of the ship

style

(string) The style of the ship - either modern or classic

jbb

(numeric) The pre-sale predicted value of the ship according to Jack's Blue Book (JBB)

price

(numeric) The actual selling price of the ship (in gold pieces, obviously)

Source

2015 annual pirate auction in Portland Oregon

---

BeardLengths

Description

A dataframe containing the lengths of beards on 3 different pirate ships

Usage

BeardLengths

Format

A data frame containing 150 rows and 2 columns

Ship

(character) - The pirate's ship

Beard

(numeric) - The length of the pirate's beard in cm

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

capture

Description

A dataframe containing a historical record of every ship the Perilous Pigeon captured on the Bodensee in the years 2014 and 2015

Usage

capture

Format

A data frame containing 1000 rows and 10 columns

size

(integer) - The size (length) of the ship (maybe in meters?)

cannons

(integer) - The number of cannons on the ship

style

(string) - The style of the ship (either modern or classic)

warnshot

(binary) - Did the ship fire a warning shot at the Perilous Pigeon when it got close?

date

(integer) - The date of the capture (1 = January 1, 365 = December 31)

heardof

(binary) - Was the target ship recognized by the captain's first mate?

decorations

(integer) - An integer between 1 and 10 indicating how decorated the ship was. 1 means it looks totally common and shabby, 10 means it is among the finest looking ship you've ever seen!

daysfromshore

(integer) - How many days from the nearest land was the ship when it was found?

speed

(integer) - How fast was the ship going when it was caught?

treasure

(numeric) - How much treasure was found on the ship when it was captured?

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

diamonds

Description

A dataframe containing information about 150 diamonds sold at auction.

Usage

diamonds

Format

A data frame containing 300 rows and 4 columns

weight

(numeric) - The weight of the diamond

clarity

(numeric) - The clarity of the diamond

color

(numeric) - The color shading of the diamond

value

The value of the diamond

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

examscores

Description

A dataframe containing the results of 4 exams given to 100 students. Each row represents a student, each column is a score on an exam

Usage

examscores

Format

A data frame containing 100 rows and 4 columns

a

(numeric) - Score on exam a

b

(numeric) - ...exam b

c

(numeric) - ...exam c

d

(numeric) - ...exam d

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

movies

Description

A dataframe containing information about the top 5000 grossing movies of all time.

Usage

movies

Format

A data frame containing 5000 rows and 13 columns

name

Movie name

rating

MPAA rating

genre

Movie genre

creative.type

Creative type

time

Running time in minutes

year

Year of release

production.method

Production method

sequel

Was the movie a sequel? 1 = yes, 0 = no

budget

Movie budget (in $USD millions)

revenue.all

Gross worldwide revenue in $USD millions

revenue.dom

Domestic revenue in $USD millions

revenue.int

International revenue in $USD millions

revenue.inf

Inflation adjusted worldwide revenue in $USD millions

Source

www.the-numbers.com

---

piratepal

Description

This function provides a number of color palettes

Usage

piratepal(
  palette = "all",
  trans = 0,
  mix.col = "white",
  mix.p = 0,
  plot.result = FALSE,
  length.out = NULL
)

Arguments

palette	A string defining the color palette to use (see examples). To use a random palette, use "random". To plot all palettes, use "all". To see all palette names, use "names"
trans	A number in the interval [0, 1] indicating how transparent to make the colors. A value of 0 means no transparency and a value of 1 means completely transparency.
mix.col	string. An optional string representing a color to mix all colors in the palette with.
mix.p	numeric. A number in the interval [0, 1] indicating how much to mix the palette colors with the color in mix.col
plot.result	A logical value indicating whether or not to display the colors.
length.out	An integer indicating how many colors to return. If length.out is larger than the number of colors in the palette, colors will be repeated.

Examples

# Check out the vignette for a full guide

vignette("piratepal", package = "yarrr")

# Show all palettes

piratepal(palette = "all")

# Show some palettes

piratepal(palette = "basel", trans = .5, plot.result = TRUE)


# Using a palette in a scatterplot

nemo.cols <- piratepal(palette = "nemo", trans = .5)

set.seed(100) # For reproducibility
x <- rnorm(100)
y <- x + rnorm(100)

plot(
  x = x, y = y, col = nemo.cols,
  pch = 16,
  cex = runif(100, min = 0, max = 2),
  main = "piratepal('nemo', trans = .5)"
)

---

pirateplot

Description

The pirateplot function creates an RDI (Raw data, Descriptive and Inferential statistic) plot showing the relationship between 1 to 3 categorical independent variables and 1 continuous dependent variable.

Usage

pirateplot(
  formula = NULL,
  data = NULL,
  plot = TRUE,
  avg.line.fun = mean,
  pal = "basel",
  pointpars = NULL,
  mix.col = "white",
  mix.p = 0,
  back.col = NULL,
  point.cex = NULL,
  point.pch = NULL,
  point.lwd = 1,
  jitter.val = 0.03,
  theme = 1,
  beside = TRUE,
  bean.b.o = NULL,
  bean.f.o = NULL,
  point.o = NULL,
  bar.f.o = NULL,
  bar.b.o = NULL,
  inf.f.o = NULL,
  inf.b.o = NULL,
  avg.line.o = NULL,
  gl.col = NULL,
  point.col = NULL,
  point.bg = NULL,
  bar.f.col = NULL,
  bean.b.col = NULL,
  bean.f.col = NULL,
  inf.f.col = NULL,
  inf.b.col = NULL,
  avg.line.col = NULL,
  bar.b.col = NULL,
  quant.col = NULL,
  avg.line.lwd = 4,
  bean.lwd = 1,
  bean.lty = 1,
  inf.lwd = NULL,
  bar.lwd = 1,
  at = NULL,
  bw = "nrd0",
  adjust = 1,
  add = FALSE,
  sortx = "alphabetical",
  decreasing = FALSE,
  cex.lab = 1,
  cex.axis = 1,
  cex.names = 1,
  force.layout = FALSE,
  quant = NULL,
  quant.length = NULL,
  quant.lwd = NULL,
  bty = "o",
  cap.beans = TRUE,
  family = NULL,
  inf.method = "hdi",
  inf.within = NULL,
  inf.p = NULL,
  hdi.iter = 1000,
  inf.disp = NULL,
  cut.min = NULL,
  cut.max = NULL,
  width.min = 0.3,
  width.max = NA,
  ylim = NULL,
  xlim = NULL,
  xlab = NULL,
  ylab = NULL,
  main = NULL,
  yaxt = NULL,
  xaxt = NULL,
  yaxt.y = NULL,
  gl.y = NULL,
  gl.lwd = NULL,
  gl.lty = NULL,
  bar.b.lwd = NULL,
  line.fun = NULL,
  line.o = NULL,
  inf.o = NULL,
  bean.o = NULL,
  inf.col = NULL,
  theme.o = NULL,
  bar.o = NULL,
  inf = NULL,
  hdi.o = NULL,
  inf.type = NULL,
  inf.band = NULL,
  gl = NULL
)

Arguments

formula	formula. A formula in the form y ~ x1 + x2 + x3 indicating the vertical response variable (y) and up to three independent variables
data	Either a dataframe containing the variables specified in formula, a list of numeric vectors, or a numeric dataframe / matrix.
plot	logical. If TRUE (the default), thent the pirateplot is produced. If FALSE, the data summaries created in the plot are returned as a list.
avg.line.fun	function. A function that determines how average lines and bar heights are determined (default is mean).
pal	string. The color palette of the plot. Can be a single color, a vector of colors, or the name of a palette in the piratepal() function (e.g.; "basel", "google", "southpark"). To see all the palettes, run piratepal(palette = "all", action = "show")
pointpars	dataframe A dataframe containing optional additional plotting parameters for points. The dataframe should have thee same number of rows as data, and have column names in the set col, bg, pch, labels.
mix.col, mix.p	Optional color mixing arguments to be passed to piratepal. See ?piratepal for examples.
back.col	string. Color of the plotting background.
point.cex, point.pch, point.lwd	numeric. The size, pch type, and line width of raw data points.
jitter.val	numeric. Amount of jitter added to points horizontally. Defaults to 0.05.
theme	integer. An integer in the set 0, 1, 2 specifying a theme (that is, new default values for opacities and colors). theme = 0 turns off all opacities which can then be individually specified individually.
beside	logical. If FALSE, then the second independent variable is spread over separate plots, rather than separated in the samep lot.
bar.f.o, point.o, inf.f.o, inf.b.o, avg.line.o, bean.b.o, bean.f.o, bar.b.o	numeric. A number between 0 and 1 indicating how opaque to make the bars, points, inference band, average line, and beans respectively. These values override whatever is in the specified theme
point.col, bar.f.col, bean.b.col, bean.f.col, inf.f.col, inf.b.col, avg.line.col, bar.b.col, quant.col, point.bg	string. Vectors of colors specifying the colors of the plotting elements. This will override values in the palette. f stands for filling, b stands for border.
bean.lwd, bean.lty, inf.lwd, avg.line.lwd, bar.lwd	numeric. Vectors of numbers customizing the look of beans and lines.
at	integer. Locations of the beans. Especially helpful when adding beans to an existing plot with add = TRUE
bw, adjust	Arguments passed to density calculations for beans (see ?density)
add	logical. Should the pirateplot elements be added to an existing plotting space?
sortx	string. How to sort the x values. Can be "sequential" (as they are found in the original dataframe), "alphabetical", or a string in the set ("mean", "median", "min", "max") indicating a function
decreasing	logical. If sortx is a named function, should values be sorted in decreasing order?
cex.lab, cex.axis, cex.names	Size of the labels, axes, and bean names.
force.layout	logical. If TRUE, then all internal plotting formatting functions (e.g.; mfrow, mar) are turned off.
quant	numeric. Adds horizontal lines representing custom quantiles.
quant.length, quant.lwd	numeric. Specifies line lengths/widths of quant.
bty, xlim, ylim, xlab, ylab, main, yaxt, xaxt	General plotting arguments
cap.beans	logical. Should maximum and minimum values of the bean densities be capped at the limits found in the data? Default is FALSE.
family	a font family (Not currently in use)
inf.method	string. A string indicating what types of inference bands to calculate. "ci" means frequentist confidence intervals, "hdi" means Bayesian Highest Density Intervals (HDI), "iqr" means interquartile range, "sd" means standard deviation, "se" means standard error, "withinci" means frequentist confidence intervals in a within design (Morey, 2008).
inf.within	string. The variable which serves as an ID variable in a within design.
inf.p	numeric. A number adjusting how inference ranges are calculated. for "ci" and "hdi", a number between 0 and 1 indicating the level of confidence (default is .95). For "sd" and "se", the number of standard deviations / standard errors added to or subtracted from the mean (default is 1).
hdi.iter	integer. Number of iterations to run when calculating the HDI. Larger values lead to better estimates, but can be more time consuming.
inf.disp	string. How should inference ranges be displayed? "line" creates a classic vertical line, "rect" creates a rectangle, "bean" forms the inference around the bean.
cut.min, cut.max	numeric. Optional minimum and maximum values of the beans.
width.min, width.max	numeric. The minimum/maximum width of the beans.
yaxt.y	numeric. Locations of tick marks on the y-axis
gl.y	numeric. Locations of the horizontal grid lines
gl.lwd, gl.lty, gl.col	Customization for grid lines. Can be entered as vectors for alternating gridline types
bar.b.lwd, line.fun, inf.o, bean.o, inf.col, theme.o, inf, inf.type, inf.band, bar.o, line.o, hdi.o, gl	depricated arguments

Examples

# Default pirateplot of weight by Time
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight
)

# Same but in grayscale
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  pal = "gray"
)


# Now using theme 2
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  main = "Chicken weight by time",
  theme = 2
) # theme 2

# theme 3
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  main = "Chicken weight by time",
  theme = 3
) # theme 3

# theme 4
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  main = "Chicken weight by time",
  theme = 4
) # theme 4

# Start with theme 2, but then customise!
pirateplot(
  formula = weight ~ Time,
  data = ChickWeight,
  theme = 2, # theme 2
  pal = "xmen", # xmen palette
  main = "Chicken weights by Time",
  point.o = .4, # Add points
  point.col = "black",
  point.bg = "white",
  point.pch = 21,
  bean.f.o = .2, # Turn down bean filling
  inf.f.o = .8, # Turn up inf filling
  gl.col = "gray", # gridlines
  gl.lwd = c(.5, 0)
) # turn off minor grid lines

# 2 IVs
pirateplot(
  formula = len ~ dose + supp,
  data = ToothGrowth,
  main = "Guinea pig tooth length by supplement",
  point.pch = 16, # Point specifications...
  point.col = "black",
  point.o = .7,
  inf.f.o = .9, # inference band opacity
  gl.col = "gray"
)


# Build everything from scratch with theme 0
#  And use 3 IVs
pirateplot(
  formula = height ~ headband + eyepatch + sex,
  data = pirates,
  pal = gray(.1), # Dark gray palette
  theme = 0, # Start from scratch
  inf.f.o = .7, # Band opacity
  inf.f.col = piratepal("basel"), # Add color to bands
  point.o = .1, # Point opacity
  avg.line.o = .8, # Average line opacity
  gl.col = gray(.6), # Gridline specifications
  gl.lty = 1,
  gl.lwd = c(.5, 0)
)

# See the vignette for more details
vignette("pirateplot", package = "yarrr")

---

pirates

Description

A dataset containing the results of a survey of 1,000 pirates.

Usage

pirates

Format

A data frame containing 1,000 rows and 14 columns

id

An integer giving the pirate's id number

sex

A string with the pirate's self reported sex

age

An integer giving the age of the pirate in years

height

Height in cm

weight

Weight in kg

headband

A binary variable indicating whether the pirate wears a headband

college

A string indicating the college the pirate went to. JSSFP stands for Jack Sparro's School of Fashion and Piratery, while CCCC stands for Captain Chunk's Cannon Crew

tattoos

An integer indicating the number of tattoos the pirate has

tchests

An integer indicating the number of treasure chests found by the pirate

parrots

An integer indicating the number of parrots owned by the pirate in his/her lifetime

favorite.pirate

A string indicating The pirate's favorite pirate

sword.type

A string indicating the type of sword the pirate uses

eyepatch

An integer indicating the number of eyepatches worn by the pirate

sword.time

A number indicating how long it takes (in seconds) for the pirate to draw his/her sword. Smaller times are better!

beard.length

A number indicating length of the pirate's beard in centimeters

fav.pixar

A string indicating Pirate's favorite pixar movie

grogg

How many mugs of grogg the pirate drinks a day on average.

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

pirateserrors

Description

A dataset containing the results of a survey of 1,000 pirates. This dataset is identical to the pirates dataset - except that it has many errors!

Usage

pirateserrors

Format

A data frame containing 1,000 rows and 14 columns

id

An integer giving the pirate's id number

sex

A string with the pirate's self reported sex

headband

A binary variable indicating whether the pirate wears a headband

age

An integer giving the age of the pirate in years

college

A string indicating the college the pirate went to. JSSFP stands for Jack Sparro's School of Fashion and Piratery, while CCCC stands for Captain Chunk's Cannon Crew

tattoos

An integer indicating the number of tattoos the pirate has

tchests

An integer indicating the number of treasure chests found by the pirate

parrots

An integer indicating the number of parrots owned by the pirate in his/her lifetime

favorite.pirate

A string indicating The pirate's favorite pirate

sword.type

A string indicating the type of sword the pirate uses

sword.time

A number indicating how long it takes (in seconds) for the pirate to draw his/her sword. Smaller times are better!

eyepatch

An integer indicating the number of eyepatches worn by the pirate

beard.length

A number indicating length of the pirate's beard in centimeters

fav.pixar

A string indicating Pirate's favorite pixar movie

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

pircharter

Description

A dataframe containing travel times of chartered ships from three pirate companies to three different destinations.

Usage

pircharter

Format

A data frame containing 1000 rows and 10 columns

company

(string) - The charter company: JoRo = Jolly Roger, BmcB = Boaty McBoat, MiPa = Millenium Parrot

destination

(string) - The destination of the charter

time

(numeric) - The travel time of the ship in hours

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

poopdeck

Description

A dataframe containing the amount of time it took to clean both pirate and shark poop from the poop deck using one of three different cleaning solutions

Usage

poopdeck

Format

A data frame containing 300 rows and 4 columns

day

(factor) - The day that the poop deck was cleaned (1 through 10000)

cleaner

(string) - The cleaning solution used

type

(string) - The type of poop being cleaned

time

(numeric) - The amount of time (in minutes) the cleaning took.

Source

2015 annual international pirate meeting at the Bodensee in Konstanz, Germany

---

recodev

Description

This function takes a vector original.vector, and converts all values in a vector old.values to the values in a new vector new.values.

Usage

recodev(original.vector, old.values, new.values, others = NULL)

Arguments

original.vector	A vector you want to recode
old.values	A vector of length M.
new.values	A vector of length M.
others	An optional value indicating what to convert all values in original.vector that are not found in old.values.

Examples

x <- c("y", "y", "XSF", "y", "0", "X", "0", "0", "y", "n", "0", "1", "1")
recodev(
  original.vector = x,
  old.values = c("y", "1", "n", "0"),
  new.values = c(1, 1, 0, 0)
)


x <- c("y", "y", "XSF", "y", "0", "X", "0", "0", "y", "n", "0", "1", "1")
recodev(
  original.vector = x,
  old.values = c("y", "1", "n", "0"),
  new.values = c(1, 1, 0, 0),
  others = NA
)

---

transparent function

Description

This function takes a standard color as an argument and returns a transparent version of that color

Usage

transparent(orig.col = "red", trans.val = 1, maxColorValue = 255)

Arguments

orig.col	The original color to be made transparent. Can be specified as a string or a vector of rgb values
trans.val	A number in the interval [0, 1] indicating how transparent to make the color.
maxColorValue	The maximum color value (only used when orig.col is an rgb vector)

Examples

# Diagram of some examples
plot(1,
  ylim = c(0, 1), xlim = c(0, 12), bty = "n",
  xaxt = "n", yaxt = "n", ylab = "", xlab = "", type = "na"
)


text(6, .9, "transparent('red', trans.val = x)")
points(
  x = 1:11, y = rep(.8, 11), pch = 16,
  col = transparent("red", seq(0, 1, .1)), cex = 2
)
text(x = 1:11, y = rep(.85, 11), seq(0, 1, .1))

text(6, .7, "transparent('red', trans.val = x)")
points(
  x = 1:11, y = rep(.6, 11), pch = 16,
  col = transparent("blue", seq(0, 1, .1)), cex = 2
)
text(x = 1:11, y = rep(.65, 11), seq(0, 1, .1))

text(6, .5, "transparent('forestgreen', trans.val = x)")
points(
  x = 1:11, y = rep(.4, 11), pch = 16,
  col = transparent("forestgreen", seq(0, 1, .1)), cex = 2
)
text(x = 1:11, y = rep(.45, 11), seq(0, 1, .1))

text(6, .3, "transparent('orchid1', trans.val = x)")
points(
  x = 1:11, y = rep(.2, 11), pch = 16,
  col = transparent("orchid1", seq(0, 1, .1)), cex = 2
)
text(x = 1:11, y = rep(.25, 11), seq(0, 1, .1))


# Scatterplot with transparent colors

a.x <- rnorm(100, mean = 0, sd = 1)
a.y <- a.x + rnorm(100, mean = 0, sd = 1)

par(mfrow = c(3, 3))

for (trans.val.i in seq(0, .1, length.out = 9)) {
  plot(a.x, a.y,
    pch = 16, col = transparent("blue", trans.val.i), cex = 1.5,
    xlim = c(-5, 5), ylim = c(-5, 5), xlab = "x", ylab = "y",
    main = paste("trans.val = ", round(trans.val.i, 2), sep = "")
  )
}

---

Opens the HTML manual for the yarrr package

Description

Opens the HTML manual for the yarrr package

Usage

yarrr.guide()

---