Spineplot and spinogram type

Description

Spineplot and spinogram type

Usage

type_spineplot(
  breaks = NULL,
  tol.ylab = 0.05,
  off = NULL,
  ylevels = NULL,
  col = NULL,
  xaxlabels = NULL,
  yaxlabels = NULL,
  weights = NULL
)

Arguments

breaks	if the explanatory variable is numeric, this controls how it is discretized. breaks is passed to hist and can be a list of arguments.
tol.ylab	convenience tolerance parameter for y-axis annotation. If the distance between two labels drops under this threshold, they are plotted equidistantly.
off	vertical offset between the bars (in per cent). It is fixed to 0 for spinograms and defaults to 2 for spine plots.
ylevels	a character or numeric vector specifying in which order the levels of the dependent variable should be plotted.
col	a vector of fill colors of the same length as levels(y). The default is to call gray.colors.
xaxlabels, yaxlabels	character vectors for annotation of x and y axis. Default to levels(y) and levels(x), respectively for the spine plot. For xaxlabels in the spinogram, the breaks are used.
weights	numeric. A vector of frequency weights for each observation in the data. If NULL all weights are implicitly assumed to be 1. If x is already a 2-way table, the weights are ignored.

Examples

library("tinyplot")

# "spineplot" type convenience string
tinyplot(Species ~ Sepal.Width, data = iris, type = "spineplot")

# Aside: specifying the type is redundant for this example, since tinyplot
# default's to "spineplot" if y is a factor (just like base plot).
tinyplot(Species ~ Sepal.Width, data = iris)

# Use `type_spineplot()` to pass extra arguments for customization
tinyplot(Species ~ Sepal.Width, data = iris, type = type_spineplot(breaks = 4))

p = palette.colors(3, "Pastel 1")
tinyplot(Species ~ Sepal.Width, data = iris, type = type_spineplot(breaks = 4, col = p))

rm(p)

# More idiomatic tinyplot way of drawing the previous plot: use y == by
tinyplot(
  Species ~ Sepal.Width | Species, data = iris, type = type_spineplot(breaks = 4),
  palette = "Pastel 1", legend = FALSE
)

# Grouped and faceted spineplots

ttnc = as.data.frame(Titanic)

tinyplot(
  Survived ~ Sex, facet = ~ Class, data = ttnc,
  type = type_spineplot(weights = ttnc$Freq)
)

# For grouped "by" spineplots, it's better visually to facet as well
tinyplot(
  Survived ~ Sex | Class, facet = "by", data = ttnc,
  type = type_spineplot(weights = ttnc$Freq)
)

# Fancier version. Note the smart inheritance of spacing etc.
tinyplot(
  Survived ~ Sex | Class, facet = "by", data = ttnc,
  type = type_spineplot(weights = ttnc$Freq),
  palette = "Dark 2", facet.args = list(nrow = 1), axes = "t"
)

# Note: It's possible to use "by" on its own (without faceting), but the
# overlaid result isn't great. We will likely overhaul this behaviour in a
# future version of tinyplot...
tinyplot(Survived ~ Sex | Class, data = ttnc,
  type = type_spineplot(weights = ttnc$Freq), alpha = 0.3
)