Package 'ggmosaic2'

Template for a double decker plot. A double decker plot is composed of a sequence of spines in the same direction, with the final spine in the opposite direction.

Description

Template for a double decker plot. A double decker plot is composed of a sequence of spines in the same direction, with the final spine in the opposite direction.

Usage

ddecker(direction = "h")

Arguments

direction

direction of first split

Value

A function of one argument, the number of splits n, that returns a character vector of divider function names ("hspine"/"vspine") to apply at each split – suitable for the divider argument of geom_mosaic() and related layers.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic(divider = ddecker("v"))

---

Facet mosaic plots with panel-specific axes

Description

facet_mosaic_grid() lays panels out like ggplot2::facet_grid(), but gives every panel its own x and y position scales. Mosaic category breaks depend on the proportions calculated inside a panel, so sharing a position scale can place one panel's ticks and labels on another panel's mosaic.

Usage

facet_mosaic_grid(
  rows = NULL,
  cols = NULL,
  space = "fixed",
  shrink = TRUE,
  labeller = "label_value",
  as.table = TRUE,
  switch = NULL,
  drop = TRUE,
  margins = FALSE,
  axes = "all",
  axis.labels = "all"
)

Arguments

rows, cols	A set of variables or expressions quoted by vars() and defining faceting groups on the rows or columns dimension. The variables can be named (the names are passed to labeller). For compatibility with the classic interface, rows can also be a formula with the rows (of the tabular display) on the LHS and the columns (of the tabular display) on the RHS; the dot in the formula is used to indicate there should be no faceting on this dimension (either row or column).
space	If "fixed", the default, all panels have the same size. If "free_y" their height will be proportional to the length of the y scale; if "free_x" their width will be proportional to the length of the x scale; or if "free" both height and width will vary. This setting has no effect unless the appropriate scales also vary.
shrink	If TRUE, will shrink scales to fit output of statistics, not raw data. If FALSE, will be range of raw data before statistical summary.
labeller	A function that takes one data frame of labels and returns a list or data frame of character vectors. Each input column corresponds to one factor. Thus there will be more than one with vars(cyl, am). Each output column gets displayed as one separate line in the strip label. This function should inherit from the "labeller" S3 class for compatibility with labeller(). You can use different labeling functions for different kind of labels, for example use label_parsed() for formatting facet labels. label_value() is used by default, check it for more details and pointers to other options.
as.table	If TRUE, the default, the facets are laid out like a table with highest values at the bottom-right. If FALSE, the facets are laid out like a plot with the highest value at the top-right.
switch	By default, the labels are displayed on the top and right of the plot. If "x", the top labels will be displayed to the bottom. If "y", the right-hand side labels will be displayed to the left. Can also be set to "both".
drop	If TRUE, the default, all factor levels not used in the data will automatically be dropped. If FALSE, all factor levels will be shown, regardless of whether or not they appear in the data.
margins	Either a logical value or a character vector. Margins are additional facets which contain all the data for each of the possible values of the faceting variables. If FALSE, no additional facets are included (the default). If TRUE, margins are included for all faceting variables. If specified as a character vector, it is the names of variables for which margins are to be created.
axes	Determines which axes will be drawn. When "margins" (default), axes will be drawn at the exterior margins. "all_x" and "all_y" will draw the respective axes at the interior panels too, whereas "all" will draw all axes at all panels.
axis.labels	Determines whether to draw labels for interior axes when the axes argument is not "margins". When "all" (default), all interior axes get labels. When "margins", only the exterior axes get labels and the interior axes get none. When "all_x" or "all_y", only draws the labels at the interior axes in the x- or y-direction respectively.

Details

Panel widths and heights remain fixed. By default, axes and their labels are drawn for every panel so that each panel's category positions are visible. The panel-specific label positions are retained with theme_mosaic(); that theme intentionally hides the tick marks themselves.

Value

A Facet object that can be added to a ggplot.

Author(s)

Gavin Klorfine

Examples

facet_data <- expand.grid(
  period = factor(c("Before", "After")),
  group = factor(c("A", "B")),
  response = factor(c("No", "Yes"))
)
facet_data$n <- c(30, 10, 20, 40, 10, 35, 40, 15)

ggplot(facet_data,
       aes(weight = n, x = product(response, group), fill = response)) +
  geom_mosaic() +
  facet_mosaic_grid(cols = vars(period))

---

Flying Etiquette Survey Data

Description

Data from the results of a SurveyMonkey survey commissioned by FiveThirtyEight for the story 41 Percent of Fliers Say It’s Rude To Recline Your Airplane Seat.

Usage

fly

Format

A data frame with 1040 rows and 27 variables:

id

Respondent ID

flight_freq

How often do you travel by plane?

do_you_recline

Do you ever recline your seat when you fly?

height

How tall are you?

has_child_under_18

Do you have any children under 18?

three_seats_two_arms

n a row of three seats, who should get to use the two arm rests?

two_seats_one_arm

In a row of two seats, who should get to use the middle arm rest?

window_shade

Who should have control over the window shade?

rude_to_move_to_unsold_seat

Is it rude to move to an unsold seat on a plane?

rude_to_talk_to_neighbor

Generally speaking, is it rude to say more than a few words to the stranger sitting next to you on a plane?

six_hr_flight_leave_seat

On a six hour flight from NYC to LA, how many times is it acceptable to get up if you're not in an aisle seat?

reclining_obligation_to_behind

Under normal circumstances, does a person who reclines their seat during a flight have any obligation to the person sitting behind them?

rude_to_recline

Is it rude to recline your seat on a plane?

eliminate_reclining

Given the opportunity, would you eliminate the possibility of reclining seats on planes entirely?

rude_to_switch_seats_friends

Is it rude to ask someone to switch seats with you in order to be closer to friends?

rude_to_switch_seats_family

Is it rude to ask someone to switch seats with you in order to be closer to family?

rude_to_wake_neighbor_bathroom

Is it rude to wake a passenger up if you are trying to go to the bathroom?

rude_to_wake_neighbor_walk

Is it rude to wake a passenger up if you are trying to walk around?

rude_to_bring_baby

In general, is it rude to bring a baby on a plane?

rude_to_bring_unruly_child

In general, is it rude to knowingly bring unruly children on a plane?

use_electronics_takeoff

Have you ever used personal electronics during take off or landing in violation of a flight attendant's direction?

smoked_inflight

Have you ever smoked a cigarette in an airplane bathroom when it was against the rules?

gender

Gender

age

Age

household_income

Household Income

education

Education

region

Region

Source

https://github.com/fivethirtyeight/data/tree/master/flying-etiquette-survey

---

Mosaic plots.

Description

A mosaic plot is a convenient graphical summary of the conditional distributions in a contingency table and is composed of spines in alternating directions.

Usage

geom_mosaic(
  mapping = NULL,
  data = NULL,
  stat = "mosaic",
  position = "identity",
  na.rm = FALSE,
  divider = mosaic(),
  offset = 0.01,
  show.legend = NA,
  inherit.aes = TRUE,
  expected = NULL,
  ...
)

stat_mosaic_text(
  mapping = NULL,
  data = NULL,
  geom = "Text",
  position = "identity",
  na.rm = FALSE,
  divider = mosaic(),
  show.legend = NA,
  inherit.aes = TRUE,
  offset = 0.01,
  expected = NULL,
  ...
)

stat_mosaic(
  mapping = NULL,
  data = NULL,
  geom = "mosaic",
  position = "identity",
  na.rm = FALSE,
  divider = mosaic(),
  show.legend = NA,
  inherit.aes = TRUE,
  offset = 0.01,
  expected = NULL,
  ...
)

Arguments

mapping	Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat	The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used to override the default coupling between geoms and stats. The stat argument accepts the following: A Stat ggproto subclass, for example StatCount. A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count". For more information and other ways to specify the stat, see the layer stat documentation.
position	A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following: The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position. A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter". For more information and other ways to specify the position, see the layer position documentation.
na.rm	If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
divider	Divider function. The default divider function is mosaic() which will use spines in alternating directions. The four options for partitioning: vspine Vertical spine partition: width constant, height varies. hspine Horizontal spine partition: height constant, width varies. vbar Vertical bar partition: height constant, width varies. hbar Horizontal bar partition: width constant, height varies. When omitted, divider can be inherited from mosaic_settings().
offset	Set the fixed gap at the deepest split. Gaps increase by a factor of 1.5 toward the outermost split. When omitted, the value can be inherited from mosaic_settings().
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().
expected	Optional specification for loglinear model residual shading. Can be a formula (e.g., ~ Var1 + Var2), a character shortcut ("independence", "saturated", "conditional"), or NULL (default, no model). When omitted, the value can be inherited from mosaic_settings. An explicitly supplied layer value takes priority; in particular, expected = NULL turns off a plot-level model for that layer. When specified, Pearson residuals are calculated and automatically mapped to fill (unless fill aesthetic is explicitly set). Use with scale_fill_residual for a diverging color scale. Positive residuals receive a solid dark blue outline and negative residuals a dashed dark red outline by default. Residuals within numerical tolerance of zero receive a solid black outline. Set colour = NA to remove the outlines from both the cells and the residual legend.
...	other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = 'red' or size = 3. They may also be parameters to the paired geom/stat.
geom	The geometric object to use to display the data for this layer. When using a ⁠stat_*()⁠ function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following: A Geom ggproto subclass, for example GeomPoint. A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point". For more information and other ways to specify the geom, see the layer geom documentation.

Details

Variables mapped only to fill or alpha retain their historical role as innermost mosaic partitions, but they are not shown on the automatic product axes. Position axes label only variables explicitly mapped through x or conds. If an aesthetic variable is also included in product(), it remains eligible for an axis label.

Product variables are ordered from innermost to outermost. With the default mosaic divider, reversing two variables swaps their horizontal and vertical roles; for example, product(predictions, actual) places actual on the primary x axis.

Value

A ggplot2 layer that can be added to a plot.

Computed variables

x

location of center of the rectangle

y

location of center of the rectangle

xmin

location of bottom left corner

xmax

location of bottom right corner

ymin

location of top left corner

ymax

location of top right corner

Author(s)

Gavin Klorfine

Examples

data(titanic)

ggplot(data = titanic, aes(x = product(Class), fill = Survived)) +
  geom_mosaic()
# good practice: use the 'dependent' variable (or most important variable)
# as fill variable

# if there is only one variable inside `product()`,
# `product()` can be omitted
ggplot(data = titanic, aes(x = Class, fill = Survived)) +
  geom_mosaic()

ggplot(data = titanic,
       aes(x = product(Class, Age), fill = Survived)) +
  geom_mosaic()

ggplot(data = titanic,
       aes(x = product(Class), conds = product(Age), fill = Survived)) +
  geom_mosaic()

# if there is only one variable inside `product()`,
# `product()` can be omitted
ggplot(data = titanic, aes(x = Class, conds = Age, fill = Survived)) +
  geom_mosaic()

ggplot(data = titanic,
       aes(x = product(Survived, Class), fill = Age)) +
  geom_mosaic()

# Variables can be transformed directly inside mosaic aesthetics
ggplot(data = mtcars,
       aes(x = product(factor(gear)), fill = factor(cyl))) +
  geom_mosaic()

# A fill-only variable colours and partitions the tiles without appearing on
# a position axis. Reverse the product order to put `actual` on the x axis.
set.seed(19790801)
predictions <- sample(iris$Species)
confusion <- as.data.frame(table(actual = iris$Species, predictions))
confusion$is_correct <- ifelse(
  confusion$actual == confusion$predictions,
  "Correct prediction", "Incorrect prediction"
)
ggplot(confusion, aes(
    weight = Freq,
    x = product(predictions, actual),
    fill = is_correct
  )) +
  geom_mosaic()

# Wrapped in donttest: still runs under R CMD check --run-donttest and is
# exercised by the package's tests to make sure it works.

data(happy)

ggplot(data = happy, aes(x = product(happy))) +
  geom_mosaic(divider = "hbar")

ggplot(data = happy, aes(x = product(happy))) +
  geom_mosaic() +
  coord_flip()

# weighting is important
ggplot(data = happy, aes(weight = wtssall, x = product(happy))) +
  geom_mosaic()

ggplot(data = happy,
       aes(weight = wtssall, x = product(health), fill = happy)) +
  geom_mosaic() +
  theme(axis.text.x=element_text(angle=35))

ggplot(data = happy,
       aes(weight = wtssall, x = product(health), fill = happy)) +
  geom_mosaic(na.rm = TRUE)

ggplot(data = happy,
       aes(weight = wtssall, x = product(health, sex, degree), fill = happy)) +
  geom_mosaic(na.rm = TRUE)

# here is where a bit more control over the spacing of the bars is helpful:
# set labels manually:
ggplot(data = happy,
       aes(weight = wtssall, x = product(age), fill = happy)) +
  geom_mosaic(na.rm = TRUE, offset = 0) +
  scale_x_productlist("Age", labels=c(17+1:72))

# thin out labels manually:
labels <- c(17+1:72)
labels[labels %% 5 != 0] <- ""
ggplot(data = happy,
       aes(weight = wtssall, x = product(age), fill = happy)) +
  geom_mosaic(na.rm = TRUE, offset = 0) +
  scale_x_productlist("Age", labels=labels)

ggplot(data = happy,
       aes(weight = wtssall, x = product(age), fill = happy,
           conds = product(sex))) +
  geom_mosaic(divider = mosaic("v"), na.rm = TRUE, offset = 0.001) +
  scale_x_productlist("Age", labels=labels)

ggplot(data = happy,
       aes(weight = wtssall, x = product(age), fill = happy)) +
  geom_mosaic(na.rm = TRUE, offset = 0) +
  facet_grid(sex~.) +
  scale_x_productlist("Age", labels=labels)

ggplot(data = happy,
       aes(weight = wtssall, x = product(happy, finrela, health))) +
  geom_mosaic(divider = mosaic("h"))

ggplot(data = happy,
       aes(weight = wtssall, x = product(happy, finrela, health))) +
  geom_mosaic(offset = .005)

# Spine example
ggplot(data = happy,
       aes(weight = wtssall, x = product(health), fill = health)) +
 geom_mosaic() +
 facet_grid(happy~.)

# Residual shading with independence model
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic(expected = "independence") +
  scale_fill_residual()

# Custom model formula
ggplot(data = titanic, aes(x = product(Class, Sex, Survived))) +
  geom_mosaic(expected = ~ Class + Sex) +
  scale_fill_residual()
 # end of donttest

---

Jittered dots in Mosaic plots.

Description

A mosaic plat with jittered dots

Usage

geom_mosaic_jitter(
  mapping = NULL,
  data = NULL,
  stat = "mosaic_jitter",
  position = "identity",
  na.rm = FALSE,
  divider = mosaic(),
  offset = 0.01,
  drop_level = FALSE,
  seed = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

stat_mosaic_jitter(
  mapping = NULL,
  data = NULL,
  geom = "mosaic_jitter",
  position = "identity",
  na.rm = FALSE,
  divider = mosaic(),
  show.legend = NA,
  inherit.aes = TRUE,
  offset = 0.01,
  drop_level = FALSE,
  seed = NA,
  ...
)

Arguments

mapping	Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat	The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used to override the default coupling between geoms and stats. The stat argument accepts the following: A Stat ggproto subclass, for example StatCount. A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count". For more information and other ways to specify the stat, see the layer stat documentation.
position	A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following: The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position. A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter". For more information and other ways to specify the position, see the layer position documentation.
na.rm	If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
divider	Divider function. The default divider function is mosaic() which will use spines in alternating directions. The four options for partitioning: vspine Vertical spine partition: width constant, height varies. hspine Horizontal spine partition: height constant, width varies. vbar Vertical bar partition: height constant, width varies. hbar Horizontal bar partition: width constant, height varies. When omitted, divider can be inherited from mosaic_settings().
offset	Set the fixed gap at the deepest split. Gaps increase by a factor of 1.5 toward the outermost split. When omitted, the value can be inherited from mosaic_settings().
drop_level	Generate points for the max - 1 level
seed	Random seed passed to set.seed. Defaults to NA, which means that set.seed will not be called.
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().
...	other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = 'red' or size = 3. They may also be parameters to the paired geom/stat.
geom	The geometric object to use to display the data for this layer. When using a ⁠stat_*()⁠ function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following: A Geom ggproto subclass, for example GeomPoint. A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point". For more information and other ways to specify the geom, see the layer geom documentation.

Details

Variables mapped only to fill, alpha, or colour remain available to the mosaic calculation and point aesthetics, but are not shown on automatic product axes. Position axes label only variables explicitly mapped through x or conds.

Value

A ggplot2 layer that can be added to a plot.

Computed variables

xmin

location of bottom left corner

xmax

location of bottom right corner

ymin

location of top left corner

ymax

location of top right corner

Author(s)

Gavin Klorfine

Examples

data(titanic)

ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(aes(fill = Survived), alpha = 0.3) +
  geom_mosaic_jitter(aes(color = Survived))

ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(alpha = 0.1) +
  geom_mosaic_jitter(aes(color = Survived), drop_level = TRUE)

ggplot(data = titanic, aes(x = product(Class, Sex))) +
  mosaic_settings(divider = c("vspine", "hspine", "hspine")) +
  geom_mosaic(alpha = 0.3, aes(fill = Survived)) +
  geom_mosaic_jitter(aes(color = Survived))

 ggplot(data = titanic,
        aes(x = product(Class), conds = product(Sex), fill = Survived)) +
  geom_mosaic(alpha = 0.3,
              divider = c("vspine", "hspine", "hspine")) +
  geom_mosaic_jitter(
              divider = c("vspine", "hspine", "hspine"))

---

Labeling for Mosaic plots.

Description

A mosaic plot with text or labels

Usage

geom_mosaic_text(
  mapping = NULL,
  data = NULL,
  stat = "mosaic",
  position = "identity",
  na.rm = FALSE,
  divider = mosaic(),
  offset = 0.01,
  show.legend = NA,
  inherit.aes = TRUE,
  as.label = FALSE,
  repel = FALSE,
  repel_params = NULL,
  check_overlap = FALSE,
  display_values = "label",
  format_digits = 1,
  expected = NULL,
  ...
)

Arguments

mapping	Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat	The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used to override the default coupling between geoms and stats. The stat argument accepts the following: A Stat ggproto subclass, for example StatCount. A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count". For more information and other ways to specify the stat, see the layer stat documentation.
position	A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following: The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position. A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter". For more information and other ways to specify the position, see the layer position documentation.
na.rm	If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
divider	Divider function. The default divider function is mosaic() which will use spines in alternating directions. The four options for partitioning: vspine Vertical spine partition: width constant, height varies. hspine Horizontal spine partition: height constant, width varies. vbar Vertical bar partition: height constant, width varies. hbar Horizontal bar partition: width constant, height varies. When omitted, divider can be inherited from mosaic_settings().
offset	Set the fixed gap at the deepest split. Gaps increase by a factor of 1.5 toward the outermost split. When omitted, the value can be inherited from mosaic_settings().
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().
as.label	Show as a ggplot label (box with round corners)
repel	Use ggrepel so labels don't overlap
repel_params	List of ggrepel parameters (e.g. list(point.padding = 0))
check_overlap	If TRUE, text that overlaps previous text in the same layer will not be plotted. check_overlap happens at draw time and in the order of the data. Therefore data should be arranged by the label column before calling geom_label() or geom_text().
display_values	Character string specifying what values to display in cells. Options: "label" (default, factor labels), "observed" (observed counts), "expected" (expected values from model), "residual" (Pearson residuals). "expected" and "residual" require a model supplied directly through expected or inherited from mosaic_settings.
format_digits	Number of decimal places for formatting numeric values (default: 1). Only used when display_values is not "label".
expected	Optional loglinear model specification (same as in geom_mosaic). An effective model is required when using display_values = "expected" or "residual". Supply a formula or character shortcut directly, or omit the argument to inherit a model from mosaic_settings. An explicitly supplied value takes priority, and NULL turns off a plot-level model for this layer.
...	other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = 'red' or size = 3. Text aesthetics that can be controlled include: size (default: 2.7), colour/color, fontface ('plain', 'bold', 'italic', 'bold.italic'), family (font family), angle (rotation in degrees), hjust/vjust (justification), and lineheight. They may also be parameters to the paired geom/stat.

Value

A ggplot2 layer that can be added to a plot.

Author(s)

Gavin Klorfine

Examples

data(titanic)

ggplot(data = titanic, aes(x = product(Class), fill = Survived)) +
  geom_mosaic() +
  geom_mosaic_text()

ggplot(data = titanic, aes(x = product(Class, Sex), fill = Survived)) +
  mosaic_settings(divider = c("vspine", "hspine", "hspine")) +
  geom_mosaic() +
  geom_mosaic_text(size = 2)

ggplot(data = happy, aes(x = product(happy, health), fill = happy)) +
  geom_mosaic(aes(x = product(health)), na.rm = TRUE, show.legend = FALSE) +
  geom_mosaic_text(na.rm = TRUE, show.legend = FALSE)

# avoid overlapping text
ggplot(data = happy, aes(x = product(happy, health), fill = happy)) +
  geom_mosaic(aes(x = product(health)), na.rm = TRUE, show.legend = FALSE) +
  geom_mosaic_text(na.rm = TRUE, check_overlap = TRUE, show.legend = FALSE)

# or use ggrepel
ggplot(data = happy, aes(x = product(happy, health), fill = happy)) +
  geom_mosaic(aes(x = product(health)), na.rm = TRUE, show.legend = FALSE) +
  geom_mosaic_text(na.rm = TRUE, repel = TRUE, show.legend = FALSE)

# and as a label
ggplot(data = happy, aes(x = product(happy, health), fill = happy)) +
  geom_mosaic(aes(x = product(health)), na.rm = TRUE, show.legend = FALSE) +
  geom_mosaic_text(
    na.rm = TRUE, repel = TRUE, as.label = TRUE,
    fill = "white", show.legend = FALSE
  )

# Display observed counts in cells
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic(aes(fill = Survived)) +
  geom_mosaic_text(display_values = "observed")

# Display residuals with one shared model specification
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  mosaic_settings(expected = "independence") +
  geom_mosaic() +
  scale_fill_residual() +
  geom_mosaic_text(display_values = "residual",
                   format_digits = 2)

# Display expected values
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  mosaic_settings(expected = "independence") +
  geom_mosaic() +
  scale_fill_residual() +
  geom_mosaic_text(display_values = "expected",
                   format_digits = 1)

---

Geom proto

Description

Geom proto

Value

A ggproto object inheriting from ggplot2::Geom, used internally by geom_mosaic() to draw the mosaic tile rectangles. Not intended to be called directly.

---

Geom proto

Description

Geom proto

Value

A ggproto object inheriting from ggplot2::Geom, used internally by geom_mosaic_jitter() to draw jittered points within mosaic plot cells. Not intended to be called directly.

---

Geom proto

Description

Geom proto

Value

A ggproto object inheriting from ggplot2::Geom, used internally by geom_mosaic_text() to draw text/label annotations on mosaic plot cells. Not intended to be called directly.

---

Data related to happiness from the general social survey.

Description

The data is a small sample of variables related to happiness from the general social survey (GSS). The GSS is a yearly cross-sectional survey of Americans, run since 1972. We combine data for more than 25 years to yield over 60 thousand observations, and of the over 5,000 variables, we select some variables that are related to happiness:

Usage

data(happy)

Format

A data frame with 62466 rows and 11 variables

• year. year of the response, 1972 to 2018.

• age. age in years: 18–89 (89 stands for all 89 year olds and older).

• degree. highest education: lt high school, high school, junior college, bachelor, graduate.

• finrela. how is your financial status compared to others: far below, below average, average, above average, far above.

• happy. happiness: very happy, pretty happy, not too happy.

• health. health: excellent, good, fair, poor.

• marital. marital status: married, never married, divorced, widowed, separated.

• sex. sex: female, male.

• polviews. from extremely conservative to extremely liberal.

• partyid. party identification: strong republican, not str republican, ind near rep, independent, ind near dem, not str democrat, strong democrat, other party.

• wtssall. probability weight. 0.39–8.74

---

Horizontal bar partition: width constant, height varies.

Description

Horizontal bar partition: width constant, height varies.

Usage

hbar(data, bounds, offset = 0.02, max = NULL)

Arguments

data	bounds data frame
bounds	bounds of space to partition
offset	space between spines
max	maximum value

Value

A data frame of rectangle boundaries (l, r, b, t), one row per level of data.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(divider = "hbar")

---

Horizontal spine partition: height constant, width varies.

Description

Horizontal spine partition: height constant, width varies.

Usage

hspine(data, bounds, offset = offset, max = NULL)

Arguments

data	bounds data frame
bounds	bounds of space to partition
offset	space between spines
max	maximum value

Value

A data frame of rectangle boundaries (l, r, b, t), one row per level of data.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(divider = "hspine")

---

Template for a mosaic plot. A mosaic plot is composed of spines in alternating directions.

Description

Template for a mosaic plot. A mosaic plot is composed of spines in alternating directions.

Usage

mosaic(direction = "h")

Arguments

direction

direction of first split

Value

A function of one argument, the number of splits n, that returns a character vector of divider function names ("hspine"/"vspine") to apply at each split – suitable for the divider argument of geom_mosaic() and related layers.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic(divider = mosaic("v"))

---

Settings for mosaic plot layers

Description

Set the divider, gap size, and model used to calculate expected frequencies for mosaic layers in a plot. A value set directly in a layer takes priority.

Usage

mosaic_settings(divider, offset, expected)

Arguments

divider	A divider function, a character vector naming divider functions, or a list of divider functions.
offset	A single non-negative number giving the gap at the deepest split. Gaps increase by a factor of 1.5 toward the outermost split.
expected	The log-linear model used to calculate expected frequencies and Pearson residuals. Supply a formula or one of "independence", "saturated", or "conditional". The conditional model requires one or more variables mapped to conds. Supply NULL to turn off model fitting, including a model set by an earlier call to mosaic_settings().

Details

A layer inherits a setting only when its corresponding argument is omitted. Settings are resolved in this order: an explicitly supplied layer argument (including expected = NULL), the plot's mosaic_settings() value, and the layer default (mosaic(), 0.01, or NULL).

divider and offset are inherited by geom_mosaic(), stat_mosaic(), geom_mosaic_text(), stat_mosaic_text(), geom_mosaic_jitter(), and stat_mosaic_jitter(). expected is inherited by the same constructors except the mosaic-jitter geom and stat.

The position of mosaic_settings() among the layers in a plot has no effect. If it is added more than once, the last supplied value for each setting is used; omitted arguments do not change earlier settings. Settings are local to the plot and do not change package or session defaults. They share configuration, not computations or fitted model objects, between layers.

Value

An object of class "ggmosaic_settings" that can be added to a ggplot with +.

Author(s)

Gavin Klorfine

See Also

geom_mosaic(), stat_mosaic(), geom_mosaic_text(), stat_mosaic_text(), geom_mosaic_jitter(), stat_mosaic_jitter(), mosaic(), and ddecker()

Examples

data(titanic)

ggplot(titanic, aes(x = product(Class, Sex))) +
  mosaic_settings(
    expected = "independence",
    divider = c("vspine", "hspine"),
    offset = 0.005
  ) +
  geom_mosaic() +
  geom_mosaic_text(display_values = "residual") +
  scale_fill_residual() +
  theme_mosaic()

# An explicit layer argument overrides the plot setting. Here NULL turns
# model fitting off for the mosaic layer.
ggplot(titanic, aes(x = product(Class, Sex), fill = Survived)) +
  mosaic_settings(expected = "independence") +
  geom_mosaic(expected = NULL)

---

Wrapper for a list

Description

Wrapper for a list

Usage

product(...)

Arguments

...	Unquoted variables going into the product plot.

Value

A list of expressions (see rlang::exprs()), one per argument, used inside aes() to mark the variables that define the mosaic's product formula.

Examples

data(titanic)
ggplot(data = titanic,
       aes(x = product(Survived, Class), fill = Survived)) +
  geom_mosaic()

---

Diverging color scale for Pearson residuals

Description

Provides a red-white-blue color scale centered at 0 for visualizing Pearson residuals from loglinear models. Designed for use with geom_mosaic() when a model is supplied through the layer's expected argument or through mosaic_settings.

Usage

scale_fill_residual(
  ...,
  low = "darkred",
  mid = "white",
  high = "darkblue",
  midpoint = 0,
  limits = NULL,
  name = "Pearson\nResidual"
)

scale_fill_residuals(
  ...,
  low = "darkred",
  mid = "white",
  high = "darkblue",
  midpoint = 0,
  limits = NULL,
  name = "Pearson\nResidual"
)

Arguments

...	Arguments passed to scale_fill_gradient2
low	Color for negative residuals (default: "darkred")
mid	Color for zero residuals (default: "white")
high	Color for positive residuals (default: "darkblue")
midpoint	Center point for color scale (default: 0)
limits	Range used for the color gradient. Values beyond supplied limits receive the corresponding endpoint color.
name	Legend title

Details

The default legend always labels -4, 0, and 4. It also labels supplied limits and the observed minimum and maximum when those differ from the limits. The legend extends to every labeled value, with solid endpoint color beyond supplied limits. When the contributing mosaic cells have outlines, positive residuals have a solid dark blue outline, negative residuals have a dashed dark red outline, and an unoutlined midpoint band (white by default) separates them at zero. Setting colour = NA on every contributing mosaic layer removes these outlines from both the cells and the legend. Black ticks are drawn outside the color bar, which stretches with the mosaic panel. Nearby vertical labels are separated, and a thin elbow connects each displaced label to its exact tick. The neighboring label uses a longer straight tick so nearby text shares a common alignment. Automatically generated numeric labels are rounded to one decimal place. The legend can be hidden normally with theme(legend.position = "none").

Value

A ggplot2 fill scale that can be added to a plot.

Author(s)

Gavin Klorfine

Examples

data(titanic)

# Independence model with residual shading
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic(expected = "independence") +
  scale_fill_residual()

# Custom colors
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic(expected = "independence") +
  scale_fill_residual(low = "red", high = "blue")

# Custom limits to highlight strong deviations
ggplot(data = titanic, aes(x = product(Class, Sex, Survived))) +
  geom_mosaic(expected = ~ Class + Sex) +
  scale_fill_residual(limits = c(-4, 4))

---

Helper function for determining scales

Description

Used internally to determine class of variable x

Usage

## S3 method for class 'productlist'
scale_type(x)

Arguments

x

variable

Value

character string "productlist"

---

Determining scales for mosaics

Description

Determining scales for mosaics

Usage

scale_x_productlist(
  name = ggplot2::waiver(),
  breaks = product_breaks(),
  minor_breaks = NULL,
  labels = product_labels(),
  limits = NULL,
  expand = ggplot2::waiver(),
  oob = scales::censor,
  na.value = NA_real_,
  transform = "identity",
  position = "bottom",
  sec.axis = ggplot2::waiver()
)

scale_y_productlist(
  name = ggplot2::waiver(),
  breaks = product_breaks(),
  minor_breaks = NULL,
  labels = product_labels(),
  limits = NULL,
  expand = ggplot2::waiver(),
  oob = scales::censor,
  na.value = NA_real_,
  transform = "identity",
  position = "left",
  sec.axis = ggplot2::waiver()
)

ScaleContinuousProduct

Arguments

name	set to pseudo waiver function product_names by default.
breaks	One of: NULL for no breaks waiver() for the default breaks computed by the transformation object A numeric vector of positions A function that takes the limits as input and returns breaks as output (e.g., a function returned by scales::extended_breaks()). Note that for position scales, limits are provided after scale expansion. Also accepts rlang lambda function notation.
minor_breaks	One of: NULL for no minor breaks waiver() for the default breaks (none for discrete, one minor break between each major break for continuous) A numeric vector of positions A function that given the limits returns a vector of minor breaks. Also accepts rlang lambda function notation. When the function has two arguments, it will be given the limits and major break positions.
labels	One of the options below. Please note that when labels is a vector, it is highly recommended to also set the breaks argument as a vector to protect against unintended mismatches. NULL for no labels waiver() for the default labels computed by the transformation object A character vector giving labels (must be same length as breaks) An expression vector (must be the same length as breaks). See ?plotmath for details. A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.
limits	One of: NULL to use the default scale range A numeric vector of length two providing limits of the scale. Use NA to refer to the existing minimum or maximum A function that accepts the existing (automatic) limits and returns new limits. Also accepts rlang lambda function notation. Note that setting limits on positional scales will remove data outside of the limits. If the purpose is to zoom, use the limit argument in the coordinate system (see coord_cartesian()).
expand	For position scales, a vector of range expansion constants used to add some padding around the data to ensure that they are placed some distance away from the axes. Use the convenience function expansion() to generate the values for the expand argument. The defaults are to expand the scale by 5% on each side for continuous variables, and by 0.6 units on each side for discrete variables.
oob	One of: Function that handles limits outside of the scale limits (out of bounds). Also accepts rlang lambda function notation. The default (scales::censor()) replaces out of bounds values with NA. scales::squish() for squishing out of bounds values into range. scales::squish_infinite() for squishing infinite values into range.
na.value	Missing values will be replaced with this value.
transform	For continuous scales, the name of a transformation object or the object itself. Built-in transformations include "asn", "atanh", "boxcox", "date", "exp", "hms", "identity", "log", "log10", "log1p", "log2", "logit", "modulus", "probability", "probit", "pseudo_log", "reciprocal", "reverse", "sqrt" and "time". A transformation object bundles together a transform, its inverse, and methods for generating breaks and labels. Transformation objects are defined in the scales package, and are called ⁠transform_<name>⁠. If transformations require arguments, you can call them from the scales package, e.g. scales::transform_boxcox(p = 2). You can create your own transformation with scales::new_transform().
position	For position scales, The position of the axis. left or right for y axes, top or bottom for x axes.
sec.axis	specify a secondary axis. By default, category labels for the inner variables of the mosaic are displayed on the opposite (top or right) side whenever more than one variable is split along a direction. Set to NULL to suppress these labels, or supply a sec_axis for full control.

Value

A ggplot2 position scale that can be added to a plot.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class, Sex))) +
  geom_mosaic() +
  scale_x_productlist("Passenger class / Sex")

---

Spine partition: divide longest dimension.

Description

Spine partition: divide longest dimension.

Usage

spine(data, bounds, offset = offset, max = NULL)

Arguments

data	bounds data frame
bounds	bounds of space to partition
offset	space between spines
max	maximum value

Value

A data frame of rectangle boundaries (l, r, b, t), one row per level of data.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(divider = "spine")

---

Internal helper function

Description

Squeeze pieces to lie within specified bounds; directly copied from package productplots

Usage

squeeze(pieces, bounds = bound())

Arguments

pieces	rectangle specified via l(eft), r(ight), b(ottom), t(op)
bounds	rectangle specified via l(eft), r(ight), b(ottom), t(op)

Value

re-scaled values for piece according to boundaries given by bounds

Author(s)

Hadley Wickham

---

Geom proto

Description

Geom proto

Value

A ggproto object inheriting from ggplot2::Stat, used internally by stat_mosaic() (and geom_mosaic()) to compute the rectangle boundaries and cell statistics for a mosaic plot layer. Not intended to be called directly.

---

Geom proto

Description

Geom proto

Value

A ggproto object inheriting from ggplot2::Stat, used internally by stat_mosaic_jitter() (and geom_mosaic_jitter()) to compute jittered point positions for a mosaic plot layer. Not intended to be called directly.

---

Geom proto

Description

Geom proto

Value

A ggproto object inheriting from ggplot2::Stat, used internally by stat_mosaic_text() (and geom_mosaic_text()) to compute label positions for a mosaic plot layer. Not intended to be called directly.

---

Theme for mosaic plots

Description

Themes set the general aspect of the plot such as the color of the background, gridlines, the size and color of fonts. theme_mosaic provides access to the regular ggplot2 theme, but removes any background, axes ticks, most of the gridlines, and ensures an aspect ratio of 1 for better viewing of the mosaics. This theme also applies a bold face to axes labels and allows for the convenient rotation of category labels.

Usage

theme_mosaic(base_size = 11, base_family = "", rot_labels = 0, ...)

Arguments

base_size	Base font size. Defaults to 11.
base_family	Base font family. Defaults to "", which uses the graphics device's default font family.
rot_labels	The angle (in degrees) used to rotate category labels. Defaults to 0 degrees, relative to the current axis orientation.
...	Additional arguments passed to ggplot2::theme(). These are applied after the mosaic theme defaults and can therefore override them.

Details

As with other ggplot2 extensions, themes set the general look-and-feel of the plot such as the color of the background, gridlines, the size and color of fonts. theme_mosaic() provides access to the regular ggplot2 theme, but: removes any background, axes ticks, most of the gridlines, and ensures an aspect ratio of 1 for better viewing of the mosaics. This theme also applies a bold face to axes labels and allows for the convenient rotation of category labels to avoid overlap

Value

A ggplot2 theme object that can be added to a plot.

Author(s)

Gavin Klorfine

Examples

library(ggmosaic2)
data(happy)
ggplot(data = happy,
       aes(weight = wtssall, x = product(health), fill = happy)) +
  geom_mosaic(na.rm = TRUE) +
  theme_mosaic()

---

Passengers and crew on board the Titanic

Description

A dataset containing some demographics and survival of people on board the Titanic

Usage

titanic

Format

A data frame with 2201 rows and 4 variables:

Class

factor variable containing the class of a passenger (1st, 2nd, 3rd) or crew.

Sex

Male/Female.

Age

Child/Adult. This information is not very reliable, because it was inferred from boarding documents that did not state actual age in years.

Survived

Yes/No.

---

Vertical bar partition: height constant, width varies.

Description

Vertical bar partition: height constant, width varies.

Usage

vbar(data, bounds, offset = 0.02, max = NULL)

Arguments

data	bounds data frame
bounds	bounds of space to partition
offset	space between spines
max	maximum value

Value

A data frame of rectangle boundaries (l, r, b, t), one row per level of data.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(divider = "vbar")

---

Vertical spine partition: width constant, height varies.

Description

Vertical spine partition: width constant, height varies.

Usage

vspine(data, bounds, offset = offset, max = NULL)

Arguments

data	bounds data frame
bounds	bounds of space to partition
offset	space between spines
max	maximum value

Value

A data frame of rectangle boundaries (l, r, b, t), one row per level of data.

Examples

data(titanic)
ggplot(data = titanic, aes(x = product(Class))) +
  geom_mosaic(divider = "vspine")

---