Title: Visualizing Social Science Data with 'ggplot2'
Version: 0.0.7
Description: A 'ggplot2' extension for implementing parliament charts and several other useful visualizations.
URL: https://github.com/erocoar/ggpol
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: ggplot2 (≥ 3.3.0), R (≥ 3.4.0)
Imports: grid, gtable, grDevices, plyr, rlang, dplyr, tibble, glue
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
Collate: 'facet_share.R' 'utilities.R' 'geom_arcbar.R' 'geom_bartext.R' 'geom_boxjitter.R' 'geom_circle.R' 'geom_confmat.R' 'geom_parliament.R' 'geom_tshighlight.R' 'ggproto-classes.R' 'stat-arcbar.R' 'stat-boxjitter.R' 'stat-circle.R' 'stat-confmat.R' 'stat-parliament.R'
NeedsCompilation: no
Packaged: 2020-11-08 13:24:59 UTC; fjtie
Author: Frederik Tiedemann [aut, cre]
Maintainer: Frederik Tiedemann <fj.tiedemann@googlemail.com>
Repository: CRAN
Date/Publication: 2020-11-08 13:40:02 UTC

ggplot extensions

Description

ggplot extensions

Confusion Matrix

Description

Plot a confusion matrix.

Usage

geom_confmat(
  mapping = NULL,
  data = NULL,
  stat = "confmat",
  position = "identity",
  width = NULL,
  height = NULL,
  annotate = TRUE,
  text.perc = FALSE,
  text.digits = 3,
  text.alpha = NULL,
  text.angle = NULL,
  text.colour = NULL,
  text.family = NULL,
  text.fontface = NULL,
  text.group = NULL,
  text.hjust = NULL,
  text.lineheight = NULL,
  text.size = NULL,
  text.vjust = NULL,
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_confmat(
  mapping = NULL,
  data = NULL,
  geom = "tile",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  na.rm = FALSE,
  normalize = FALSE,
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

width

The tile height.

height

The tile width.

annotate

Boolean indicator for whether to include values as text in each tile.

text.perc

Boolean indicator for whether to add '%' to the end of each value.

text.digits

Numeric vector equal to length one, indicating the number of digits to display. 'round(x, text.digits)'.

text.alpha

Alpha value for the text grobs.

text.angle

Angle value for the text grobs.

text.colour

Colour of the text grobs.

text.family

Font family of the text grobs.

text.fontface

Font face of the text grobs.

text.group

Groups of the text grobs.

text.hjust

Hjust of the text grobs.

text.lineheight

Lineheight of the text grobs.

text.size

Size of the text grobs.

text.vjust

Vjust of the text grobs.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

geom

The geometric object to use display the data

normalize

Boolean indicator for whether to scale the frequency values.

Examples

x <- sample(LETTERS[seq(4)], 50, replace = TRUE)
y <- sample(LETTERS[seq(4)], 50, replace = TRUE)

ggplot() + 
  geom_confmat(aes(x = x, y = y), normalize = TRUE, text.perc = TRUE)

A shared axis for two panels

Description

'facet_share' uses [facet_wrap()] to build two panels with a shared axis.

Usage

facet_share(
  facets,
  scales = "fixed",
  reverse_num = FALSE,
  shrink = TRUE,
  labeller = "label_value",
  as.table = TRUE,
  switch = NULL,
  drop = TRUE,
  dir = "h",
  strip.position = "top"
)

Arguments

facets

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, can also be a formula or character vector. Use either a one sided formula, ~a + b, or a character vector, c("a", "b").

scales

Should scales be fixed ("fixed", the default), free ("free"), or free in one dimension ("free_x", "free_y")?

reverse_num

Used when passing on flipped data (times -1) for the second (right/bottom) panel. If 'TRUE', this will multiply the axis labels for that panel by -1.

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.

dir

Direction: either "h" for horizontal, the default, or "v", for vertical.

strip.position

By default, the labels are displayed on the top of the plot. Using strip.position it is possible to place the labels on either of the four sides by setting strip.position = c("top", "bottom", "left", "right")

Create an Arc-Barchart

Description

An arc bar diagram that allows for spacing between the individual arc components and spans 180 degrees.

Usage

geom_arcbar(
  mapping = NULL,
  data = NULL,
  stat = "arcbar",
  position = "identity",
  n = 360,
  sep = 0.05,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

stat_arcbar(
  mapping = NULL,
  data = NULL,
  geom = "arcbar",
  position = "identity",
  n = 360,
  sep = 0.05,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

n

The number of

sep

Separation between the different shares, as a total proportion of pi.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

geom

The geometric object to use display the data

Aesthetics

geom_arcbar understands the following aesthetics (required aesthetics are in bold):

- **shares** - **r0** - inner radius - **r1** - outer radius - color - fill - linetype - alpha

Examples

bt <- data.frame(
  parties = factor(c("CDU", "CSU", "AfD", "FDP", "SPD", 
                     "Linke", "Gruene", "Fraktionslos"),
                   levels = c("CDU", "CSU", "AfD", "FDP", "SPD", 
                              "Linke", "Gruene", "Fraktionslos")),
  seats   = c(200, 46, 92, 80, 153, 69, 67, 2),
  colors  = c("black", "blue", "lightblue", "yellow", "red",
              "purple", "green", "grey"),
  stringsAsFactors = FALSE)

ggplot(bt) + 
  geom_arcbar(aes(shares = seats, r0 = 5, r1 = 10, fill = parties)) + 
  scale_fill_manual(values = bt$colors) +
  coord_fixed() +
  theme_void()

Repelling text for GeomBar.

Description

Repelling text for GeomBar.

Usage

geom_bartext(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  parse = FALSE,
  nudge_x = 0,
  nudge_y = 0,
  spacing = 0.003,
  dir = "v",
  check_overlap = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

parse

If TRUE, the labels will be parsed into expressions and displayed as described in ?plotmath.

nudge_x

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales.

nudge_y

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales.

spacing

Defaults to 0.003. Minimum spacing between labels in NPC units.

dir

Defaults to "v", i.e. vertical repel of overlapping groups of labels. Can alternatively be set to "h" for horizontal repel.

check_overlap

If TRUE, text that overlaps previous text in the same layer will not be plotted.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

Examples

df <- data.frame(L = rep(LETTERS[1:2], each = 4),
                 l = rep(letters[1:4], 2),
                 val = c(96.5, 1, 2, 0.5, 48, 0.7, 0.3, 51))
 
ggplot(df, aes(x = L, y = val, fill = l)) +
  geom_bar(stat = "identity") +
  geom_bartext(aes(label = paste0(val, "%")), position = position_stack(vjust = 0.5)) +
  ggtitle("GeomBartext")

A hybrid boxplot.

Description

Half boxplot, half scatterplot with customizable jitter.

Usage

geom_boxjitter(
  mapping = NULL,
  data = NULL,
  stat = "BoxJitter",
  position = "dodge",
  ...,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  outlier.intersect = FALSE,
  jitter.colour = NULL,
  jitter.color = NULL,
  jitter.fill = NULL,
  jitter.shape = 19,
  jitter.size = 1.5,
  jitter.stroke = 0.5,
  jitter.alpha = NULL,
  jitter.position = ggplot2::PositionJitter,
  jitter.params = list(width = NULL, height = NULL),
  boxplot.expand = FALSE,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  errorbar.draw = FALSE,
  errorbar.length = 0.5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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

Use to override the default connection between geom_boxplot and stat_boxplot.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

outlier.colour

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.color

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.fill

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.shape

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.size

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.stroke

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.alpha

Default aesthetics for outliers. Set to NULL to inherit from the aesthetics used for the box.

In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.

Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.shape = NA. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden.

outlier.intersect

Defaults to 'FALSE'. If set to 'TRUE', outliers will be part of the jitter-plot (but keeping the given outlier graphical parameters) rather than plotted vertically above / below the whisker lines.

jitter.colour, jitter.color, jitter.fill, jitter.shape, jitter.size, jitter.stroke, jitter.alpha

Default aesthetics for jitter, set to 'NULL' to inherit from the aesthetics used for the box.

jitter.position

Position object used for calculating jitter (defaults to 'ggplot2::PositionJitter').

jitter.params

Parameters passed to 'jitter.position' (for 'ggplot2::PositionJitter', this is 'width', 'height' and 'seed').

boxplot.expand

Defaults to 'FALSE'. If set to 'TRUE', the full boxplots will be plotted.

notch

If FALSE (default) make a standard box plot. If TRUE, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different.

notchwidth

For a notched box plot, width of the notch relative to the body (defaults to notchwidth = 0.5).

varwidth

If FALSE (default) make a standard box plot. If TRUE, boxes are drawn with widths proportional to the square-roots of the number of observations in the groups (possibly weighted, using the weight aesthetic).

errorbar.draw

Draw horizontal whiskers at the top and bottom (the IQR). Defaults to 'FALSE'.

errorbar.length

Length of the horizontal whiskers (errorbar). Defaults to half the width of the half-boxplot, or half the width of the entire boxplot if 'boxplot.expand' is set to 'TRUE'.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

Examples

set.seed(221)
df <- data.frame(score = rgamma(150, 4, 1), 
                 gender = sample(c("M", "F"), 150, replace = TRUE), 
                 genotype = factor(sample(1:3, 150, replace = TRUE)))

ggplot(df) + geom_boxjitter(aes(x = gender, y = score, fill = genotype),
                            jitter.shape = 21, jitter.color = NA,
                            outlier.color = NA, errorbar.draw = TRUE) +
  scale_fill_manual(values = c("#CF3721", "#31A9B8", "#258039")) +
  theme_minimal()

Circles with pre-defined radii.

Description

Similar to '[geom_point()]', but allows for full control of the size.

Usage

geom_circle(
  mapping = NULL,
  data = NULL,
  stat = "circle",
  position = "identity",
  n = 360,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

stat_circle(
  mapping = NULL,
  data = NULL,
  geom = "circle",
  position = "identity",
  n = 360,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

n

The number of points calculated for the circle polygon, defaults to 360.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

geom

The geometric object to use display the data

Aesthetics

geom_circle understands the following aesthetics (required aesthetics are in bold):

- **x** - x-coordinate of center - **y** - y-coordinate of center - **r** - radius - color - fill - linetype - alpha

Examples

set.seed(22189)
df <- data.frame(x = sample(1:10, 3), y = sample(1:10, 3), 
                 r = sample(3:4, 3, replace = TRUE))

ggplot(df) + geom_circle(aes(x = x, y = y, r = r, fill = gl(3, 1))) +
  coord_fixed()

Create a Parliament Diagram

Description

Draws a parliament diagram based on parties' member counts, where each point in the arc represents a single member of parliament. Parties are plotted right-to-left.

Usage

geom_parliament(
  mapping = NULL,
  data = NULL,
  stat = "parliament",
  position = "identity",
  r0 = 1.5,
  r1 = 3,
  n = 360,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

stat_parliament(
  mapping = NULL,
  data = NULL,
  geom = "parliament",
  position = "identity",
  r0 = 1.5,
  r1 = 3,
  n = 360,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

r0

Inner radius, defaults to 1.5.

r1

Outer radius, defaults to 3.

n

Number of passed to 'StatCircle', defaults to 360.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

geom

The geometric object to use display the data

Aesthetics

geom_parliament understands the following aesthetics (required aesthetics are in bold): - **seats** - number of seats of the parties - fill - color - linetype - alpha

Computed variables

x,y

coordinates of individual MPs

Examples

bt <- data.frame(
  parties = factor(c("CDU", "CSU", "AfD", "FDP", "SPD", 
                     "Linke", "Gruene", "Fraktionslos"),
                   levels = c("CDU", "CSU", "AfD", "FDP", "SPD", 
                              "Linke", "Gruene", "Fraktionslos")),
  seats   = c(200, 46, 92, 80, 153, 69, 67, 2),
  colors  = c("black", "blue", "lightblue", "yellow", 
              "red","purple", "green", "grey"),
  stringsAsFactors = FALSE)

ggplot(bt) + 
  geom_parliament(aes(seats = seats, fill = parties), color = "black") + 
  scale_fill_manual(values = bt$colors, labels = bt$parties) +
  coord_fixed() + 
  theme_void()

Timeseries highlighting

Description

This is a version of [ggplot2::geom_rect()] that defaults to spanning the entirety of the y-axis.

Usage

geom_tshighlight(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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. borders().

Aesthetics

geom_tshighlight understands the following aesthetics (required aesthetics are in bold): - **xmin** - **xmax** - fill - color

Examples

ggplot(economics, aes(x = date, y = unemploy)) + 
  geom_line() +
  geom_tshighlight(aes(xmin = as.Date("01/01/1990", format = "%d/%m/%Y"), 
                       xmax = as.Date("01/01/2000", format = "%d/%m/%Y")),
                   alpha = 0.01)