ggpp
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Grammar of graphics extensions to 'ggplot2'
ggpp ![](https://github.com/aphalo/ggpp/raw/master/man/figures/logo-ggpp.png)
Purpose
Package ‘ggpp’ provides a set of building blocks that extend the
Grammar of Graphics implemented in package ‘ggplot2’ (>= 3.0.0). New
“geoms” support insets in plots, marginal marks and the use of native
plot coordinates (npc). Position functions implement new approaches to
nudging usable with any geometry, but especially useful together with
geom_text_s()
, ggrepel::geom_text_repel()
and
ggrepel::geom_label_repel()
.
Extended Grammar of graphics
Geometries
Geometries geom_table()
, geom_plot()
and geom_grob()
make it
possible to add inset tables, inset plots, and arbitrary ‘grid’
graphical objects including bitmaps and vector graphics as layers to a
ggplot using native coordinates for x
and y
.
Geometries geom_text_npc()
, geom_label_npc()
, geom_table_npc()
,
geom_plot_npc()
and geom_grob_npc()
, geom_text_npc()
and
geom_label_npc()
are versions of geometries that accept positions on
x and y axes using aesthetics npcx
and npcy
values expressed in
“npc” units.
Geometries geom_x_margin_arrow()
, geom_y_margin_arrow()
,
geom_x_margin_grob()
, geom_y_margin_grob()
, geom_x_margin_point()
and geom_y_margin_point()
make it possible to add marks along the x
and y axes. geom_vhlines()
and geom_quadrant_lines()
draw vertical
and horizontal reference lines within a single layer.
Geometries geom_text_s()
, geom_label_s()
, geom_point_s()
,
geom_table()
, geom_plot()
and geom_grob()
connect (by default) the
plot elements added at a nudged position to the original position with a
segment or arrow.
Aesthetics and scales
Scales scale_npcx_continuous()
and scale_npcy_continuous()
and the
corresponding new aesthetics npcx
and npcy
make it possible to add
graphic elements and text to plots using coordinates expressed in npc
units for the location within the plotting area.
Statistics
Statistic stat_fmt_tb()
helps with the formatting of tables to be
plotted with geom_table()
.
Four statistics, stat_dens2d_filter()
, stat_dens2d_label()
,
stat_dens1d_filter()
and stat_dens1d_label()
, implement tagging or
selective labelling of observations based on the local 2D density of
observations in a panel. Another two statistics,
stat_dens1d_filter_g()
and stat_dens1d_filter_g()
compute the
density by group instead of by plot panel. These six statistics are
designed to work well together with geom_text_repel()
and
geom_label_repel()
from package ‘ggrepel’.
The statistics stat_apply_panel()
and stat_apply_group()
are useful
for applying arbitrary functions returning numeric vectors like
cumsum()
, cummax()
and diff()
. Statistics stat_centroid()
and
stat_summary_xy()
allow computation of summaries on both x and y
and passing them to a geom.
Position functions
Position functions implementing different flavours of nudging are
provided: position_nudge_keep()
, position_nudge_to()
,
position_nudge_center()
and position_nudge_line()
. These last two
functions make it possible to apply nudging that varies automatically
according to the relative position of points with respect to arbitrary
points or lines, or with respect to a polynomial or smoothing spline
fitted on-the-fly to the the observations.
Position functions position_stacknudge()
, position_fillnudge()
,
position_jitternudge()
, position_dodgenudge()
and
position_dodge2nudge()
each combines the roles of two position
functions. They make it possible to easily nudge labels in plot layers
that use stacking, dodging or jitter. Functions
position_jitter_keep()
, position_stack_keep()
,
position_fill_keep()
, position_dodge_keep()
,
position_dosge2_keep()
behave like the positions from ‘ggplot2’ but
keep in data the original coordinates.
In contrast to position functions from ‘ggplot2’ all these position
functions keep the original x and y coordinates when displacing
them. This makes them compatible with the repulsive geometries from
package ‘ggrepel’ (>= 0.9.1) as well as with geom_text_s()
,
geom_point_s()
, geom_table()
, geom_plot()
and geom_grob()
from
this package. All these geoms can draw segments or arrows connecting the
original positions to the displaced positions. They remain backwards
compatible and can be used in all geometries that have a position
formal parameter.
Justification
Justifications "outward_mean"
, "inward_mean"
, "outward_median"
and
"inward_median"
implementing outward and inward justification relative
to the centroid of the data instead of to the center of the x or y
scales. Justification outward or inward from an arbitrary origin is also
supported.
History
This package is a “spin-off” from package ‘ggpmisc’ containing extensions to the grammar originally written for use wihtin ‘ggpmisc’. As ‘ggpmisc’ had grown in size, splitting it into two packages was necessary to easy development and maintenance and to facilitate imports into other packages. For the time being, package ‘ggpmisc’ imports and re-exports all visible definitions from ‘ggpp’.
Examples
The plots below exemplify some of the things that ‘ggpp’ makes possible or makes easier to code compared to ‘ggplot’ used by itself. Additional examples including several combining ‘ggpp’ and ‘ggrepel’ are provided in the package vignette.
library(ggpp)
library(ggrepel)
library(dplyr)
Insets
A plot with an inset table.
mtcars %>%
group_by(cyl) %>%
summarize(wt = mean(wt), mpg = mean(mpg)) %>%
ungroup() %>%
mutate(wt = sprintf("%.2f", wt),
mpg = sprintf("%.1f", mpg)) -> tb
df <- tibble(x = 5.45, y = 34, tb = list(tb))
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
geom_point() +
geom_table(data = df, aes(x = x, y = y, label = tb))
A plot with an inset plot.
Inset plot positioned using native plot coordinates (npc) and using keywords insted of numerical values in the range 0..1 which are also accepted.
p <- ggplot(mtcars, aes(factor(cyl), mpg, colour = factor(cyl))) +
stat_boxplot() +
labs(y = NULL, x = "Engine cylinders (number)") +
theme_bw(9) + theme(legend.position = "none")
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
geom_point(show.legend = FALSE) +
annotate("plot_npc", npcx = "left", npcy = "bottom", label = p) +
expand_limits(y = 0, x = 0)
Centroids
Means computed on-the-fly and shown as asterisks.
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
geom_point() +
stat_centroid(shape = "asterisk", size = 6)
Medians computed on-the-fly displayed marginal arrows.
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
geom_point() +
stat_centroid(geom = "y_margin_arrow", .fun = median,
aes(yintercept = after_stat(y)), arrow.length = 0.05)
Nudging and stacking combined
df <- data.frame(x1 = c(1, 2, 1, 3, -1),
x2 = c("a", "a", "b", "b", "b"),
grp = c("some long name", "other name", "some name",
"another name", "a name"))
# Add labels to a horizontal column plot (stacked by default)
ggplot(data = df, aes(x2, x1, group = grp)) +
geom_col(aes(fill = grp), width=0.5) +
geom_hline(yintercept = 0) +
geom_text(
aes(label = grp),
position = position_stacknudge(vjust = 1, y = -0.2)) +
theme(legend.position = "none")
Installation
Installation of the most recent stable version from CRAN:
install.packages("ggpp")
Installation of the current unstable version from GitHub:
# install.packages("devtools")
devtools::install_github("aphalo/ggpp")
Documentation
HTML documentation for the package, including help pages and the User Guide, is available at (https://docs.r4photobiology.info/ggpp/).
News about updates are regularly posted at (https://www.r4photobiology.info/).
Chapter 7 in Aphalo (2020) explains both basic concepts of the gramamr of graphics as implemented in ‘ggplot2’ as well as extensions to this grammar including several of those made available by packages ‘ggpp’ and ‘ggpmisc’.
Contributing
Please report bugs and request new features at (https://github.com/aphalo/ggpp/issues). Pull requests are welcome at (https://github.com/aphalo/ggpp).
Citation
If you use this package to produce scientific or commercial publications, please cite according to:
citation("ggpp")
References
Aphalo, Pedro J. (2020) Learn R: As a Language. The R Series. Boca Raton and London: Chapman and Hall/CRC Press. ISBN: 978-0-367-18253-3. 350 pp.
License
© 2016-2021 Pedro J. Aphalo ([email protected]). Released under the GPL, version 2 or greater. This software carries no warranty of any kind.