ggblanket is a package of ggplot2 wrapper functions.
The primary objective is to simplify ggplot2 visualisation.
Secondary objectives relate to:
Computational speed has been traded-off.
set_blanket()gg_* function wraps a geomcol argument to colour/fill by a variablefacet argument to facet by a variablefacet2 argument to facet by a 2nd variablemapping argument*_label defaults for axis and legend titlesggplot2::geom_* arguments via
...*_mode_* themes with legend variantsgeom_* layersset_blanket()gg_blanket() function with geom
flexibilitylibrary(dplyr)
library(stringr)
library(ggplot2)
library(scales)
library(ggblanket)
library(palmerpenguins)
library(patchwork)
penguins2 <- penguins |>
labelled::set_variable_labels(
bill_length_mm = "Bill length (mm)",
bill_depth_mm = "Bill depth (mm)",
flipper_length_mm = "Flipper length (mm)",
body_mass_g = "Body mass (g)",
) |>
mutate(sex = factor(sex, labels = c("Female", "Male"))) |>
tidyr::drop_na(sex) set_blanket()The set_blanket() function should be run first.
This sets the default style of plots with themes and colours etc. It can be customised.
It should be run at the start of every script or quarto document.
gg_* function wraps a geomEach gg_* function wraps a
ggplot2::ggplot() function with the associated
ggplot2::geom_*() function.
Almost every geom in ggplot2 is wrapped.
Position related aesthetics can be added directly as arguments.
col argument to colour/fill by a
variableThe colour and fill aesthetics of ggplot2 are merged into a single
concept represented by the col argument.
This combined aesthetic means that all colour outlines and all fill
interiors should be coloured with the col_palette by the
col variable.
Use colour = NA or fill = NA to turn one of
these off.
facet argument to facet by a variableUsers provide an unquoted facet variable to facet
by.
When facet is specified, the facet_layout
will default to a "wrap" of the facet variable
(if facet2 = NULL).
facet2 argument to facet by a 2nd variableUsers can also provide an unquoted facet2 variable to
facet by.
When facet2 is specified, the facet_layout
will default to a "grid" of the facet variable
(horizontally) by the facet2 variable (vertically).
mapping argumentSome aesthetics are not available via an argument
(e.g. alpha, size, shape,
linetype and linewidth).
These can be accessed via the mapping argument using the
aes() function.
To customise associated scales/guides, + on the
applicable ggplot2 layer. In some situations, you may have to reverse
the values in the relevant scale etc.
Note you can use
set_blanket(geom_colour = lightness[1], ...) to make legend
symbols black if needed.
penguins2 |>
gg_jitter(
x = species,
y = flipper_length_mm,
col = island,
mapping = aes(shape = island),
) There are numerous arguments to customise plots that are prefixed by
whether they relate to x, y, col
or facet.
For x, y and col, these relate
to associated arguments within ggplot2 scales and guides. For
facet, they relate to associated arguments within
ggplot2::facet_wrap and
ggplot2::facet_grid.
Scales and guides associated with other other aesthetics can be customised by adding the applicable ggplot2 layer.
penguins2 |>
gg_jitter(
x = flipper_length_mm,
y = body_mass_g,
col = flipper_length_mm,
x_breaks = scales::breaks_extended(n = 4, only.loose = TRUE),
x_labels = \(x) stringr::str_sub(x, 1, 1),
y_expand_limits = 1000,
y_labels = label_number(big.mark = " "),
y_transform = "log10",
col_label = "Flipper\nlength (mm)",
col_steps = TRUE,
col_breaks = \(x) quantile(x, seq(0, 1, 0.25)),
col_palette = viridis::rocket(n = 9, direction = -1),
)*_label defaults for axis and legend
titlesThe x_label, y_label and
col_label for the axis and legend titles can be manually
specified with the applicable *_label argument (or
+ ggplot2::labs(...)).
If not specified, they will first take any label attribute associated with the applicable variable.
If none, they will then convert the variable name to a label name
using the label_to_case function, which defaults to
sentence case (i.e. snakecase::to_sentence_case).
ggplot2::geom_* arguments via
...The ... argument provides access to all other arguments
in the ggplot2::geom_*() function.
Common arguments to add include colour,
fill, alpha, linewidth,
linetype, size and width, which
enables fixing of these to a particular value.
Use the ggplot2::geom_* help to see what arguments are
available.
penguins2 |>
gg_smooth(
x = flipper_length_mm,
y = body_mass_g,
col = sex,
col_palette = c("#003f5c", "#ffa600"),
colour = "#bc5090",
linewidth = 1,
linetype = "dashed",
alpha = 1,
se = TRUE,
level = 0.999,
) *_mode_* themes with legend
variantslight_mode_*, grey_mode_* and
dark_mode_* theme families are provided with variants that
differ based on legend placement with suffix r (right),
b (bottom), t (top) and n
(none).
These themes were built for use with the mode
argument.
penguins2 |>
gg_histogram(
x = flipper_length_mm,
col = species,
title = "Penguin flipper length by species",
subtitle = "Palmer Archipelago, Antarctica",
caption = "Source: Gorman, 2020",
mode = grey_mode_t() + theme(legend.title = element_blank()),
) If not specified, the gg_* function will guess the plot
orientation (based on whether the y axis is discrete).
Where x_orientation = TRUE, it will:
mode theme.y_limits the range of y_breaks and (b)
y_expand = c(0, 0).The vice versa will occur for when
y_orientation = TRUE.
Note you can avoid all this by +-ing your theme on to
the gg_* output, and adding a
*_limits = c(NA, NA) argument (or
*_limits = c(0, NA) for bars).
p1 <- penguins2 |>
gg_jitter(
x = sex,
y = bill_depth_mm,
subtitle = "\nx_orientation = TRUE",
)
p2 <- penguins2 |>
gg_jitter(
x = bill_depth_mm,
y = sex,
subtitle = "\ny_orientation = TRUE",
)
p1 + p2geom_* layersUsers can make plots with multiple layers by adding on
ggplot2::geom_* layers.
Aesthetics directly added in the gg_* function are
globally inherited. Those added via the mapping argument
are only available locally to the layer associated with the
gg_* function.
It works best to add as many of the globally inherited aesthetics as
possible to the gg_* function.
The gg_*() function should also be appropriate to be the
bottom layer of the plot. You may sometimes need to use
gg_blanket() which defaults to a blank
geom.
penguins2 |>
group_by(species, sex) |>
summarise(
lower = quantile(flipper_length_mm, probs = 0.05),
upper = quantile(flipper_length_mm, probs = 0.95),
flipper_length_mm = mean(flipper_length_mm, na.rm = TRUE),
) |>
labelled::copy_labels_from(penguins2) |>
gg_col(
x = flipper_length_mm,
xmin = lower,
xmax = upper,
y = species,
col = sex,
position = position_dodge(),
width = 0.75,
) +
geom_errorbar(
width = 0.1,
position = position_dodge(width = 0.75),
colour = lightness[1],
) set_blanket()The set_blanket function sets customisable defaults for
the:
col = NULL for most
geoms)col = NULL
for other geoms often used for annotation)The ggplot2::update_geom_defaults() function can be used
to further fine-tune geom defaults.
set_blanket() also works on ggplot2 code.
set_blanket(
mode = dark_mode_r(),
geom_colour = "#e7298a",
annotate_colour = darkness[1],
col_palette_d = c("#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e",
"#e6ab02", "#a6761d", "#666666"), #RColorBrewer Dark2
)
p1 <- penguins2 |>
gg_point(
x = flipper_length_mm,
y = body_mass_g,
x_breaks = breaks_extended(n = 4, only.loose = TRUE),
) +
geom_vline(xintercept = 200) +
annotate("text", x = I(0.25), y = I(0.75), label = "Here")
p2 <- penguins2 |>
gg_histogram(
x = flipper_length_mm,
col = species,
x_breaks = breaks_extended(n = 4, only.loose = TRUE),
) +
geom_vline(xintercept = 200) +
annotate("text", x = I(0.75), y = I(0.75), label = "Here")
p1 + p2gg_blanket() function with geom
flexibilityThe package is driven by the gg_blanket function, which
has a geom argument with ggplot2::geom_blank
defaults for geom, stat and
position.
All other functions wrap this function with a fixed
geom, and their own default stat and
position arguments as per the applicable
geom_* function.
This function can often be used with geoms that do not have an
associated gg_* function.
expand.grid(x = 1:10, y = 1:10) |>
tibble() |>
mutate(angle = runif(100, 0, 2*pi)) |>
mutate(speed = runif(100, 0, sqrt(0.1 * x))) |>
gg_blanket(
geom = "spoke",
x = x,
y = y,
col = speed,
mapping = aes(angle = angle, radius = speed),
) +
geom_point()See the ggblanket website for further information, including articles and function reference.