ggplot2/_pkgdown.yml

293 lines
7.7 KiB
YAML

url: https://ggplot2.tidyverse.org
template:
package: tidytemplate
bootstrap: 5
includes:
in_header: |
<script defer data-domain="ggplot2.tidyverse.org,all.tidyverse.org" src="https://plausible.io/js/plausible.js"></script>
development:
mode: auto
authors:
Claus Wilke:
href: https://clauswilke.com
Kara Woo:
href: https://karawoo.com
Hiroaki Yutani:
href: https://yutani.rbind.io
Dewey Dunnington:
href: https://fishandwhistle.net
home:
links:
- text: Learn more
href: https://r4ds.had.co.nz/data-visualisation.html
- text: Extensions
href: https://exts.ggplot2.tidyverse.org/gallery/
reference:
- title: Plot basics
desc: >
All ggplot2 plots begin with a call to `ggplot()`, supplying default data and
aesthetic mappings, specified by `aes()`. You then add layers, scales,
coords and facets with `+`. To save a plot to disk, use `ggsave()`.
contents:
- ggplot
- aes
- "`+.gg`"
- ggsave
- qplot
- title: Layers
- subtitle: Geoms
desc: >
A layer combines data, aesthetic mapping, a geom (geometric object),
a stat (statistical transformation), and a position adjustment. Typically,
you will create layers using a `geom_` function, overriding the default
position and stat if needed.
contents:
- starts_with("geom_")
- subtitle: Stats
desc: >
A handful of layers are more easily specified with a `stat_` function,
drawing attention to the statistical transformation rather than the visual
appearance. The computed variables can be mapped using `after_stat()`.
contents:
- stat_ecdf
- stat_ellipse
- stat_function
- stat_identity
- stat_summary_2d
- stat_summary_bin
- stat_unique
- stat_sf_coordinates
- after_stat
- subtitle: Position adjustment
desc: >
All layers have a position adjustment that resolves overlapping geoms.
Override the default by using the `position` argument to the `geom_` or
`stat_` function.
contents:
- starts_with("position_")
- subtitle: Annotations
desc: >
Annotations are a special type of layer that don't inherit global settings
from the plot. They are used to add fixed reference data to plots.
contents:
- geom_abline
- annotate
- annotation_custom
- annotation_logticks
- annotation_map
- annotation_raster
- borders
- title: Aesthetics
desc: >
The following help topics give a broad overview of some of the ways
you can use each aesthetic.
contents:
- aes_colour_fill_alpha
- aes_group_order
- aes_linetype_size_shape
- aes_position
- title: Scales
desc: >
Scales control the details of how data values are translated to visual
properties. Override the default scales to tweak details like the axis
labels or legend keys, or to use a completely different translation from
data to aesthetic. `labs()` and `lims()` are convenient helpers for the
most common adjustments to the labels and limits.
contents:
- labs
- lims
- expand_limits
- expansion
- starts_with("scale_")
- get_alt_text
- title: "Guides: axes and legends"
desc: >
The guides (the axes and legends) help readers interpret your plots.
Guides are mostly controlled via the scale (e.g. with the `limits`,
`breaks`, and `labels` arguments), but sometimes you will need additional
control over guide appearance. Use `guides()` or the `guide` argument to
individual scales along with `guide_*()` functions.
contents:
- draw_key
- guide_colourbar
- guide_legend
- guide_axis
- guide_bins
- guide_coloursteps
- guide_none
- guides
- sec_axis
- title: Facetting
desc: >
Facetting generates small multiples, each displaying a different
subset of the data. Facets are an alternative to aesthetics for
displaying additional discrete variables.
contents:
- facet_grid
- facet_wrap
- vars
- subtitle: Labels
desc: >
These functions provide a flexible toolkit for controlling the display
of the "strip" labels on facets.
contents:
- labeller
- labellers
- label_value
- label_bquote
- title: Coordinate systems
desc: >
The coordinate system determines how the `x` and `y` aesthetics combine
to position elements in the plot. The default coordinate system is
Cartesian (`coord_cartesian()`), which can be tweaked with `coord_map()`,
`coord_fixed()`, `coord_flip()`, and `coord_trans()`, or completely
replaced with `coord_polar()`.
contents:
- coord_cartesian
- coord_fixed
- coord_flip
- coord_map
- coord_polar
- coord_trans
- title: Themes
desc: >
Themes control the display of all non-data elements of the plot. You
can override all settings with a complete theme like `theme_bw()`, or
choose to tweak individual settings by using `theme()` and the `element_`
functions. Use `theme_set()` to modify the active theme, affecting all
future plots.
contents:
- theme
- theme_bw
- theme_update
- element_line
- margin
- title: Programming with ggplot2
desc: >
These functions provides tools to help you program with ggplot2,
creating functions and for-loops that generate plots for you.
contents:
- aes_
- print.ggplot
- title: Extending ggplot2
desc: >
To create your own geoms, stats, scales, and facets, you'll need to learn
a bit about the object oriented system that ggplot2 uses. Start by
reading `vignette("extending-ggplot2")` then consult these functions
for more details.
contents:
- ggproto
- print.ggproto
- title: Vector helpers
desc: >
ggplot2 also provides a handful of helpers that are useful for creating
visualisations.
contents:
- cut_interval
- hmisc
- mean_se
- resolution
- title: Data
desc: >
ggplot2 comes with a selection of built-in datasets that are used in
examples to illustrate various visualisation challenges.
contents:
- diamonds
- economics
- faithfuld
- midwest
- mpg
- msleep
- presidential
- seals
- txhousing
- luv_colours
- title: Autoplot and fortify
desc: >
`autoplot()` is an extension mechanism for ggplot2: it provides a way
for package authors to add methods that work like the base `plot()`
function, generating useful default plots with little user interaction.
`fortify()` turns objects into tidy data frames: it has largely been
superseded by the [broom package](https://github.com/tidyverse/broom).
contents:
- autoplot
- autolayer
- fortify
- map_data
articles:
- title: Building plots
navbar: ~
contents:
- ggplot2-specs
- title: Developer
navbar: Developer
contents:
- extending-ggplot2
- ggplot2-in-packages
- profiling
- title: FAQ
navbar: FAQ
contents:
- articles/faq-axes
- articles/faq-faceting
- articles/faq-customising
- articles/faq-annotation
- articles/faq-reordering
- articles/faq-bars
news:
releases:
- text: "Version 3.4.0"
href: https://www.tidyverse.org/blog/2022/11/ggplot2-3-4-0/
- text: "Version 3.3.0"
href: https://www.tidyverse.org/blog/2020/03/ggplot2-3-3-0/
- text: "Version 3.2.0"
href: https://www.tidyverse.org/articles/2019/06/ggplot2-3-2-0/
- text: "Version 3.1.0"
href: https://www.tidyverse.org/articles/2018/10/ggplot2-3-1-0/
- text: "Version 3.0.0"
href: https://www.tidyverse.org/articles/2018/07/ggplot2-3-0-0/
- text: "Version 2.2.0"
href: https://posit.co/blog/ggplot2-2-2-0/
- text: "Version 2.1.0"
href: https://posit.co/blog/ggplot2-2-1-0/
- text: "Version 2.0.0"
href: https://posit.co/blog/ggplot2-2-0-0/
- text: "Version 1.0.0"
href: https://posit.co/blog/ggplot2-updates/
navbar:
structure:
left: [intro, reference, news, articles, extensions]
components:
extensions:
text: Extensions
href: https://exts.ggplot2.tidyverse.org/gallery/