= R ggplot2 =

'''ggplot2''' is a package for plotting and other data visualization tasks.

<<TableOfContents>>

----



== Installation ==

`ggplot2` is a part of the [[R/Tidyverse|tidyverse]] collection. 

----



== Usage ==

The core `ggplot` function returns a `ggplot` object. This object does nothing on its own; geometry functions must be applied by 'adding' to the object.

As a basic example:

{{{
library(tidyverse)

ggplot(data = df, mapping = aes(x = foo, y = bar)) + geom_point() + geom_smooth()
}}}

Geometry function include:

 * `geom_point()`
 * `geom_smooth()`
   * The `method` option determines how the line is calculated.
   * If unset and if there are fewer than 1,000 cases, [[Statistics/LocallyEstimatedScatterplotSmoothing|LOESS]] is used. If unset and if there are 1,000 cases or more, [[Statistics/GeneralizedAdditiveModel|GAM]] is used.
   * Other available options include `"lm"` and `"glm"`.
 * `geom_abline(intercept=A, slope=B)`
 * `geom_hline(yintercept=Y)
 * `geom_vline(xintercept=X)
   * Can pass a vector to add multiple lines.



=== Aesthetic Mappings ===

The `aes` option creates an aesthetic `mapping` object. The main point of this function call is to standardize property names. For example, `color`, `colour`, `col`, and `fg` are all coerced to the same property name. The `mapping` option can be specified for either the `ggplot` function for global properties, or for a geometry function for local properties. Consider:

{{{
ggplot(data = df, mapping = aes(x = foo, y = bar)) + geom_point(aes(color="blue")) + geom_smooth(aes(color="red"))
}}}

The `aes` function can also evaluate functions of vectors, like:

{{{
aes(x = foo/bar, y = baz^2)
}}}

Note however that the function eagerly evaluates properties, so tricks have to be used if attempting to abstract the function call, as by a macro.

----



== Theming ==

'''Themes''' are used to customize the appearance of a graph. They are applied to a `ggplot` object with the addition (`+`) operator.

{{{
library(tidyverse)
ggplot(data = DATA, mapping = aes(MAPPINGS)) +  GEOM_FUNC() + THEME_OBJ
}}}



=== Theme Objects ===

A set of default themes are built into the `ggplot2` package and accessible from functions:

 * `theme_grey()`
 * `theme_gray()`
 * `theme_bw()`
 * `theme_linedraw()`
 * `theme_light()`
 * `theme_dark()`
 * `theme_minimal()`
 * `theme_classic()`
 * `theme_void()`
 * `theme_test()`

Alternatively, construct a new theme using the `theme` function.

{{{
ggplot(data = df, mapping = aes(x = foo, y = bar)) + mytheme
}}}

A common strategy is to use one of the above default themes as a starting point and then to apply customizations.

{{{
ggplot(data = df, mapping = aes(x = foo, y = bar)) + theme_minimal() + mytheme
}}}



=== Options ===

To set the font for a graph's text:

{{{
mytheme <- theme(text = element_text(family = "DejaVu"))
}}}

To enlarge the title:

{{{
mytheme <- theme(plot.title = element_text(size = 20))
}}}

Note that targetting `title` instead of `plot.title` would affect the size of ''all'' title-like objects (e.g. axes labels, legend title, and so on).

To rotate the x-axis labels 90 degrees:

{{{
mytheme <- theme(axis.text.x = element_text(angle = 90, hjust = 0.5, vjust = 0.5))
}}}

To color the y-axis labels:

{{{
mytheme <- theme(axis.text.y = element_text(colour = "grey20"))
}}}

To italicize the group titles in a faceted plot:

{{{
mytheme <- theme(strip.text = element_text(face = "italic"))
}}}

----



== See also ==

[[https://ggplot2.tidyverse.org/reference/index.html|ggplot2 package reference]]



----
CategoryRicottone