aes_: Define aesthetic mappings programmatically

In ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics

Define aesthetic mappings programmatically

Description

Aesthetic mappings describe how variables in the data are mapped to visual properties (aesthetics) of geoms. aes() uses non-standard evaluation to capture the variable names. aes_() and aes_string() require you to explicitly quote the inputs either with "" for aes_string(), or with quote or ~ for aes_(). (aes_q() is an alias to aes_()). This makes aes_() and aes_string() easy to program with.

aes_string() and aes_() are particularly useful when writing functions that create plots because you can use strings or quoted names/calls to define the aesthetic mappings, rather than having to use substitute() to generate a call to aes().

I recommend using aes_(), because creating the equivalents of aes(colour = "my colour") or aes(x = `X$1`) with aes_string() is quite clunky.

Usage

aes_(x, y, ...)

aes_string(x, y, ...)

aes_q(x, y, ...)

Arguments

x, y, ...

List of name value pairs. Elements must be either quoted calls, strings, one-sided formulas or constants.

Life cycle

All these functions are soft-deprecated. Please use tidy evaluation idioms instead. Regarding aes_string(), you can replace it with .data pronoun. For example, the following code can achieve the same mapping as aes_string(x_var, y_var).

x_var <- "foo"
y_var <- "bar"
aes(.data[[x_var]], .data[[y_var]])

For more details, please see vignette("ggplot2-in-packages").

See Also

aes()

ggplot2 documentation built on June 22, 2024, 11:35 a.m.