With missing background in informatics I have difficulties to understand the differences between aes
and aes_string
in ggplot2 and its implications for daily usage.
From the description (?aes_string
) I was able to understand that both describe how variables in the data are mapped to visual properties (aesthetics) of geom
.
Furthermore it is said that aes uses non-standard evaluation to capture the variable names.
whereas aes_string
uses regular evaluation
.
From example code it is clear that both produce the same output (a list of unevaluated expressions
):
> aes_string(x = "mpg", y = "wt") List of 2 $ x: symbol mpg $ y: symbol wt > aes(x = mpg, y = wt) List of 2 $ x: symbol mpg $ y: symbol wt
Non-standard evaluation
is described by Hadley Wickham in his book Advanced R as a method to not only call the values of a functions argument but also the code that produced them.
I would assume that regular evaluation
in opposition only calls the values from the function, but I did not find a source to confirm this assumption. Furthermore it is unclear to me how those two differ and why this should be relevant to me when I use the package.
On the inside-R website it is mentioned that aes_string is particularly useful when writing functions that create plots because you can use strings to define the aesthetic mappings, rather than having to mess around with expressions.
But in that sense it is unclear to me why I should ever use aes
and not opt always for aes_string
whenever using ggplot2
... In that sense it would help me to find some clarifications on those concepts and a practical hint for daily usage.
aes() is a quoting function. This means that its inputs are quoted to be evaluated in the context of the data. This makes it easy to work with variables from the data frame because you can name those directly. The flip side is that you have to use quasiquotation to program with aes() .
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() .
aes
saves you some typing as you don't need the quotes. That is all. You are of course free to always use aes_string
. You should use aes_string
if you want to pass the variable names programmatically.
Internally aes
uses match.call
for the non-standard evaluation. Here is a simple example for illustration:
fun <- function(x, y) as.list(match.call()) str(fun(a, b)) #List of 3 # $ : symbol fun # $ x: symbol a # $ y: symbol b
For comparison:
library(ggplot2) str(aes(x = a, y = b)) #List of 2 # $ x: symbol a # $ y: symbol b
The symbols are evaluated at a later stage.
aes_string
uses parse
to achieve the same:
str(aes_string(x = "a", y = "b")) #List of 2 # $ x: symbol a # $ y: symbol b
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