ggplot2
allows to easily map a variable to marker
features of a scatterplot. This post
explaines how it works through several examples, with explanation
and code.
Here is the magick of ggplot2: the ability to
map a variable to marker features. Here, the marker
color
depends on its value in the field called
Species
in the input data frame.
Note that the legend is built automatically.
# load ggplot2
library(ggplot2)
library(hrbrthemes)
# mtcars dataset is natively available in R
# head(mtcars)
# A basic scatterplot with color depending on Species
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, color=Species)) +
geom_point(size=6) +
theme_ipsum()
You can map variables to any marker features. For instance, specie is represente below using transparency (left), shape (middle) and size (right).
# load ggplot2
library(ggplot2)
library(hrbrthemes)
# Transparency
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, alpha=Species)) +
geom_point(size=6, color="#69b3a2") +
theme_ipsum()
# Shape
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, shape=Species)) +
geom_point(size=6) +
theme_ipsum()
# Size
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, shape=Species)) +
geom_point(size=6) +
theme_ipsum()
Last but not least, note that you can map one or several variables
to one or several features. Here, shape, transparency, size and
color all depends on the marker Species
value.