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ggplot2
ShortcutsThis package allows easy access to some common ggplot2
tasks.
Rotating the x
axis labels is a very frequently looked
up task, and we can make it easier. If we create a simple
ggplot2
plot
then by default, this looks like
We can perform various rotations though
p1 <- p +
easy_rotate_x_labels() +
labs(title = "default rotation")
p2 <- p +
easy_rotate_x_labels(angle = 45, side = "right") +
labs(title = "angle = 45")
p3 <- p +
easy_rotate_x_labels("startattop") +
labs(title = "text starts at top")
p4 <- p +
easy_rotate_x_labels("startatbottom") +
labs(title = "text starts at bottom")
(p1 + p2) / (p3 + p4)
Removing legends is made easier by the
easy_remove_legend
function. When called without arguments,
all legends are removed (equivalent to
theme(legend.position = "none")
). Alternatively, the names
of aesthetics for which legends should be removed can be passed.
p <- ggplot(mtcars, aes(wt, mpg, colour = cyl, size = hp)) +
geom_point()
p1 <- p +
labs(title = "With all legends")
p2 <- p +
easy_remove_legend() +
labs(title = "Remove all legends")
p3 <- p +
easy_remove_legend(size) +
labs(title = "Remove size legend")
p4 <- p +
easy_remove_legend(size, color) +
labs(title = "Remove both legends specifically")
(p1 + p2) / (p3 + p4)
Grid lines can be completely removed, or removed in only one direction
p <- ggplot(mtcars, aes(hp, mpg)) + geom_point()
p1 <- p + easy_remove_gridlines() +
labs(title = "Remove all gridlines")
p2 <- p + easy_remove_gridlines(major = FALSE) +
labs(title = "Remove minor gridlines")
p3 <- p + easy_remove_gridlines(minor = FALSE) +
labs(title = "Remove minor gridlines")
p4 <- p + easy_remove_x_gridlines() +
labs(title = "Remove x gridlines")
# or
# p + easy_remove_gridlines(axis = "x")
# p + easy_remove_y_gridlines()
(p1 + p2) / (p3 + p4)
Changing plot labels to a specified string isn’t particularly
difficult (labs(x = "my label")
) but wouldn’t it be even
nicer if you could just add labels to your data.frame
columns (e.g. using labelled::var_labels()
) and have these
reflected in your plot. easy_labs()
makes this
possible.
## create a copy of the iris data
iris_labs <- iris
## add labels to the columns
lbl <- c('Sepal Length', 'Sepal Width', 'Petal Length', 'Petal Width', 'Flower\nSpecies')
var_label(iris_labs) <- split(lbl, names(iris_labs))
These are visible if you use View(iris_labs)
in
RStudio
p <- ggplot(iris_labs, aes(x = Sepal.Length, y = Sepal.Width)) +
geom_line(aes(colour = Species))
p1 <- p + labs(title = "default labels")
p2 <- p +
easy_labs() +
labs(title = "Replace titles with column labels")
p3 <- p +
easy_labs(x = 'My x axis') +
labs(title = "Manually add x axis label")
iris_labs_2 <- iris_labs
var_label(iris_labs_2$Species) <- "Sub-genera"
p4 <- p + geom_point(data = iris_labs_2, aes(fill = Species), shape = 24) +
easy_labs() +
labs(title = "Additional labels can be added in other aesthetics")
(p1 + p2) / (p3 + p4)
easy_labs also extends to facetting
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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