geom_abline | R Documentation |
These paired geoms and stats add straight lines to a plot, either horizontal, vertical or specified by slope and intercept. These are useful for annotating plots.
geom_abline(
mapping = NULL,
data = NULL,
...,
slope,
intercept,
na.rm = FALSE,
show.legend = NA
)
geom_hline(
mapping = NULL,
data = NULL,
...,
yintercept,
na.rm = FALSE,
show.legend = NA
)
geom_vline(
mapping = NULL,
data = NULL,
...,
xintercept,
na.rm = FALSE,
show.legend = NA
)
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
... |
other arguments passed on to |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
xintercept, yintercept, slope, intercept |
Parameters that control the
position of the line. If these are set, |
These geoms act slightly different to other geoms. You can supply the
parameters in two ways: either as arguments to the layer function,
or via aesthetics. If you use arguments, e.g.
geom_abline(intercept = 0, slope = 1)
, then behind the scenes
the geom makes a new data frame containing just the data you've supplied.
That means that the lines will be the same in all facets; if you want them
to vary across facets, construct the data frame yourself and use aesthetics.
Unlike most other geoms, these geoms do not inherit aesthetics from the plot default, because they do not understand x and y aesthetics which are commonly set in the plot. They also do not affect the x and y scales.
These geoms are drawn using with geom_line
so support the
same aesthetics: alpha, colour, linetype and size. They also each have
aesthetics that control the position of the line:
geom_vline
: xintercept
geom_hline
: yintercept
geom_abline
: slope
and intercept
See geom_segment
for a more general approach to
adding straight line segments to a plot.
p <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
# Fixed values
p + geom_vline(xintercept = 5)
p + geom_vline(xintercept = 1:5)
p + geom_hline(yintercept = 20)
p + geom_abline() # Can't see it - outside the range of the data
p + geom_abline(intercept = 20)
# Calculate slope and intercept of line of best fit
coef(lm(mpg ~ wt, data = mtcars))
p + geom_abline(intercept = 37, slope = -5)
# But this is easier to do with geom_smooth:
p + geom_smooth(method = "lm", se = FALSE)
# To show different lines in different facets, use aesthetics
p <- ggplot(mtcars, aes(mpg, wt)) +
geom_point() +
facet_wrap(~ cyl)
mean_wt <- data.frame(cyl = c(4, 6, 8), wt = c(2.28, 3.11, 4.00))
p + geom_hline(aes(yintercept = wt), mean_wt)
# You can also control other aesthetics
ggplot(mtcars, aes(mpg, wt, colour = wt)) +
geom_point() +
geom_hline(aes(yintercept = wt, colour = wt), mean_wt) +
facet_wrap(~ cyl)
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