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)
NULL, the default, the data is inherited from the plot
data as specified in the call to
data.frame, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify for which variables will be created.
function will be called with a single argument,
the plot data. The return value must be a
will be used as the layer data.
layer. These are often aesthetics, used to set an aesthetic to a fixed value, like
color = "red"or
size = 3. They may also be parameters to the paired geom/stat.
FALSE(the default), removes missing values with a warning. If
TRUEsilently removes missing values.
NA, the default, includes if any aesthetics are mapped.
FALSEnever includes, and
geom_lineso support the same aesthetics: alpha, colour, linetype and size. They also each have aesthetics that control the position of the line:
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.
geom_segmentfor 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)