geom_abline(mapping = NULL, data = NULL, stat = "abline",
position = "identity", show_guide = FALSE, ...)FALSE)aes or aes_string. Only
needs to be set at the layer level if you are overriding
the plot defaults.# Fixed slopes and intercepts 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) p + geom_abline(intercept = 10, colour = "red", size = 2)
# See ?stat_smooth for fitting smooth models to data p + stat_smooth(method="lm", se=FALSE)
# Slopes and intercepts as data p <- ggplot(mtcars, aes(x = wt, y=mpg), . ~ cyl) + geom_point() df <- data.frame(a=rnorm(10, 25), b=rnorm(10, 0)) p + geom_abline(aes(intercept=a, slope=b), data=df)
# Slopes and intercepts from linear model library(plyr) coefs <- ddply(mtcars, .(cyl), function(df) { m <- lm(mpg ~ wt, data=df) data.frame(a = coef(m)[1], b = coef(m)[2]) }) str(coefs) p + geom_abline(data=coefs, aes(intercept=a, slope=b))
# It's actually a bit easier to do this with stat_smooth p + geom_smooth(aes(group=cyl), method="lm") p + geom_smooth(aes(group=cyl), method="lm", fullrange=TRUE)
# With coordinate transforms p + geom_abline(intercept = 37, slope = -5) + coord_flip() p + geom_abline(intercept = 37, slope = -5) + coord_polar()
stat_smooth to add lines derived from the
data, geom_hline for horizontal lines,
geom_vline for vertical lines
geom_segmentgeom_hline and
geom_vline, it's useful for annotating plots. You
can supply the parameters for geom_abline, intercept and
slope, in two ways: either explicitly as fixed values, or
in a data frame. If you specify the fixed values
(geom_abline(intercept=0, slope=1)) then the line
will be the same in all panels. If the intercept and
slope are stored in the data, then they can vary from
panel to panel. See the examples for more ideas.