# geom_abline

##### Line specified by slope and intercept.

The abline geom adds a line with specified slope and intercept to the plot.

##### Usage

```
geom_abline(mapping = NULL, data = NULL, stat = "abline",
position = "identity", show_guide = FALSE, ...)
```

##### Arguments

- mapping
- The aesthetic mapping, usually constructed with
`aes`

or`aes_string`

. Only needs to be set at the layer level if you are overriding the plot defaults. - data
- A layer specific dataset - only needed if you want to override the plot defaults.
- stat
- The statistical transformation to use on the data for this layer.
- position
- The position adjustment to use for overlapping points on this layer
- show_guide
- should a legend be drawn? (defaults to
`FALSE`

) - ...
- other arguments passed on to
`layer`

. This can include aesthetics whose values you want to set, not map. See`layer`

for more details.

##### Details

With its siblings `geom_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.

##### Aesthetics

# 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_segment`

*Documentation reproduced from package ggplot2, version 1.0.1, License: GPL-2*