| geom_polygon {ggplot2} | R Documentation |
Polygon, a filled path
geom_polygon(mapping=NULL, data=NULL, stat="identity", position="identity", ...)
mapping |
mapping between variables and aesthetics generated by aes |
data |
dataset used in this layer, if not specified uses plot dataset |
stat |
statistic used by this layer |
position |
position adjustment used by this layer |
... |
ignored |
This page describes geom_polygon, see layer and qplot for how to create a complete plot from individual components.
A layer
The following aesthetics can be used with geom_polygon. Aesthetics are mapped to variables in the data with the aes function: geom\_polygon(\code{aes}(x = var))
x: x position (required)
y: y position (required)
colour: border colour
fill: internal colour
size: size
linetype: line type
Hadley Wickham, http://had.co.nz/
geom_path: an unfilled polygon
geom_ribbon: a polygon anchored on the x-axis
## Not run:
# When using geom_polygon, you will typically need two data frames:
# one contains the coordinates of each polygon (positions), and the
# other the values associated with each polygon (values). An id
# variable links the two together
ids <- factor(c("1.1", "2.1", "1.2", "2.2", "1.3", "2.3"))
values <- data.frame(
id = ids,
value = c(3, 3.1, 3.1, 3.2, 3.15, 3.5)
)
positions <- data.frame(
id = rep(ids, each = 4),
x = c(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,
0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),
y = c(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,
2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)
)
# Currently we need to manually merge the two together
datapoly <- merge(values, positions, by=c("id"))
(p <- ggplot(datapoly, aes(x=x, y=y)) + geom_polygon(aes(fill=value, group=id)))
# Which seems like a lot of work, but then it's easy to add on
# other features in this coordinate system, e.g.:
stream <- data.frame(
x = cumsum(runif(50, max = 0.1)),
y = cumsum(runif(50,max = 0.1))
)
p + geom_line(data = stream, colour="grey30", size= 5)
# And if the positions are in longitude and latitude, you can use
# coord_map to produce different map projections.
## End(Not run)