| mapplot {latticeExtra} | R Documentation |
Produces Trellis displays of numeric (and eventually categorical) data on a map. This is largely meant as a demonstration, and users looking for serious map drawing capabilities should look elsewhere (see below).
mapplot(x, data, ...)
## S3 method for class 'formula':
mapplot(x, data, map, outer = TRUE,
prepanel = prepanel.mapplot,
panel = panel.mapplot,
aspect = "iso",
legend = NULL,
breaks, cuts = 30,
colramp = colorRampPalette(brewer.pal(n = 11, name = "Spectral")),
colorkey = TRUE,
...)
prepanel.mapplot(x, y, map, ...)
panel.mapplot(x, y, map, breaks, colramp, lwd = 0.01, ...)
x, y |
For mapplot, an object on which method dispatch is
carried out. For the formula method, a formula of the form y
~ x, with additional conditioning variables as desired. The
extended form of conditioning using y ~ x1 + x2 etc. is also
allowed. The formula might be interpreted as in a dot plot, except
that y is taken to be the names of geographical units in
map.
Suitable subsets (packets) of x and y are passed to
the prepanel and panel functions.
|
data |
A data source where names in the formula are evaluated |
map |
An object of class "map" (package maps),
containing boundary information. The names of the geographical
units must match the y variable in the formula. |
outer |
logical; how variables separated by + in the
formula are interpreted. It is not advisable to change the
default. |
prepanel, panel |
the prepanel and panel functions |
aspect |
aspect ratio |
breaks, cuts, colramp |
controls conversion of numeric x
values to a false colo. colramp may be a vector of colors or
a function that produces colors (such as cm.colors) |
legend, colorkey |
controls legends; usually just a color key
giving the association between numeric values of x and
color. |
lwd |
line width |
... |
Further arguments passed on to the underlying engine.
See xyplot for details. |
An object of class "trellis".
This function is meant to demonstrate how maps can be incorporated in a Trellis display. Users seriously interested in geographical data should consider using software written by people who know what they are doing.
Deepayan Sarkar
http://en.wikipedia.org/wiki/Choropleth_map
library(maps)
library(mapproj)
data(USCancerRates)
mapplot(rownames(USCancerRates) ~ log(rate.male) + log(rate.female),
data = USCancerRates,
map = map("county", plot = FALSE, fill = TRUE,
projection = "mercator"))
mapplot(rownames(USCancerRates) ~ log(rate.male) + log(rate.female),
data = USCancerRates,
map = map("county", plot = FALSE, fill = TRUE,
projection = "tetra"),
scales = list(draw = FALSE))
data(ancestry)
county.map <-
map('county', plot = FALSE, fill = TRUE,
projection = "azequalarea")
mapplot(county ~ log10(population), ancestry, map = county.map)
## Not run:
## this may take a while (should get better area records)
county.areas <-
area.map(county.map, regions = county.map$names, sqmi = FALSE)
ancestry$density <-
with(ancestry, population / county.areas[as.character(county)])
mapplot(county ~ log(density), ancestry,
map = county.map, border = NA,
colramp = colorRampPalette(c("white", "black")))
## End(Not run)