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 = 0.5, ...)
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)