Alaska and Hawaii can be found in the 'world' or 'world2' databases of the 'maps' package. The following is a bit a hack but it works
---- library(maps) library(scales) mergeMaps <- function(...) { maps <- list(...) if (length(maps) < 2) stop("need at least two maps") map <- maps[[1]] for (i in 2:length(maps)) { map$x <- c(map$x, NA, maps[[i]]$x) map$y <- c(map$y, NA, maps[[i]]$y) map$names <- c(map$names, maps[[i]]$names) } map$range <- c(range(map$x, na.rm = TRUE), range(map$y, na.rm = TRUE)) map } shiftMap <- function(map, xmin=-180) { sel <- !is.na(map$x) map$x <- (map$x - xmin) %% 360 + xmin map$range <- c(range(map$x, na.rm = TRUE), range(map$y, na.rm = TRUE)) map } m <- shiftMap(mergeMaps(map('state', fill=TRUE, plot=FALSE), map('world', 'USA:Alaska', fill=TRUE, plot=FALSE), map('world', 'Hawaii', fill=TRUE, plot=FALSE)), xmin=0) s_data <- tolower(rownames(USArrests)) s_map <- tolower(m$names) mapping <- lapply(s_data, function(state) { which(grepl(state, s_map)) }) ## check if the mapping is good! col_pal <- col_numeric("Greens", domain=NULL, na.color = 'lightyellow') cols <- rep('lightyellow', length(s_data)) Map(function(indices, col) { cols[indices] <<- col }, mapping, col_pal(USArrests$UrbanPop)) map(m, col=cols, fill=TRUE) # map.axexs() ## or with no borders map(m, col=cols, fill=TRUE, border=NA) ---- Greetings, Adrian On Fri, Dec 11, 2015 at 1:22 AM, Benjamin Tyner <bty...@gmail.com> wrote: > Very nice Adrian. Is there a straightforward way to add Alaska and Hawaii at > the lower left? (without resorting to choroplethr package) > > > On 12/10/2015 06:09 AM, Adrian Waddell wrote: >> >> Hi, >> >> You can also use the 'maps' package for the map data and the 'scales' >> package for the color mapping. >> >> E.g. >> >> library(maps) >> library(scales) >> >> m <- map('state', fill=TRUE, plot=FALSE) >> >> s_data <- tolower(rownames(USArrests)) >> s_map <- tolower(m$names) >> >> mapping <- lapply(s_data, function(state) { >> which(grepl(state, s_map)) >> }) >> ## check if the mapping is good! >> >> col_pal <- col_numeric("Greens", domain=NULL, na.color = 'lightyellow') >> >> cols <- rep('lightyellow', length(s_data)) >> >> Map(function(indices, col) { >> cols[indices] <<- col >> }, mapping, col_pal(USArrests$UrbanPop)) >> >> map(m, col=cols, fill=TRUE) >> >> >> Adrian >> >> >> >> On Mon, Dec 7, 2015 at 9:34 AM, Erich Neuwirth >> <erich.neuwi...@univie.ac.at> wrote: >>> >>> ggplot2 also can do this with >>> fortify >>> geom_polygon >>> >>> Von meinem iPad gesendet >>> >>>> Am 06.12.2015 um 21:03 schrieb Benjamin Tyner <bty...@gmail.com>: >>>> >>>> Hi >>>> >>>> I wish to draw a basic choropleth (US, by state) and am wondering if >>>> anyone has any recommendations? I've tried the following thus far: >>>> >>>> 1. choroplethr: this works, but required installation of 30+ >>>> dependencies. I would prefer something with fewer dependencies. >>>> 2. tmap: this also seems promising, but most of the examples I saw were >>>> specific to European maps. Can it be adapted for US? >>>> 3. statebins: doesn't draw true choropleths, but I liked that it doesn't >>>> have many dependencies. >>>> >>>> Regards >>>> Ben >>>> >>>> ______________________________________________ >>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>> PLEASE do read the posting guide >>>> http://www.R-project.org/posting-guide.html >>>> and provide commented, minimal, self-contained, reproducible code. >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.