Where do R's supportive members mainly come from?

r-supportive-members

library(pipeR) # https://github.com/renkun-ken/pipeR
library(rlist) # https://github.com/renkun-ken/rlist
library(rvest) # https://github.com/hadley/rvest
library(stringr) # https://github.com/hadley/stringr
# please ensure rvest is the latest dev version

Pipe("http://www.r-project.org/foundation/memberlist.html")$
  html()$ # use xpath to scrape the name list
  html_nodes(xpath = "//table[2]//td//text() | //table[3]//td//text()")$
  html_text(trim = TRUE)$
  str_match_all(".+\\s\\((.+)\\)")$ # select their nations
  list.rbind()[,2]$ # combine to matrix and select nation column
  str_split(", ")$ # some members have multiple nationalities
  unlist()$
  table()$
  sort(decreasing = TRUE)$
  head(10)$
  barplot(main = "Where do R's supportive members mainly come from?")

If you really want to maintain the mainstream pipeline (plotting the chart) and branch it with a map, the following code works:

library(pipeR) # https://github.com/renkun-ken/pipeR
library(rlist) # https://github.com/renkun-ken/rlist
library(rvest) # https://github.com/hadley/rvest
library(stringr) # https://github.com/hadley/stringr
library(choroplethr)

ptable <- Pipe("http://www.r-project.org/foundation/memberlist.html")$
  html()$ # use xpath to scrape the name list
  html_node(xpath = "//table[2]//td//text() | //table[3]//td//text()")$
  html_text(trim = TRUE)$
  str_match_all(".+\\s\\((.+)\\)")$ # select their nations
  list.rbind()[,2]$ # combine to matrix and select nation column
  str_split(", ")$ # some members have multiple nationalities
  unlist()$
  table()$
  .(~ Pipe(.)$
      data.frame()$
      setNames(c("region","value"))$
      choroplethr("world") -> map)$
  sort(decreasing = TRUE)$
  head(10)$
  barplot(main = "Where do R's supportive members mainly come from?")$
  .(~ print(map))

This requires pipeR v0.5 to allow -> for assignment or otherwise you can only use less elegant = :)

Thanks very much
Yes Ari has done a good job on choroplethr and it works in shiny and rmarkdown which I don't believe some of the attractive rMaps options do. There is also a prob with country aliases e.g UK in my example