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README.md

statebins

statebins - U.S. State Cartogram Heatmaps in R; an alternative to choropleth maps for USA States

The following functions are implemented:

  • statebins - creates "statebin" charts in the style of http://bit.ly/statebins - This version uses discrete RColorBrewer scales, binned by the "breaks" parameter.
  • statebins_continuous - creates "statebin" charts in the style of http://bit.ly/statebins - This version uses a continuous scale based on RColorBrewer scales (passing in a 6 element RColorBrewer palette to scale_fill_gradientn).
  • statebins_manual - creates "statebin" charts using manually specified colors in a column

TODO

  • The current version is usable, but I think the plot margins and the legends need work
  • Apply algorithm to switch to light-on-dark depending on the background tile color

News

  • Version 1.2.1 released - Added support for PR/Puerto Rico[1] and fixed a bug[2] when using anything but a data.frame as input. Also no longer fails (deals with the following but with a warning) when duplicate states are in the input data or invalid states are in the input data.
  • Version 1.1.0 released - statebins_manual() for manual placement of colors and moving of AK in support of a pull request by hansthompson
  • Version 1.0.0 released

Installation

devtools::install_github("hrbrmstr/statebins")

Usage

All of the following examples use the WaPo data. It looks like the columns they use are scaled data and I didn't take the time to figure out what they did, so the final figure just mimics their output (including the non-annotated legend).

library(statebins)

# current verison
packageVersion("statebins")
## [1] '1.2.2'
# the original wapo data

dat <- read.csv("http://www.washingtonpost.com/wp-srv/special/business/states-most-threatened-by-trade/states.csv?cache=1", stringsAsFactors=FALSE)

gg <- statebins(dat, "state", "avgshare94_00", breaks=4, 
                labels=c("0-1", "1-2", "2-3", "3-4"),
                legend_title="Share of workforce with jobs lost or threatened by trade", font_size=3, 
                brewer_pal="Blues", text_color="black", 
                plot_title="1994-2000", title_position="bottom")
## Warning: `show_guide` has been deprecated. Please use `show.legend` instead.
gg
## TableGrob (2 x 1) "arrange": 2 grobs
##     z     cells    name              grob
##     1 (1-1,1-1) arrange    gtable[layout]
## sub 2 (2-2,1-1) arrange text[GRID.text.1]
# continuous scale, legend on top

gg2 <- statebins_continuous(dat, "state", "avgshare01_07",
                            legend_title="Share of workforce with jobs lost or threatened by trade", legend_position="top",
                            brewer_pal="OrRd", text_color="black", font_size=3, 
                            plot_title="2001-2007", title_position="bottom")
## Warning: `show_guide` has been deprecated. Please use `show.legend` instead.
gg2
## TableGrob (2 x 1) "arrange": 2 grobs
##     z     cells    name               grob
##     1 (1-1,1-1) arrange     gtable[layout]
## sub 2 (2-2,1-1) arrange text[GRID.text.53]
# continuous scale, no legend

gg3 <- statebins_continuous(dat, "state", "avgshare08_12",
                            legend_title="States", legend_position="none",
                            brewer_pal="Purples", text_color="black", font_size=3, 
                            plot_title="2008-2012", title_position="bottom")
## Warning: `show_guide` has been deprecated. Please use `show.legend` instead.
gg3
## TableGrob (2 x 1) "arrange": 2 grobs
##     z     cells    name               grob
##     1 (1-1,1-1) arrange     gtable[layout]
## sub 2 (2-2,1-1) arrange text[GRID.text.89]
# mortality (only to show PR and using a data.table)
# from: http://www.cdc.gov/nchs/fastats/state-and-territorial-data.htm

dat <- data.table::fread("http://dds.ec/data/deaths.csv")
statebins_continuous(dat, "state", "death_rate", legend_title="Per 100K pop",
                    plot_title="Mortality Rate (2010)")
## Warning: `show_guide` has been deprecated. Please use `show.legend` instead.
## TableGrob (2 x 1) "arrange": 2 grobs
##     z     cells    name                grob
##     1 (1-1,1-1) arrange      gtable[layout]
## sub 2 (2-2,1-1) arrange text[GRID.text.117]
# fertility (only to show tbl_dt)

dat <- dplyr::tbl_dt(dat)
statebins_continuous(dat, "state", "fertility_rate", legend_title="Per 100K pop", 
                     plot_title="Fertility Rate (2010)", brewer_pal="PuBuGn")
## Warning: `show_guide` has been deprecated. Please use `show.legend` instead.
## TableGrob (2 x 1) "arrange": 2 grobs
##     z     cells    name                grob
##     1 (1-1,1-1) arrange      gtable[layout]
## sub 2 (2-2,1-1) arrange text[GRID.text.153]
# manual - perhaps good for elections?

library(httr)
library(dplyr)
election_2012 <- GET("https://raw.githubusercontent.com/hrbrmstr/statebins/master/tmp/election2012.csv")
results <- read.csv(textConnection(content(election_2012, as="text")), header=TRUE, stringsAsFactors=FALSE)
results <- results %>% mutate(color=ifelse(is.na(Obama), "#2166ac", "#b2182b")) %>% select(state, color)
results %>% statebins_manual(font_size=4, text_color = "white", labels=c("Romney", "Obama"), legend_position="right", legend_title="Winner")
## Warning: `show_guide` has been deprecated. Please use `show.legend` instead.

# or, more like the one in the WaPo article; i might be picking the wrong columns here. it's just for an example

sb <- function(col, title) {
  statebins(dat, "state",col, brewer_pal="Blues", text_color="black", legend_position="none", font_size=3, plot_title=title, breaks=4, labels=1:4)
}
# cheating and using <table> to arrange them below and also making a WaPo-like legend, 
# since mucking with grid graphics margins/padding was not an option time-wise at the moment

sb("avgshare94_00", "1994-2000")
sb("avgshare01_07", "2001-2007")
sb("avgshare08_12", "2008-2012")
![img](./tmp/statebins-composite.png)

And, we'll throw in a gratuitous animation for good measure:

# data set from StatsAmerica - http://www.statsamerica.org/profiles/sip_index.html

# median household income from the ACS survey
miacs <- read.csv("http://dds.ec/data/median-income-acs.csv", header=TRUE, stringsAsFactors=FALSE)

# generate frames based on year
sapply(unique(miacs$year), function(year) {
  
  png(file=sprintf("tmp/household%d.png", year),
      type="quartz", antialias="subpixel", width=800, height=600)
  
  rng <- floor(range(miacs[miacs$year==year,]$mh_inc))
  
  ggtmp <- statebins(miacs[miacs$year==year,], "state", "mh_inc",
                   legend_title="States", legend_position="none",
                   brewer_pal="Greens", text_color="black", font_size=3,
                   plot_title=sprintf("Median Household Income (ACS) %d\n$%s - $%s", year, comma(rng[1]), comma(rng[2])), title_position="top")
  
  print(ggtmp)
  
  dev.off()
  
})

# animate them with ImageMagick
system("convert -background white -alpha remove -layers OptimizePlus -delay 150 tmp/*.png -loop 1 tmp/household.gif")
![img](./tmp/household.gif)

Test Results

library(statebins)
library(testthat)

date()
## [1] "Mon Dec 21 08:21:03 2015"
test_dir("tests/")
## testthat results ========================================================================================================
## OK: 0 SKIPPED: 0 FAILED: 0