--- title: "README" author: "Bob Rudis" date: January 30, 2015 output: md_document: variant: markdown_github --- 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](https://github.com/hrbrmstr/statebins/issues/2)] and fixed a bug[[2](https://github.com/hrbrmstr/statebins/issues/3)] 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](https://github.com/hrbrmstr/statebins/pull/1) by [hansthompson](https://github.com/hansthompson) - Version `1.0.0` released ### Installation ```{r eval=FALSE} devtools::install_github("hrbrmstr/statebins") ``` ```{r echo=FALSE, message=FALSE, warning=FALSE, error=FALSE} options(width=120) ``` ### Usage All of the following examples use the [WaPo data](http://www.washingtonpost.com/wp-srv/special/business/states-most-threatened-by-trade/states.csv?cache=1). 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). ```{r message=FALSE} library(statebins) # current verison packageVersion("statebins") # 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") gg # 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") gg2 # 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") gg3 # 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)") # 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") # 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") # 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) } ``` ```{r eval=FALSE} # cheating and using 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: ```{r eval=FALSE} # 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 ```{r} library(statebins) library(testthat) date() test_dir("tests/") ```