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# statebins
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Create ‘U.S.’ Uniform Square State Cartogram Heatmaps
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## What’s in the tin?
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The following functions are implemented:
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- `statebins`: Creates “statebin” charts in the style of
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<http://bit.ly/statebins>
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- `theme_statebins`: Base statebins theme
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## Installation
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``` r
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devtools::install_github("hrbrmstr/statebins")
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```
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## Usage
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All of the following examples use the [WaPo
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data](http://www.washingtonpost.com/wp-srv/special/business/states-most-threatened-by-trade/states.csv?cache=1).
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It looks like the columns they use are scaled data and I didn’t take the
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time to figure out what they did, so the final figure just mimics their
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output (including the non-annotated legend).
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``` r
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library(statebins)
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library(tidyverse)
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# current verison
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packageVersion("statebins")
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```
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## [1] '1.3.0'
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``` r
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# the original wapo data
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adat <- suppressMessages(read_csv(system.file("extdata", "wapostates.csv", package="statebins")))
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mutate(
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adat,
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share = cut(avgshare94_00, breaks = 4, labels = c("0-1", "1-2", "2-3", "3-4"))
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) %>%
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statebins(
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value_col = "share",
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ggplot2_scale_function = scale_fill_brewer,
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name = "Share of workforce with jobs lost or threatened by trade"
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) +
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labs(title = "1994-2000") +
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theme_statebins()
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```
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<img src="README_files/figure-gfm/unnamed-chunk-3-1.png" width="672" />
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``` r
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# continuous scale, legend on top
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statebins(
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adat, value_col = "avgshare01_07",
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name = "Share of workforce with jobs lost or threatened by trade",
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palette = "OrRd", direction = 1
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) +
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labs(x="2001-2007") +
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theme_statebins(legend_position="top")
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```
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<img src="README_files/figure-gfm/unnamed-chunk-3-2.png" width="672" />
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``` r
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# continuous scale, no legend
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statebins(adat, value_col = "avgshare08_12", palette = "Purples") +
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labs(x="2008-2010") +
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theme_statebins(legend_position = "none")
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```
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<img src="README_files/figure-gfm/unnamed-chunk-3-3.png" width="672" />
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``` r
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# mortality data (has Puerto Rico)
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# from: http://www.cdc.gov/nchs/fastats/state-and-territorial-data.htm
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dat <- suppressMessages(read_csv(system.file("extdata", "deaths.csv", package="statebins")))
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statebins(dat, value_col = "death_rate", name="Per 100K pop") +
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labs(title="Mortality Rate (2010)") +
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theme_statebins()
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```
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<img src="README_files/figure-gfm/unnamed-chunk-3-4.png" width="672" />
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``` r
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# fertility data
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statebins(dat, value_col="fertility_rate", name="Per 100K pop", palette="PuBuGn") +
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labs(title="Fertility Rate (2010)") +
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theme_statebins()
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```
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<img src="README_files/figure-gfm/unnamed-chunk-3-5.png" width="672" />
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``` r
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# manual - perhaps good for elections?
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election_2012 <- suppressMessages(read_csv(system.file("extdata", "election2012.csv", package="statebins")))
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mutate(election_2012, value = ifelse(is.na(Obama), "Romney", "Obama")) %>%
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statebins(
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font_size=4, dark_label = "white", light_label = "white",
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ggplot2_scale_function = scale_fill_manual,
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name = "Winner",
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values = c(Romney = "#2166ac", Obama = "#b2182b")
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) +
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theme_statebins()
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```
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<img src="README_files/figure-gfm/unnamed-chunk-3-6.png" width="672" />
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### Rounded rects\!
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``` r
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data(USArrests)
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USArrests$state <- rownames(USArrests)
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statebins(USArrests, value_col="Assault", name = "Assault", round=TRUE) +
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theme_statebins(legend_position="right")
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```
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<img src="README_files/figure-gfm/unnamed-chunk-4-1.png" width="672" />
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### All the “states”
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`statebins` now has PR, VI & NYC (by name or abbreviation) so you can
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use them, too:
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``` r
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library(statebins)
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library(tidyverse)
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library(viridis)
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data(USArrests)
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# make up some data for the example
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rownames_to_column(USArrests, "state") %>%
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bind_rows(
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data_frame(
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state = c("Virgin Islands", "Puerto Rico", "New York City"),
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Murder = rep(mean(max(USArrests$Murder),3)),
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Assault = rep(mean(max(USArrests$Assault),3)),
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Rape = rep(mean(max(USArrests$Rape),3)),
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UrbanPop = c(93, 95, 100)
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)
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) -> us_arrests
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statebins(us_arrests, value_col="Assault",
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ggplot2_scale_function = viridis::scale_fill_viridis) +
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labs(title="USArrests + made up data") +
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theme_statebins("right")
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```
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<img src="README_files/figure-gfm/unnamed-chunk-5-1.png" width="672" />
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