Introduction

choroplethr v3.0 is now available on github. You can get it by typing

# install.packages("devtools")
library(devtools)
install_github('arilamstein/[email protected]')

Version 1.3.0 has two new features:

1. Data frame df_zip_demographics contains eight demographic statistics about each ZIP Code Tabulated Area (ZCTA) in the US. Data comes from the 2013 5-year American Community Survey (ACS).
2. Function ?get_zip_demographics will return a data.frame with those same statistics from an arbitrary ACS.

Data

Here is how to access the data:

library(choroplethrZip)
data(df_zip_demographics)

?df_zip_demographics
colnames(df_zip_demographics)
 [1] "region" "total_population" "percent_white" 
 [4] "percent_black" "percent_asian" "percent_hispanic" 
 [7] "per_capita_income" "median_rent" "median_age"

summary(df_zip_demographics[, "total_population"])
 Min. 1st Qu. Median Mean 3rd Qu. Max. 
 0    721     2802   9517 13000   114700

Mapping the Data

Here is a program which will create national maps of the data:

# for each column in the data.frame
for (i in 2:ncol(df_zip_demographics))
{
 # set the value and title
 df_zip_demographics$value = df_zip_demographics[,i]
 title = paste0("2013 ZCTA Demographics:n",
                colnames(df_zip_demographics[i]))

 # print the map
 choro = zip_choropleth(df_zip_demographics, title=title)
 print(choro)
}

Note that national zip maps can take a few minutes to render. Here is the output.

New Vignette

Additionally, I have created a new vignette about these features.