#Get required mapping packages
install.packages(c("choroplethr", "choroplethrMaps")) 
library(choroplethr)
library(choroplethrMaps)

#Pull data from Census Bureau API
data_web<-readLines("http://api.census.gov/data/2014/acs5/profile?get=NAME,DP03_0062E,DP03_0065E,DP03_0067E,DP03_0069E,DP03_0071E,DP03_0073E&for=county:*",warn="F")

#Clean up the data, get rid of \\
temp1<-gsub("[^[:alnum:], _]", '', data_web)

#Split string by ",", i.e. expandes single element into many 
temp2<-strsplit(temp1,",")

#Need to realign header row as "," was used to seperate County Name and State, but header only had Name element
temp2[[1]]<-c(temp2[[1]][1],"State",temp2[[1]][2:9])

#Using do.call() to iterate through list elements a data.frame, note skip 1st one as it contains header information
data <- as.data.frame(do.call(rbind, temp2[-1]), stringsAsFactors=FALSE)
#Grab header information and assign variable names to data.frame
names(data) <- temp2[[1]]

#Get rid of Puerto Rico
data <- data[data$state != "72",]

####################################
#Plotting...
#The county_choropleth() needs
#  1. region column: state fips + county fips; type = numeric
#  2. value column: the data being plotted; type = numeric
####################################

#Create modified data.frame with only two columns; set value to column being plotted
plot.data<-data.frame(region=paste(data[,9],data[,10],sep=""),value=data[,3], stringsAsFactors=FALSE)

#Forcing numeric data type
plot.data<-data.frame(region=as.numeric(plot.data[,1]),value=as.numeric(plot.data[,2]))

#Creat plot using county_choropleth() function
county_choropleth(plot.data,title="Median Household Income ")