My LinkedIn News (spam?) feed just flashed an interesting choropleth of housing price changes across states (House Prices in Sep 2016 relative to pre-2008 peak)
I'll try to replicate something similar using FHFA data available here
For ease, I'm actually plotting the Price Index itself for Q3-2016 for purchase-only transactions. choroplethr & choroplethrMaps are the packages that make this job really easy!
I use stringdist for some fuzzy matching to cater to the package requirements. Yeah! My sweet little AI tool! :-) ... any it actually works perfectly! ;-)
Here is the output and it is amazing to be able to produce such a neat graphic with so little code!
TODO: I'll revisit this for a lot of analysis that can done from this wealth of information as I find time
Here is the code!
require("data.table") dt <- fread("data/HPI_master.csv") # Let us get the state level data for purchase-only transactions dt <- dt[yr==2016][level=="State"][period == 3][hpi_flavor == "purchase-only"] # Credit: https://cran.r-project.org/web/packages/choroplethr/vignettes/b-state-choropleth.html library(choroplethr) library(choroplethrMaps) # install.packages('stringdist') require("stringdist") standard_states <- state.regions$region dt[,state_num:=amatch(place_name, standard_states, maxDist = 5)] dt[,state_final:=standard_states[state_num]] dt[,region:=state_final] dt[,value:=as.numeric(index_nsa)] state_choropleth(dt)